Publications

Résumé : Abstract : Resumen : Dans cette étude, nous évaluons par modélisation numérique les apports énergétiques susceptibles de se produire dans une structure de chaussée routière hybride revêtue d'une couche de roulement semi-transparente ou opaque collée sur une couche de base poreuse, siège d'une circulation de fluide caloporteur. Les études numériques conduites proposent une résolution couplée de différents phénomènes thermiques : diffusion/convection dans le cas d'une chaussée drainante opaque en surface, et diffusion/convection/radiation pour une chaussée avec un revêtement semi-transparent. Les systèmes d'équations couplées sont résolus numériquement à l'aide de la méthode des éléments finis. Ce modèle a été développé directement sur un noyau Matlab c. Une discussion sur les résultats obtenus est proposée suivie d'une conclusion et de perspectives.

Résumé : Abstract : Resumen : L'étude présentée vise à optimiser la quantité d'énergie à apporter à une route solaire hybride pour éviter la formation de verglas en surface. La loi de commande optimale étudiée s'appuie sur un modèle multiphysique aux éléments finis, élaboré pour calculer le champ de température dans la structure dans des conditions environnementales variables. Une pénalisation des périodes de gel à la surface est introduite et l'énergie à fournir au système pour l'en préserver est calculée à partir de la méthode de l'état adjoint. Les résultats obtenus pour trois localisations en France (i.e. climats) sont discutés et analysés. Nomenclature B luminance énergétique d'un corps noir [W.m −2 .sr −1 ] h coefficient d'échange [W.m −2 .K −1 ] k conductivité thermique [W.m −1 .K −1 ] L luminance énergétique [W.m −2 .sr −1 ] n normale extérieure t temps [s] T température [K] T min seuil de température [K] ε émissivité κ coefficient d'absorption [m −1 ] λ longueur d'onde [µm] Ω domaine spatial étudié Φ s flux solaire [W.m −2 ] ρc capacité thermique [J.m −3 .K −1 ] σ coefficient de diffusion [m −1 ] ϑ direction dans la sphère unité a , c indices relatifs à l'air et au ciel ν fréquence [Hz]

Résumé : Abstract : Resumen : Ces travaux portent sur l’estimation conjointe de la température de surface et de l’émissivité d’objets observés par thermographie infrarouge in-situ. La conversion du flux radiatif en température se heurte au manque de connaissance des propriétés radiatives de la scène réelle et en particulier de l’émissivité. L’éclairement reçu par la caméra depuis une cible virtuelle composée de quatre matériaux connus est simulé. Ensuite, une comparaison de quatre méthodes statistiques pour estimer simultanément l’émissivité et la température et ainsi évaluer leur sensibilité est proposée.

Résumé : Abstract : Resumen : Cette étude s’intéresse à l’évaluation et à l’amélioration de solutions d’instrumentation thermique pour la surveillance long terme d’infrastructures de transport de nouvelle génération. Un site d’essais a été équipé de thermocouples et d’un système de thermographie infrarouge couplé au suivi de paramètres environnementaux. Une méthode de reconstruction spatiale des images infrarouges est présentée. Les donnéee de mesure acquises sur site, puis post-traitées, sont analysées sur le plan temporel. Une conclusion sur les résultats obtenus et des perspectives sont proposées.

Résumé : Abstract : Resumen : Last decade, the need for wireless sensors solutions as core-solutions of Structural Monitoring gained in interest. The cost of wireless devices compared to the cost of wiring important structures (bridges, energy-plants,...) is attractive. Most of recent development in WSN domain focused on energy (saving or harvesting), on wireless protocols, on embedded algorithms. But it is a fact that, most of monitoring applications need samples to be time-stamped. According to the application, the wished time resolution could be up to one second for automation monitoring, one millisecond for vibration, one microsecond for acoustic monitoring, one nanosecond for electricity or light propagation... The consequence for a Wireless network of electronic nodes is that, by nature, no common signal could physically provide a synchronization top. But, as each electronic device, a wireless sensor time-base uses a timer incremented by a quartz whose initial value is theoretical up to some p.p.m. and whose period drift on time because of age, temperature,... Two kind of solutions could be regarded : a synchronization signal provided by the wireless protocol itself; an absolute synchronization from a referential source such as: GPS, Frankfurt clock, Galileo,... In the first way, it will be demonstrated the poor accuracy and the need of energy such a mechanism offers. In the second way, the article will details how a deterministic (Universal Time), accurate and resilient algorithm has been implemented. The article also provides specific results of application on acoustic monitoring system and electricity propagation where the accuracy of a WSN has reached up to 10 nanosecond UT. Consequence on energy consumption of this algorithm are given with a description of future works to improve the energy balance while keeping the device sober and synchronized.

Résumé : Abstract : Resumen : In order to ensure safe driving without human supervision the autonomous vehicles are using a wide range of sensors as cameras, lasers, lidar to evaluate the road scene and to measure the vehicle trajectory. The vehicle weight is of critical importance since it affects both braking dynamics and stability in curves. This total weight depends on the number of occupants and goods or luggage, so it has to be dynamically estimated, at least at each traveling start. The literature review indicates that some infrastructure-based sensors exist but tire related systems are preferable if the vehicles can start routes at indefinite points. In this work an experimental system is developed to estimated the load applied to a non rolling tire with several concurrent sensors. First the elongation of the tire to road contact patch is estimated by the means of an internal optical fiber sensor based on Rayleigh scattering interferometry, since this elongation is related to the applied load according to literature results. A laser sensor situated inside the tire is giving the tire sidewalls defection which is related to applied load too. At last tire to road contact patch length and width are estimated by using Fuji pressure sensible paper. As a results for loads of 2.8 to 4.8 kN the optical sensor and the laser sensor are leading to load estimation error lower than 3%. Moreover the estimated tire contact patch is confirming the tire belt elongation estimated by the optical fiber sensor. In perspective the two measurements from optical fiber and laser could be used by autonomous vehicles in order to have a redundant load estimation for one or several wheel, under vehicle symmetry hypothesis.

Résumé : Abstract : Resumen : This article aims at modeling the WIM sensor electrical behavior to provide a better understanding of the mechanical and electrical proprieties of piezoelectric sensors. The model is considered in the frequency domain, supposing any sinusoidal solicitation with constant frequency or any other type of solicitation. Tests, having real WIM sensors placed on the pavement of a test track at IFSTTAR/ Nantes was used to verify the nature of the electro-mechanical (EM) behavior of the real sensors over punching, flexural and extension effects. Also, two different pavement numerical simulations deliver the mechanical response using linear elasticity and viscoelastic proprieties. The output of these two simulations are compared with two WIM signals obtained at same load and speed at two different temperature conditions.

Résumé : Abstract : Resumen : The scattering of guided waves through a coupling region is a crucial information when studying waveguides. In this paper, the second strain gradient theory (SSG) is used to describe wave transmission and reflection in a three-dimensional micro-sized medium. First, the constitutive relation of 3D SSG model is derived while six quintic Hermite polynomial shape functions are used for the displacement field. Then Hamilton's principle is used for the weak formulation of the unit-cell's stiffness matrix finite element stiffness, mass matrices and force vector. Eventually the wave diffusion (i.e. including reflection and transmission coefficients) are computed and discussed for various coupling conditions.

Résumé : Abstract : Resumen : The increasing use of the baffled-rotary kiln equipment in many innovative materials processing industrial applications suggests examining the heat transfer phenomena in order to improve the multi-phase flow modeling. Their development and use will be relevant for tackling the current energy issues. The heat transfer models available for the rotary kiln in the literature are, for now, not enough efficient for the baffled-rotary kiln case. The present paper is aimed at suggesting a wall heat transfer correlation for the rotary kilns with secondary inlet. The experimental thermal data acquired within large-scale rotary drum applied to the asphalt concrete materials production, are remained in order to give rise new issues. These latter results are connected to a visualization campaign performed at the pilot-scale in order to assess the transversal distribution of the granular materials. Their analysis suggest a more appropriate physical modeling of the wall heat transfer path leading to transform the classical correlation of type Nu=f(Re,Pr) in a new expression of type Nu=f(Re,St) based on a inventory corresponding to the hot and cold fluxes flowing within the baffled-rotary kiln. Thus, the introduction of the Stanton number (St) in the wall heat transfer correlation is compared with the experimental Nusselt numbers calculated from the inner heat transfer coefficients measured in the large-scale baffled-rotary kiln. This expression is found more convenient for the baffled-rotary kiln application.

Résumé : Abstract : Resumen : Intelligent transportation systems use GNSS receivers as basic technological components. In urban applications one faces the problem of GNSS multipath and particularly of non-line-of-sight (NLOS) satellites. The development of GNSS receiver technologies for mass market encompasses the capability NLOS satellites processing by innovative techniques, not only based on the Signal to Noise Ratio, but also on vision or city model. This is particularly needed for urban positioning of cars for applications which require high accuracy and integrity, typically driving automation. This article deals with the detection of NLOS satellites among those tracked by an automotive-range receiver. We aim at developing a method jointly based on the analysis of video stream and a 3D map model of the environment. The article provides a literature review, an evaluation of some existing techniques and a preliminary analysis of the implementation of the retained algorithm on a prototype developed in the frame of a European H2020 "Fundamental Elements call" project.

Résumé : Abstract : Resumen : The lane-level localization of vehicles with low-cost sensors is a challenging task. In situations in which Global Navigation Satellite Systems (GNSSs) suffer from weak observation geometry or from the influence of reflected signals, the fusion of heterogeneous information presents a suitable approach for improving the localization accuracy. We propose a solution based on a monocular front-facing camera, a low-cost inertial measurement unit (IMU), and a single-frequency GNSS receiver. The sensor data fusion is implemented as a tightly coupled Kalman filter that corrects the IMU-based trajectory with GNSS observations while employing European Geostationary Overlay Service correction data. Further, we consider vision-based complementary data that serve as an additional source of information. In contrast to other approaches, the camera is not used to infer the motion of the vehicle, but rather for directly correcting the localization results under the usage of map information. More specifically, the so-called camera-to-map alignment is done by comparing virtual 3D views (candidates) created from projected map data with lane geometry features that are extracted from the camera image. One strength of the proposed solution is its compatibility with state-of-the-art map data, which are publicly available from different sources. We validate the approach on real-world data recorded in The Netherlands and show that it presents a promising and cost-efficient means to support future advanced driver assistance systems

Résumé : Abstract : Resumen : Load estimation of wheels, especially for heavy vehicles, is of importance for several reasons. First safety imposes to respect loading limits for a given tire, but the variety of road infrastructures or bridges passed by a vehicle are defining constraints of larger scales as structure resistance or pavement durability. Moreover, multiple-wheels load estimation may be an efficient verification mean of the loading uniformity of goods inside a heavy vehicle. All these reasons are justifying the interest for a continuous estimation of load for each wheel. In this context, this work aims at contributing to the development of an intelligent tire solution, able to estimate the loading applied on a wheel from the elongation measurement of the tire-to-road contact patch. As a first step of proof of concept, without regarding durability, this measurement has been done with a tire instrumented with a longitudinal, circumferential optical fiber. Measurement on a static test wheel has shown the relevance of the method to detect slight elongation of the contact patch, surrounded by compression of nearby tire areas. The Distributed Optic Fiber (DOF) measurement, widely used in the structural health monitoring domain (SHM), has been related to the force applied to the wheel, by a near linear relation, on the experienced domain of 70mm to 110 mm for the contact length and 1.1 to 2.6 kN for the vertically applied force. As a result, demonstration is done that an intelligent tire could provide a relevant information on a given wheel load of a vehicle. The optimization of the experimental setup should lead to a robust system, usable continuously on heavy vehicles, to detect harmful loading displacements or to qualify adequacy between vehicle load and road infrastructure capacity.

Résumé : Abstract : Resumen : In a context of decreasing resources and of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. This work aims to demonstrate that road energy demand and associated pollutant emissions can be reduced by working out minor optimization of road infrastructure itself. For this to happen, a simple eco-driving potential criterion is built upon infrastructure parameters such as slopes and sight distances. This criterion aims to detect Misplaced Speed-sectioning Positions (MSP) with regard to the Starting Point of Deceleration (SPD); with speed-sectioning being the succession of speed changes along a given route. An enhanced energy waste formulation is then developed to quantify the vehicles energy waste due to misplaced road-signs. Thirdly, a traffic simulation constitutes a framework for energy evaluation; considering a full flow of vehicles, based on real traffic data, and by modeling several driver behaviors. Simulation results show that a significant fuel reduction of up to 5.5% can be achieved locally, simply by moving a road sign, for rural areas and without degrading road safety.

Résumé : Abstract : Resumen : Recent advances in efficient variance computation of modal parameter estimates from the output-only subspace-based identification algorithms make the modal parameter variance a practical modal indicator, indicating the accuracy of the estimation. A further modal indicator is the Modal Assurance Criterion (MAC), for which a recently developed uncertainty quantification scheme estimates the variance at a fixed model order. The Modal Phase Collinearity (MPC) is another popular indicator, for which an uncertainty scheme is currently missing. Unlike other modal parameters, which are Gaussian distributed, estimates of MAC and MPC are close to the border of their respective distribution support and cannot be approximated as a Gaussian random variable. This paper addresses the respective uncertainty quantification of MAC and MPC. The results are validated in the context of operational modal analysis (OMA) of a spring mass system.

Résumé : Abstract : Resumen : The transfer function of a linear system is defined in terms of the quadruplet of matrices (A, B, C, D) that can be identified from input and output measurements. Similarly these matrices determine the state space evolution for the considered dynamical system. Estimation of the quadruplet has been well studied in the literature from both theoretical and practical points of view. Nonetheless, the uncertainty quantification of their estimation errors has been mainly discussed from a theoretical viewpoint. For several output-only and input/output subspace methods, the variance of the (A, C) matrices can be effectively obtained with recently developed first-order perturbation-based schemes. This paper addresses the estimation of the (B, D) matrices, and the remaining problem of the effective variance computation of their estimates and the resulting transfer function. The proposed schemes are validated on a simulation of a mechanical system.

Résumé : Abstract : Resumen : The concept of value of information (VoI) enables quantification of the benefits provided by structural health monitoring (SHM) systems – in principle. Its implementation is challenging, as it requires an explicit modelling of the structural system’s life cycle, in particular of the decisions that are taken based on the SHM information. In this paper, we approach the VoI analysis through an influence diagram (ID), which supports the modelling process. We provide a simple example for illustration and discuss challenges associated with real-life implementation.

Résumé : Abstract : Resumen : This paper presents the design of a novel Ground-Penetrating Radar (GPR) test site that has been integrated into the mini-city demonstrator Sense-City located at University Paris-Est (France). This test site provides several sources of measurement interest expressed by the presence of a multilayered soil with significant dielectric contrasts, and various dielectric pipes and blades buried at various depths in trenches filled with a backfill soil different from the natural soil. This paper presents experimental Bscans associated with the pipe zone acquired by three different GPR systems at frequencies ranging from 300 MHz to 1.5 GHz. The interpretation and comparison of the raw Bscans have allowed to characterize the dielectric properties of the soil layers, and to detect the hyperbola signatures of the buried pipes. The results of this study will help to guide future developments on polarization, operating frequency and signal processing to extract parameters (orientation, dielectric characteristics, position and size) associated with pipes.

Résumé : Abstract : Resumen : Afin de choisir les paraffines les mieux adaptées pour lutter contre les îlots de chaleur urbains, trois paraffines vendues comme ayant des températures de fusion de 28, 31 et 35°C ont été caractérisées en Analyse ThermoGravimétrique et Analyse Thermique Différentielle. La conductivité et la diffusivité thermique des paraffines à l’état solide ont également été mesurées. Les paraffines ont une bonne stabilité thermique et permettent de stocker de grandes quantités d’énergie thermique dans une large gamme de température. La particularité des paraffines est l’existence de phases rotatoires intermédiaires entre la phase liquide et la phase solide qui sont responsables des dédoublements des pics de cristallisation pendant leur refroidissement.

Résumé : Abstract : Resumen : Transportation and infrastructure sectors face difficulties during the winter season. When road's temperature drops below 3°C, the risk of ice formation increases, leading to reduced traction and snow accumulation. The use of phase change materials (PCMs) can be a potential solution. However, it is important to consider various factors when selecting PCMs, including phase change temperature, latent heat, and long-term stability. In this study, our focus was on RT5HC, a paraffin with a melting temperature of 5°C. Various thermal analysis techniques were employed to characterize its thermophysical properties, particularly its thermal stability and latent heat. The results of the study demonstrated that the RT5HC paraffin reveals good thermal stability for the intended application. Moreover, its high latent heat provides an advantage for thermal energy storage. These findings contribute to advancements in the field of PCMs and offer promising prospects for their use in preventing ice formation and freezing during winter periods.

Résumé : Abstract : Resumen : Similarly to other industrial areas, there is a strong interest for the use of bonded FRP (Fiber Reinforced Polymers) repair or reinforcement for steel structures in the case of offshore applications. However, the reliability of the adhesively bonded (FRP) shall stand as high as steel renewal, this requires additional developments, in particular, a complete understanding of the repair mechanical strength which depends on material and interfacial properties. Fracture mechanics is an interesting approach to assess the risk to undergo interlaminar fracture or steel to adhesive interfacial disbonding failure. The experimental determination of the required design values for this an approach (critical toughness) are generally obtained using common tests such as Double Cantilever Beam (DCB), End Notched Flexure (ENF) or Mixed Mode Bending (MMB) tests. These tests require a precise crack length monitoring that is currently carried out using visual observation or Digital Image Correlation (DIC) on the flank of the sample. This may induce error in crack length measurement especially if the crack doesn't remain straight during the test. The paper presents a study of crack front monitoring by a distributed optical fiber as an alternative to the standard techniques to monitor crack front and to determine the critical toughness in mode I and II through respectively, DCB (Double Cantilever Beam) and ENF (End Notched Flexure) tests. Firstly, the issues related to the use of this continuous optical fiber are raised (insertion, precision resolution, measurement noise, exploitation methodologies). Then, some experimental investigations on ENF and DCB tests are presented and analyzed using the proposed methodology to monitor crack propagation using the optical fiber strain measurement. The obtained results are compared, focusing on the proper determination of the critical toughness of the adhesive. These results show that an optical fiber bonded on the surface of the sample can be used to measure and follow the crack propagation during the test which simplifies and adds precision to the standardize critical toughness computation method.

Résumé : Abstract : Resumen : The floating production, storage and offloading units (FPSO) being generally in a tropical area, makes corrosion a fundamental ageing problem of these steel structures. Therefore, there is a strong need for proposing repair solutions having low impact on their exploitation. The owner of these units are highly interested in the development of "cold repair" in contrast with "hot works" which require to stop the production for security risks, like adhesively bonded FRP (Fibre Reinforced Polymer) patch which requires additional development, in particular in the design step. The design of these reinforcements needs a complete understanding of the mechanical state of the patch which is based on the different materials and interfaces properties. Fracture mechanics seems an interesting option to express the mechanical state of the patch and more particularly the risk to undergo interlaminar fracture or steel interface debonding failure before materials failure. The experimental definition of the required design values for such an approach (critical toughnesses) are generally obtained with common tests such as DCB or ENF tests. The presented study is focused on the determination of the critical toughness in mode II through ENF (End Notched Flexure) test which can be done following some standards, such as ASTM D7905. A distributed optical fibre was used to verify the correct determination of the initial crack length, to determine the crack propagation during the test, and to monitor the fracture process zone length. The currently used methods, such as visual observation or Digital Image Correlation (DIC) of the crack front at the border of the sample, may indeed induce error if the crack is not straight. To compare these methods, the realized test was monitored using a distributed optical fibre placed in the centre of the lap width, in and on the specimen. Firstly, the issues related to the integration of this continuous optical fibre will be raised (insertion, precision resolution, measurement noise). Then, some experimental investigations will be described presenting different monitoring strategies using continuous optical fibre measurement and Digital Image Correlation technique (DIC). The obtained results will be analyzed focusing on the proper determination of the critical toughness of the adhesive. This will then be used to design and optimize the monitoring strategy of a wider experimental campaign.

Résumé : Abstract : Resumen : Ground Penetrating Radar (GPR) has become one of the popular Non-Destructive Testing (NDT) methods in the field of Geophysics and civil engineering applications. In this context, for applications like concrete rebars assessments, utility networks surveys, the precise localization of embedded cylindrical pipes remains still challenging due to complex geometrical and dielectric characteristics of the stratified medium. In recent years, several hyperbola-centric machines learning based novel techniques have been introduced to accomplish localization of cylindrical objects from the GPR data. In this paper, performance of Multi-layer perceptron (MLP) based Artificial Neural Networks (ANN) model combined with six statistical travel time features extracted from hyperbola were studied. The model is used to predict the velocity of the stratified medium, depth of cylindrical pipe and radius of the pipe. The approach is based on hyperbola traces emerging from a set of B-scans, whereas the shape of hyperbola highly varies with depth and radius of the pipe as well as the velocity of the medium. Hence, Finite-Difference Time-Domain (FDTD) based 2D numerical tool namely GprMax is used to simulate GPR data. A parametric comparison is also included in the performance analysis of the techniques in terms of relative error estimations against designed parameters.

Résumé : Abstract : Resumen : The Modal Assurance Criterion (MAC) is a modal indicator designed to decide whether the mode shapes used in its computation are corresponding to the same mode. During structural monitoring, it can be applied to evaluate changes in the mode shapes. When the mode shapes are estimated from measurement data, the MAC inherits their statistical properties, thus is afflicted with statistical uncertainty. The evaluation of this uncertainty is particularly relevant when the MAC estimate is close to 1, where 1 indicates equal mode shapes. In structural monitoring, it can be used to assess changes in mode shapes after early damage. While the framework for uncertainty quantification of modal parameters is well-known and developed in the context of subspace-based system identification methods, uncertainty quantification for the MAC has not been developed yet. A particular challenge for its statistical characterization is its boundedness in the interval between 0 and 1. In this paper it is shown that this boundedness yields two different distributions of the MAC estimates. The MAC computed between estimates of different mode shapes is inside the interval (0, 1), and a Gaussian approximation of its distribution is obtained. When the MAC is computed between estimates of equal mode shapes, the resultant MAC estimate is close to 1, and the classical Gaussian approximation is inadequate. In this case it is shown that the MAC estimate is linked to a quadratic form of the mode shapes, whose distribution can be approximated by a scaled and shifted χ 2 distribution. For both cases, uncertainty bounds related to the MAC estimates are established. The proposed frameworks are validated by extensive Monte Carlo simulations and then applied to evaluate mode shape changes due to damage during monitoring of the S101 Bridge.

Résumé : Abstract : Resumen : The transfer function of a linear mechanical system can be defined in terms of the quadruplet of statespace matrices (A, B, C, D) that can be identified from input and output measurements with subspace-based system identification methods. The estimation of the quadruplet has been well studied in the literature from both theoretical and practical viewpoints. Nonetheless, a practical algorithm for uncertainty quantification of its estimation errors and the uncertainty of the resultant parametric transfer function is missing in the context of subspace identification. For several output-only and input/output subspace methods, the covariance related to the matrices (A, C) and to the resulting modal parameters can be effectively obtained with recently developed first-order perturbation-based schemes, while the corresponding uncertainty quantification for the input-related matrices (B, D) is missing. In this paper, explicit expressions for the covariance related to matrices (B, D) are developed, and applied to the covariance estimation of the resulting transfer function. The proposed schemes are validated on simulated data of a mechanical system and are applied to laboratory measurements of a plate.

Résumé : Abstract : Resumen : The Modal Phase Collinearity (MPC) is a modal indicator designed to decide whether the mode shape used in its computation is a real or complex-valued vector. Its estimate inherits the statistical properties of the corresponding mode shape estimate. While the statistical framework for the uncertainty quantification of modal parameters is well-known and developed in the context of subspace-based system identification methods, uncertainty quantification for the MPC estimate has not been carried out yet. In this paper, the uncertainty quantification of the MPC estimates is developed when the corresponding mode shapes are complex-valued vectors. In this case, the theoretical value of the MPC is strictly lower than 1 and it is shown that the distribution of the MPC estimate can be approximated as Gaussian. The computation of its variance and the resulting confidence intervals of the MPC estimate are developed. The proposed framework is validated in Monte Carlo simulations and illustrated on experimental data of an offshore structure.

Résumé : Abstract : Resumen : The quantification of statistical uncertainty in modal parameter estimates has become a standard tool, used in applications to, e.g., damage diagnosis, reliability analysis, modal tracking and model calibration. Although efficient multi-order algorithms to obtain the (co)variance of the modal parameter estimates with subspace methods have been proposed in the past, the effect of a misspecified model order on the uncertainty estimates has not been investigated. In fact, the covariance estimates may be inaccurate due to the presence of small singular values in the supposed signal space. In this paper we go back to the roots of the uncertainty propagation in subspace methods and revise it to account for the case when a part of the noise space is erroneously added to the signal space. What is more, the proposed scheme adapts a different approach for the sensitivity analysis of the signal space, which improves the numerical efficiency. The performance is illustrated on an extensive Monte Carlo simulation of a simple mechanical system and applied to real data from a bridge.

Résumé : Abstract : Resumen : Higher order gradient elasticity theories are widely applied to determine the wave propagation characteristics of microsized structures. The novelty of this paper, firstly, is using the Second Strain Gradient (SSG) theory to explore the mechanism of a micro-sized 2D beam grid. The strong formulas of continuum model including governing equations and boundary conditions are derived by using the Hamilton principle. Then, a valuable long-range Lattice Spring Model (LSM) is elaborated, providing a reasonable explanation for the model based on SSG theory. The dynamic continuum equations from LSM are calculated through the Fourier series transform approach. Finally, the dynamic properties of 2D beam grid are analyzed within the Wave Finite Element Method (WFEM) framework. The band structure and slowness surfaces, confined to the irreducible first Brillouin zone, are studied in frequency spectrum. The energy flow vector fields and wave beaming effects are discussed through SSG theory and Classical Theory (CT) of elasticity. The results show that the proposed approach is of significant potential for investigating the 2D wave propagation characteristics of complex micro-sized periodic structures.

Résumé : Abstract : Resumen : For joint estimation of states and parameters in time varying time-delay systems (TDS) involving both distributed and lumped time-delays, a general approach is proposed in this paper to transforming existing (non adaptive) observers to adaptive observers. In addition to the convergence conditions of the considered existing observers, a persistent excitation condition is introduced in order to ensure the convergence of parameter estimation. In contrast to implicitly formulated convergence conditions, which are usually assumed jointly for both state and parameter estimations in most TDS adaptive observers, the persistent excitation condition in the proposed approach is explicitly formulated and decoupled from the conditions initially assumed for state estimation.

Résumé : Abstract : Resumen : Damage localization in civil or mechanical structures is a subject of active development and research. In this paper, vibration measurements and a finite element model are used to locate loss of stiffness in a steel frame structure at the University of British Columbia. Damage localization is not very well developed so far and few methods show promising properties in practice. Among them, the Stochastic Dynamic Damage Locating Vector (SDDLV) approach has interesting capabilities. In this paper, it is compared to a sensitivity based approach developed by the authors. Both approaches have in common to be built on the estimated transfer matrix difference between reference and damaged states. Both methods are tested for localization and quantification on the Yellow Frame structure at the University of British Columbia.

Résumé : Abstract : Resumen : Deaf pilots in France are currently allowed to fly planes with the help of a second pilot handling voice and radio communication. Yet, they are not allowed to pilot independently. Fans4All is an association that aims at making aeronautics more accessible to pilots who are hearing or speaking impaired (HSI). In this paper we present our experience as a multidisciplinary design team (including two HSI pi-lots) working towards this goal. We present the current and past steps to develop a Multimodal Sensory Communication Device (MSCD) composed of a touchscreen tablet and a haptic jacket, as well as the visual vocabulary to define messages between HSI pilots and air traffic controllers. Moreover, we present our approach combining quantitative and qualitative methods for evaluation. We hope that our work will help making aeronautics more accessible to people with impairments.

Résumé : Abstract : Resumen : This work presents a novel method for simulating the behavior of solid objects with the Lattice Boltzmann Method (LBM). To introduce and validate our proposed framework, comparative studies are performed for computing the static equilibrium of isotropic materials. Remembering that the LBM has strong theoretical foundations in the Boltzmann equation; this latter is firstly adjusted to solid motions, through its Boltzmann-Vlasov special case. This is indeed the case when combined with a suitable mean-field external force term to set a reliable solid framework. Secondly, a library is built and plugged on the top of the well-known Parallel Lattice Boltzmann Solver (PaLaBoS) library. Numerical implementations based on the previous equation of motion for solids are led in a non-intrusive manner so as to present results with an easy and flawless reproducibility. A newly designed Lattice Boltzmann Method for Solids (LBMS) is exhibited through a few key algorithms, showing the overall operation plus the major improvements. Efficiency, robustness and accuracy of the proposed approach are illustrated and contrasted with a commercial Finite Element Analysis (FEA) software. The obtained results reveal considerable potential concerning static and further dynamic simulations involving solid constitutive laws within the LBM formalism.

Résumé : Abstract : Resumen : Underplatform dampers (UPDs) are traditionally used in aircraft engines to reduce the risk of high cycle fatigue. By introducing friction in the system, vibrations at resonance are damped. However, UDPs are also the source of nonlinear behaviours making the analysis and the design of such components complex. The shape of such friction dampers has a substantial impact on the damping performances, topology optimisation is seldomly utilised-particularly for nonlinear structures. In the present work, we present a numerical approach to optimise the topology of friction dampers in order to minimise the vibration amplitude at a resonance peak. The proposed approach is based on the Moving Morphable Components framework to parametrise the damper topology, and the Efficient Global Optimisation algorithm is employed for the optimisation. The results demonstrate the relevance of such an approach for the optimisation of nonlinear vibrations in the presence of friction. New efficient damper geometries are identified in a few iterations of the algorithm, illustrating the efficiency of the approach. Results show that the most efficient geometry divides the vibration amplitude at resonance by 3, corresponds to a lower mass (80%) and a smaller frequency shift compared to the non-optimised case. More generally, the different geometries are analysed and tools for clustering are proposed. Different clusters are identified and compared. Thus, more general conclusions can be obtained. More specifically, the most efficient geometries correspond to geometries that reduce the mass of the damper and increase the length of the contact surface. Physically, it corresponds to a reduction of the initial normal contact pressure, which implies that the contact points enter stick/slip earlier, bringing more damping. The results show how topology optimisation can be employed for nonlinear vibrations to identify efficient layouts for components.

Résumé : Abstract : Resumen : In turbomachinery, components are pushed to their limits to meet more stringent specifications in order to increase their performances. In this context, structural topology optimisation is a promising technology as it improves substantially the mechanical properties while drastically reducing the mass. With the coming of additive manufacturing, optimised geometry can be manufactured making this technology even more attractive. The aim of this work is to investigate the potential of topology optimisation to optimise a full bladed disc to improve its dynamic performances in terms of mass, stress and modal coincidences. The topology of a 3D-Finite Element Model of an academic bladed disc is optimised in this work and experimental validation is expected. So first, the disc is designed to fit in the test-rig and the mechanical integrity of the 3D-printed disc is experimentally verified. Second, the topology of the blades is optimised. Based on a trial-and-error process, the appropriate topology optimisation problem properties for vibration optimisation are identified. Thus, adding a static force at the blade tip forces a better material distribution over the domain and increases the blade stiffness. To minimise the number of coincidences, a numerical strategy based on iterative topology optimisation simulations is proposed to identify the correct set of frequential constraints. Final results show that the mass of the blade is reduced up to 32% and the number of frequential coincidences is reduced from 11 to 4. Final geometries are 3D-printed and mounted on the disc.

Résumé : Abstract : Resumen : Pavement survey is one of the most important applications for ground penetrating radar (GPR) in civil engineering. In the case of centimeter scale of GPR waves, the influence of interface roughness cannot be neglected and should be taken into account in the radar data model. The objective of this article is to estimate the time-delay in the presence of interface roughness by GPR. Using the property of noncircular signals, we propose a modified orthogonal matching pursuit method to estimate the pavement parameters for both overlapped and nonoverlapped echoes. Compared with subspace-based methods in coherent scenarios, the proposed method can estimate the time delays of backscattered echoes without applying the cumbersome interpolation and spatial smoothing procedures, which are more practical in real applications. The performance of the proposed method is tested on both simulated and experimental data. The estimation results show the good performance of the proposed method.

Résumé : Abstract : Resumen : In civil engineering, ground-penetrating radar is widely used for road pavement survey. In contrast to the existing literature, this paper takes account of the influence of interface roughness (surface and interlayer roughness) within the scope of the data processing of radar signals. The rigorous electromagnetic method PILE (propagation inside layer expansion) provides the simulated data that show the influence of the interface roughness on the backscattered primary echoes of stratified media, the interface roughness provides a continuous frequency decay of the magnitude of the echoes. The observed frequency variations of the radar magnitude introduce some shape distortion on the radar waveform. The latter variations can be modelled by exponential function, which provides satisfactory results for a narrow bandwidth (2 GHz). An adaptation of the root-MUSIC algorithm is proposed. As a result, it is allowed to jointly estimate the time delay and the interface roughness. Then, the algorithm is tested on the data simulated by the PILE method, and numerical examples are provided to assess the performance of this algorithm. The associated results show that the proposed algorithm can estimate both the time delay and roughness parameters with a small relative error.

Résumé : Abstract : Resumen : In civil engineering, ground penetrating radar is a common technique for evaluating the structure and quality of road pavement. This paper focuses on the estimation of the time delay and interface roughness of civil engineering structure, like pavements. The influence of interface roughness is taken into account in the signal model. A modified estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm combined with an interpolated spatial smoothing technique is proposed. It allows us to jointly and efficiently estimate the time delay and interface roughness by ultrawideband radar (the upper frequency up to 8-10 GHz) with low computational complexity. The proposed algorithm is tested on both numerical and experimental data. Simulation and experimental results show the good performance of the proposed algorithm.

Résumé : Abstract : Resumen : Cet article présente un monitoring thermique conduit pendant plusieurs jours sur le tablier du pont de « Musmeci » à Potenza (Italie). L’analyse des données est conduite en exploitant la mesure de paramètres météorologiques synchronisée avec l’acquisition d’images thermiques. Une analyse par FFT, permet de détecter sur les séquences de cartes d’amplitude et de phase la structure interne du tablier. Un modèle thermique exprimé dans le domaine fréquentiel a été développé et couplé à une procédure d’estimation de paramètres. Une cartographie de la distribution spatiale de la conductivité thermique apparente est ainsi calculée puis comparée avec l’analyse d’images par approche fréquentielle.

Résumé : Abstract : Resumen : If de-icers still are the main solution to avoid black ice occurrence and snow accumulation on pavements, some alternatives based on transportation infrastructure modifications have been tested over the past years. They aim at the reduction of environmental impacts and at coping with budgets constraints and cuts, including in winter maintenance. Among existing ones, the implementation of phase changes materials (PCM) into the infrastructure was evaluated to delay the occurrence of water in its solid phase on the surface. Additional results were obtained with an asphalt concrete in simulated winter conditions, indicating a tenuous thermal effect at the surface.

Résumé : Abstract : Resumen : Transportation is undergoing a radical transformation toward a novel way of thinking about road pavement: a sustainable, multifunctional infrastructure able to satisfy mobility needs, ensuring high safety standards, low carbon impact, automated detection through smart sensors, and resilience against natural and anthropogenic hazards. In this scenario, the road could also play a role for energy harvesting, thanks to the exploitation of solar radiation. The latter can be directly converted into electricity by solar cells placed under a semitransparent layer, or it can be harvested through a calorific flowing fluid. The aim of this paper is to introduce the concept of “hybrid road,” which is able to exploit both approaches. The innovative pavement is a multilayered structure composed by a semitransparent top layer made of glass aggregates bonded together thanks to a semitransparent resin, an electrical layer containing the solar cells, a porous asphalt layer for the circulation of the calorific fluid, and finally, a base waterproof layer. The hybrid road can generate electricity, contrast the heat-island effect, exploit the harvested energy to run a heat pump for heating purposes, or facilitate road deicing during winter. The present paper details experimental data obtained through energetic tests performed with a laboratory-size prototype of the hybrid road. The results show that the prototype is able to harvest around 55.2 W through the heat-transfer fluid. Furthermore, the heat exchange between water and asphalt has a cooling effect on the entire prototype.

Résumé : Abstract : Resumen : This paper addresses how the value of damage detection information depends on key parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation.

Résumé : Abstract : Resumen : While today's galloping urbanization weighs heavily on both People and Environment, the massive instrumentation of urban spaces appears a landmark toward sustainability. Collecting massively distributed information requires the use of high-performance communication systems as well as sensors with very small ecological footprint. Because of their high sensitivity, the wide range of their observables, their energetic self-sufficiency and their low cost, micro- and nano- sensors are particularly well suited to urban metrology. A 8 years, 9 MC equipment project funded by the French 'Programme d'Investissement d'Avenir' starting in 2012, the Sense-City project will offer a suite of high-quality facilities for the design, prototyping and performance assessment of micro- and nanosensors devoted to sustainable urbanization. The scientific program of Sense-City is built around four programs, environmental monitoring, structural health monitoring, energy performances monitoring and people health and exposure monitoring. We present the activities of the consortium partners, IFSTTAR, ESIEE-Paris, CSTB, LPICM, and the prospects brought by Sense-City equipment in terms of sensor prototyping, benchmarking and operation validation. We discuss how the various sensors developed by LPICM and ESIEE (for instance conformable chemical and gas microsensors using nanomaterials at LPICM, miniaturized gas chromatographs or microfluidic lab-on-chip for particles analysis at ESIEE-Paris) can be integrated by IFSTTAR into sensors networks tested by IFSTTAR and CSTB in both lab and urban settings. The massively distributed data are interpreted using advanced physical models and inverse methods in order to monitor water, air or soil quality, infrastructure and network safety, building energy performances as well as people health and exposure. We discuss the shortcomings of evaluating the performances of sensors only in lab conditions or directly in real, urban conditions. As a solution, Sense-City will provide an environment of intermediate complexity for the testing of environmental sensors, a realistic urban test space in climatic conditions, both far more complex than clean rooms and far more controllable than actual cities.

Résumé : Abstract : Resumen : From the past decades the monitoring of civil engineering structure became a major field of research anddevelopment process in the domains of modelling and integrated instrumentation. This increasing of interest canbe attributed in part to the need of controlling the aging of such structures and on the other hand to the need tooptimize maintenance costs. From this standpoint the project Cloud2SM (Cloud architecture design for StructuralMonitoring with in-line Sensors and Models tasking), has been launched to develop a robust information systemable to assess the long term monitoring of civil engineering structures as well as interfacing various sensors anddata. The specificity of such architecture is to be based on the notion of data processing through physical orstatistical models. Thus the data processing, whether material or mathematical, can be seen here as a resource ofthe main architecture.

Résumé : Abstract : Resumen : Aerospace industry needs accurate coating thickness measurement as well as adhesion testing for preventing the corrosion of wear of metal substrates. Recently, a constant attention is focused towards the potentialities offered by non-invasive sensing techniques and their technological advancements. This communication deals with time of flight THz imaging, enhanced by a noise filtering procedure based on the Singular Value Decomposition of the data matrix. In this work, THz imaging is exploited to analyse painted steel samples in order to detect paint coating layers and provide images of them and of the interface between the coating layer and the steel substrate.

Résumé : Abstract : Resumen : Le développement de réseaux de capteurs déployables à bas coût sur des ouvrages courants présente d'importants enjeux de recherche et de développement : les sujets des capteurs sans fils, de la récupération d'énergie, et de la synchronisation comportent encore des verrous scientifiques à lever. Des projets de recherche amont aux solutions innovantes opérationnelles, cet atelier propose un aperçu des techniques de détection des pathologies des ouvrages

Résumé : Abstract : Resumen : Benzene 1,2,4,5-tetrasulfonic acid (H4B4S) was prepared in two steps starting from 1,2,4,5-Te¬tra¬chlorobenzene. Slow evaporation of an aqueous reaction mixture of H4B4S and Cu2(OH)2(CO3) led to light green single crystals of [Cu2(B4S)(H2O)8] • 0.5 H2O. X-ray single crystal investi¬ga¬tions revealed the compound to be triclinic [P-1, Z = 1, a = 710.0(1), b = 713.7(1), c = 1077.1(2) pm, α = 98.41(2)°, β = 102.91(2)°, γ = 100.69(2)°]. In the crystal struc-ture the Cu2+ ions are coordinated by four water molecules and two monodentate sulfo¬na¬te anions yielding a tetragonally distorted [CuO6] octahedron. The anions are connected to fur-ther copper ions leading to ladder shaped chains running along the [110] direction. Accor¬ding to DTA/TG investi¬gations the dehydration of the compound is finished at 240°C and the de-com¬position of the anhydrous sulfonate starts at 340°C.

Résumé : Abstract : Resumen : Bayesian filtering based approaches for diagnosis of structural damage have been widely employed in structural health monitoring (SHM) research. The approach however may lead to an inaccurate alarm/decision due to the presence of faulty sensor/s. Nevertheless, sensor faults are inevitable during real field SHM in which sensor may malfunction or get detached from the structural surface, registering completely irrelevant information as measurement. Eventually, such erroneous information induce error in the estimation which leads to an inaccurate, sometimes divergent and impractical solution. The current study deals with Bayesian filtering based structural damage detection in the presence of one or multiple (consecutive) sensor faults. The damage detection is addressed with joint state-parameter estimation approach while a switching filtering strategy is employed for sensor fault detection. Switching approach employs multiple possible sensor fault models which are subsequently integrated to the measurement model of the joint estimation approach. The selection of the competent model (/switching between model ensembles) is undertaken recursively based on their likelihood against measured response. The proposed approach is tested on a numerical lumped mass model of a shear frame building, followed by a laboratory experiment on a cantilever beam. It has been perceived that estimation of health for structures measured with faulty sensors can actually lead to a false (positive and negative) alarm which can, however, be avoided by the employment of the proposed approach. The performance of the proposed approach is further established for healthy and damaged system with pre-existing and sudden sensor faults.

Résumé : Abstract : Resumen : Le vieillissement des structures de génie civil, leur utilisation de plus en plus intensive et les sollicitations environnementales nécessitent de développer de nouveaux outils de suivi et diagnostic. Apparu avec l’avènement des technologies de l’information et de la communication, le « Structural Health Monitoring » (SHM), intègre les méthodes de contrôle au sein de systèmes d’information complets permettant, par exemple, l’utilisation de l’historique des mesures. Au sein d'I4S, équipe de recherche commune de l'Inria et de l'Ifsttar, le projet Cloud2SM a pour objectifs d’étudier et proposer une architecture décentralisée et normalisée permettant le suivi sur le long terme des structures in-situ. Il associe une approche capteurs et modèles. Le logiciel Cloud2IR, un des composants de cette architecture, a été conçu et développé au sein de ce projet. Il permet de mettre en œuvre sur site extérieur, de manière autonome, des acquisitions de données issues de caméras infrarouges et d’autres capteurs de suivi des paramètres environnementaux. En plus de découpler la gestion des capteurs et leurs données en s’appuyant sur l'utilisation d'un « framework » dédié, Cloud2IR à la particularité d'encapsuler automatiquement les données dans des formats normalisés et/ou orientés web services. Intégré à une architecture réseau nationale, Cloud2IR est déployé et testé, depuis mi-2015, sur différents sites (Nantes, Rennes et Paris). Les essais conduits associent des mesures par thermographie infrarouge pour le suivi thermique plein champ avec des capteurs environnementaux. Après avoir exposé la philosophie de Cloud2IR ainsi que la nécessité de standardisation des larges volumes de données, un exemple de déploiement sur site sera présenté.

Résumé : Abstract : Resumen : En 2013, une structure de voie ferroviaire innovante a été construite en France. Il s’agit d’une voie sur dalles en béton (appelée voie New Ballastless Track) qui a été mise en service en décembre 2013. Plusieurs sections de cette voie ont été instrumentées. Les données collectées quotidiennement sont traitées et comparées aux résultats de simulations numériques par éléments finis. L’analyse des résultats a ainsi permis de valider le modèle numérique qui a servi à la conception de la voie expérimentale. Une des particularités de ce modèle est de prendre en compte les effets de gradients thermiques de la dalle de voie sur le comportement mécanique de la structure NBT. Dans cet article, nous présentons l’instrumentation qui a été utilisée pour mettre en évidence ces gradients thermiques et suivre leurs effets sur le comportement mécanique de la structure NBT.

Résumé : Abstract : Resumen : Pour évaluer la méthode de localisation de dommages SDDLV, un benchmark à partir des données issues uniquement de capteurs a été proposé. Des essais ont été réalisés en laboratoire sur une maquette à l'échelle 1/200 de la travée centrale du pont de Saint-Nazaire équipée d'accéléromètres. Le dommage introduit simule la rupture d'une paire de câbles supportant le pont. La méthode SDDLV a permis d'identifier les modifications de la matrice de souplesses de la maquette en exploitant les données mesurées par des accéléromètres soumis à un bruit blanc. Dans un second temps, un modèle éléments finis de la structure est utilisé dans le cadre d'une analyse statique pour la cartographie des éléments endommagés sans qu'il soit nécessaire de le mettre à jour. Sur la maquette, un endommagement particulier a pu être correctement localisé dans un contexte où d'une part le décalage fréquentiel entre l'état sain et l'état endommagé n'est que de l'ordre de 1% pour les modes de vibrations utiles à l'analyse et que d'autre part la correspondance entre les modes calculés par éléments finis et les modes identifiés lors des essais n'est qu'approximative.

Résumé : Abstract : Resumen : Un suivi pendant six ans (et 800 000 chargements) de défauts d’interface de chaussées, des systèmes radar variés allant du système impulsionnel mono-antenne aux réseaux d’antennes...

Résumé : Abstract : Resumen : In the context of detecting changes in structural systems, several vibration-based damage detection methods have been proposed and successfully applied to both mechanical and civil structures over the past years. These methods involve computing data-based features, which are then evaluated in statistical tests to detect damages. While being sensitive to damages, the data-based features are affected by changes in the ambient excitation properties that potentially lead to false alarms in the statistical tests, a characteristic that renders their use impractical for structural monitoring. In this paper, a damage detection method is presented that is robust to changes in the covariance of the ambient excitation. The proposed approach is based on the Mahalanobis distance of output covariance Hankel matrices, which are normalized with respect to possibly changing excitation properties. The statistical properties of the developed damage feature are reported, and used for efficient hypothesis testing. Its robustness towards changes in the excitation covariance is illustrated on numerical simulations and successfully tested on a numerical offshore foundation model.

Résumé : Abstract : Resumen : Vibration measurements for structural health monitoring (SHM) by operational modal analysis (OMA) are classically obtained from sensors that are embedded in or physically attached to the monitored structure, like accelerometers or strain gauges. However, the setup time of these sensors and their restricted number and space coverage limit their monitoring capabilities. Video image-based sensing methods can overcome these shortcomings. With adequate image processing methods, motion signals are extracted from video image flows, which are then processed by system identification methods to estimate modal parameters. In this way, the pixels in selected regions of interest within the images act as a dense network of contactless sensors distributed over the whole structure. In this paper, the efficiency of this video-based approach is demonstrated with laboratory experiments on a cantilever beam, in particular, by evaluating its capability for detecting weak damages mimicked by slight mass modifications. To this end, the steerable filter-based method (ST), that recovers displacements from local phase, is first extended to overcome its motion limitation of one pixel size. Then, the performance of the improved motion extraction method is compared with two other well-established methods in the context of OMA, where natural frequencies, damping ratios and mode shapes with high spatial resolution are estimated together with their uncertainty bounds using covariance-driven subspace identification. The compared methods are evaluated with the help of reference laser displacement measurements as well as a finite element model of the beam, revealing differences in the accuracy of the estimated mode shapes depending on the chosen method for motion extraction. Finally, aiming to investigate early structural damage detection, experiments are carried out under small structural changes and the results are compared to a reference state with the help of estimated uncertainties. Small but statistically significant changes in the modal parameters are detected, showing the potential of the vision based framework for SHM.

Résumé : Abstract : Resumen : Typically, for linear parameter varying systems, which can potentially get influenced by spatio-temporal external parameters, possible changes in their eigenstructure are not easy to be attributed conclusively to system faults or spatio-temporal parametric variations. Such spatio-temporal variations can although be estimated alongside, yet at the cost of making the estimable system dimension disproportionately large. Such augmented system dimension can thereby jeopardize tracking of the system evolution, either due to computational constraints or due to insufficient measurement channels (ill-posedness). This paper proposes a localized estimation approach wherein only a subdomain of the entire system is considered which reduces the dimension of the estimated model within manageable limits. To focus on the subdomain properties without knowledge of the rest of the model parameterization, a robust algorithm is developed through output injection using a Kitanidis filtering approach to induce robustness in the system parameter estimation against the boundary measurements. Finally, the subdomain model is estimated employing a marginalized filtering approach wherein a particle filter is employed for estimating both the eigenstructure and the controlling parameter while an ensemble Kalman filter estimates the states. The approach is demonstrated with the help of a mechanical system under spatial variation in temperature for which subdomain isolation necessitates the interface to be measured. In the context of numerical application, the induced fault is due to damage and the mechanical model is controlled and parameterized by the internal temperature, whose variations can be significant due to substantial external thermal variations inducing significant variations in dynamic properties.

Résumé : Abstract : Resumen : The implementation of phase change thermal storage technology represents a high-potential strategy for mitigating energy consumption and reducing heating and cooling loads in buildings. However, the practical thermal storage effectiveness is affected significantly by the outdoor thermal conditions specific to each location. This work studied the thermal behaviors of a novel composite concrete containing phase change material (PCM concrete) when inserted into building envelopes. Numerical simulations have been conducted to assess the full-year impact of this PCM concrete on buildings with multi-layer walls, considering four cities with different climates. Results indicate that this novel PCM concrete demonstrates maximum effectiveness in Paris, effectively reducing indoor temperature fluctuations in summer. Conversely, in the other three cities with high solar-air temperatures in summer, the PCM concrete remains melting, reducing its thermal storage effectiveness. Instead, it performs better thermal behaviors during spring and autumn. In summary, the new PCM concrete demonstrates a good capacity to regulate indoor temperature, however, this effectiveness is primarily impacted by the outdoor solar-air temperature. Therefore, to maximize the latent heat storage potential of PCM, it is crucial to select an appropriate PCM with optimal phase change temperature zones, particularly when this technology is implemented in diverse climatic zones.

Résumé : Abstract : Resumen : Non-destructive evaluation (NDE) method has been popularly used for thermal diagnosis of building envelop in order to retrofit old buildings, detect civil engineering structures and accredit new buildings. The infrared thermography technique has been widely applied in the NDE method. In order to develop new solutions for diagnostic of local thermal performance, experiments were carried out on two cases of multi-layer walls. Experimental results of emissivity, temperature, and heat fluxes will be shown and analyzed in this article. The main originality of this work is to try to compute the front face temperature response to transient periodic heating by computing the front face pulse response. Such front face pulse response is obtained by a deconvolution method and a TSVD inverse method. The thermal properties of the wall will be characterized through the opotimization method based on the thermal quadrupoles model.

Résumé : Abstract : Resumen : The purpose of this study is to characterize the influence of environmental parameters for long-term in-situ structure monitoring as well as projections errors due to camera view and digitization. Measurements made on an instrumented test site have been made during the last 3 years, bringing an interesting dataset to exploit. The model used to convert the gathered data to temperature is firstly presented and discussed. Then, the effect of camera resectioning on infrared measurements is commented. Finally, the effect of the environmental parameters is studied and perspectives are proposed.

Résumé : Abstract : Resumen : Ballastless track structure are presently seen as an attractive alternative to conventional ballast. A new model was designed and a real-scale mockup was built and tested in fatigue test at IFSTTAR laboratory. To verify numerical simulations, the railway structure was monitored by conventional strain gages. A distributed fiber-optic strain sensing based on Rayleigh backscatter was also tested in this experiment. Fiber-optic cables were used as long-gage sensors and they were embedded in the concrete slabs of the structure. Firstly, we verified that the sensors were enough mechanical and chemical resistant for withstanding the stresses and the caustic environment experienced during concrete pouring process. Secondly, we validated the strain profiles measurements by comparison with the values obtained by strain gages. A good agreement was found throughout the duration of the fatigue test of 10 million cycles. Moreover, some cracks were observed early during the fatigue test. It is important to be able to monitor them during the service of ballastless track line. We showed that cracks can be detected and localized by fiber-optic distributed strain measurements. Finally, this experiment demonstrates that fiber-optic distributed strain sensing technique based on Rayleigh backscatter is a promising sensing technique to monitor ballastless track structures and more generally, civil engineering structures.

Résumé : Abstract : Resumen : In this numerical study, an optimal energetic control model applied to local heating sources to prevent black-ice occurrence at transport infrastructure surface is addressed. The heat transfer Finite Element Model developed and boundary conditions hypothesis considered are firstly presented. Several heat powering strategies, in time and space, are then introduced. Secondly, control laws are presented with the objective of preventing ice formation while avoiding excessive energy consumption by taking also into account weather forecast information. In particular, the adjoint state method is adapted for the case of an operation without some continuous properties (discontinuous time heat sources). In such case, a projection from the space of continuous time functions to a piecewise constant one is proposed. To perform optimal control, the adjoint state method is addressed and discussed for the different powering solutions. To preserve some specific technical components and maintain their lifetime, operational constraints are considered and different formulations for the control law are proposed. Time dependent convecto-radiative boundary conditions are introduced in the model by extracting information from existing weather databases. Extension to updated inline weather forecast services is also presented and discussed. The final minimization problem considered has to act on both energy consumption and non-freezing surface temperature by integrating these specific constraints. As a consequence, the final optimal solution is estimated by an algorithm relying on the combination of adjoint state method and gradient descent that fits mathematical constraints. Results obtained by numerical simulations for different operative conditions with various weather conditions are presented and discussed. Finally, conclusion and perspectives are proposed.

Résumé : Abstract : Resumen : Technological progress in uncooled infrared focal plane array sensors has contributed significantly to enlarge the scope of applications of such sensing technique in many domains: Leisure, Manufacturing, Process Survey, Building insulation diagnostic, Civil Engineering, Road works, etc.. . Different outdoor situations and objects of interest monitored by an in-house designed measurement architecture are presented. Designed instrumentation architectures and measurements correction from varying environmental conditions and geometrical considerations are discussed. A first step toward joint estimation of emissivity and temperature is introduced for outdoor applications. Then moving object detection by an AI approach applied on thermal image sequences is also presented and discussed. Finally conclusion and perspectives are proposed.

Résumé : Abstract : Resumen : This study addresses the development of a software for the simulation of radiative exchanges in in-situ 3D scenes. By using the progressive radiosity method, implemented on a graphic card to improve the computation speed, a direct solution to the radiative transfer equation is proposed. The software integrates the SMARTS2 atmospheric model to take into account the solar irradiance. Moreover, a camera model has been implemented to simulate the acquisition chain from the camera's irradiance to the digital signal. To validate the software, a comparison between simulated data and actual measurements is proposed. Finally, prospects for extending the software are presented.

Résumé : Abstract : Resumen : Bayesian filtering based structural health monitoring algorithms typically assume stationary white Gaussian noise models to represent an unknown input forcing. However, typical structural damages occur mostly under the action of extreme loading conditions, like earthquake or high wind/waves, which are characteristically non-stationary and non-Gaussian. Clearly, this invalidates this basic assumption, causing these algorithms to perform poorly under non-stationary noise conditions. This paper extends an existing interacting filtering algorithm to efficiently estimate structural damages while being robust to unknown non-stationary non-Gaussian input forcing. Furthermore, this approach is generalized beyond linear measurements to encompass the case of non-linear measurements such as strains. The joint estimation of state and parameters is performed by combining Ensemble Kalman filtering, for non-linear system state estimation, and Particle filtering to estimate changes in the structural parameters. The robustness against input forcing is achieved through an output injection approach embedded in the state filter equation. Numerical simulations for two kinds of response measurements (acceleration and strain) are performed on a 3D frame structure under different damage location and severity scenarios. The sensitivity with respect to noise and the impact of different sensor combinations have also been investigated.

Résumé : Abstract : Resumen : Le nombre d’unités flottantes de production, de stockage et de déchargement (FPSO) est en augmentation continue et la problématique de la corrosion est un élément important pour ces unités. Il est nécessaire de proposer des solutions de réparation ayant un faible impact sur leur exploitation, évitant notamment les travaux à chaud. Pour ces raisons, l'utilisation de patchs en PRF (Polymère Renforcé de Fibres) collés apparaît comme une solution particulièrement intéressante. Cependant, de fortes problématiques existent concernant la définition de méthodologies de conception, la robustesse et la prise en compte de la durabilité pour la conception de ces réparations. Afin de développer une telle méthodologie, Bureau Veritas pilote un projet industriel conjoint appelé SBO (JIP Strength Bond Offshore) visant à définir une telle stratégie de conception. Le travail présente une partie des résultats obtenus via une application des principes de la mécanique de la rupture pour la caractérisation de la résistance d’assemblages collés composite-acier. Premièrement, les conclusions du dimensionnement sont présentées. La réalisation de la campagne d’essai expérimentale est ensuite détaillée (fabrication des éprouvettes, et réalisation des essais monotones en traction et flexion). Enfin, les résultats de la campagne d’essais de fatigue sont développés et comparés aux références normatives.

Résumé : Abstract : Resumen : To avert catastrophic failure in the structures, joints are typically designed to yield, but not fail, so that energy accumulated under cyclic loading is dissipated. Eventually, this renders the structural joints to be characteristically weaker and more vulnerable than the members. Yet, damage detection research mostly assumes damage in the members only. This article proposes a model-based predictor-corrector algorithm that uses an interacting filtering approach to efficiently estimate joint damage in the presence of input and measurement uncertainties. For the predictor model, a novel strain-displacement relationship specific to semi-rigid frames is developed to map nodal displacements to corresponding strain measurements. The proposed estimation method embeds robustness against non-stationary input (e.g. seismic excitation) in the state filter, itself. For this, an output injection technique is integrated within the state filter. The modified state filter (robust Kalman filter) runs within an enveloping parameter filter (Particle filter) to simultaneously estimate the system states and joint damage parameters, respectively, using the response signal. Strain has been adopted as measurement since it is frame independent (beneficial for seismic activity) and also comparatively cheaper to use. Numerical studies are performed on a two-dimensional three storythree bay shear frame for different joint damage locations and severities. The sensitivity and the stability of the proposed approach are further investigated. Experimental validation of the proposed algorithm is carried out on a 2-D steel frame.

Résumé : Abstract : Resumen : This paper is concerned with the strain transfer modeling of distributed optical fiber sensors. A general solution describing the strain transfer for any arbitrary strain distribution is introduced. Then, experimental results of validation are presented.

Résumé : Abstract : Resumen : Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presented and applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably.

Résumé : Abstract : Resumen : This paper deals with uncertainty considerations in damage diagnosis using the stochas-tic subspace-based damage detection technique. With this method, a model is estimated from data in a (healthy) reference state and confronted to measurement data from the possibly damaged state in a hypothesis test. Previously, only the uncertainty related to the measurement data was considered in this test, whereas the uncertainty in the estimation of the reference model has not been considered. We derive a new test framework, which takes into account both the uncertainties in the estimation of the reference model as well as the uncertainties related to the measurement data. Perturbation theory is applied to obtain the relevant covariances. In a numerical study the effect of the new computation is shown, when the reference model is estimated with different accuracies, and the performance of the hypothesis tests is evaluated for small damages. Using the derived covariance scheme increases the probability of detection when the reference model estimate is subject to high uncertainty, leading to a more reliable test.

Résumé : Abstract : Resumen : The statistical subspace-based damage detection technique has shown promising theoretical and practical results for vibration-based structural health monitoring. It evaluates a subspace-based residual function with efficient hypothesis testing tools, and has the ability of detecting small changes in chosen system parameters. In the residual function, a Hankel matrix of output covariances estimated from test data is confronted to its left null space associated to a reference model. The hypothesis test takes into account the covariance of the residual for decision making. Ideally, the reference model is assumed to be perfectly known without any uncertainty, which is not a realistic assumption. In practice, the left null space is usually estimated from a reference data set to avoid model errors in the residual computation. Then, the associated uncertainties may be non-negligible, in particular when the available reference data is of limited length. In this paper, it is investigated how the statistical distribution of the residual is affected when the reference null space is estimated. The asymptotic residual distribution is derived, where its refined covariance term considers also the uncertainty related to the reference null space estimate. The associated damage detection test closes a theoretical gap for real-world applications and leads to increased robustness of the method in practice. The importance of including the estimation uncertainty of the reference null space is shown in a numerical study and on experimental data of a progressively damaged steel frame.

Résumé : Abstract : Resumen : The purpose of model updating is to minimize the misfit between the structural response measurements and an assumed numerical model. In the context of damage quantification, this misfit is characterized by some features computed from the response data measured on the faulty structure, and its Finite Element (FE) model in the healthy condition. The FE model is parameterized so that the estimated features are related to the physical parameters of the model. Therein, the parameterization size may be large. As a consequence of low instrumentation, different parameters can have a similar effect on the estimated features, resulting in non uniqueness of the updating problem solutions, even taking into account the inherent uncertainty errors, originating both from the model and the measurements. In this paper a model updating-based damage quantification strategy is proposed. It involves the minimization of two Hankel matrices, one computed from the data and another from the optimized model. The difference between those two matrices is studied, in particular in the practical case where the ambient excitation is unknown. It yields a statistical residual, whose deviations from zero can be evaluated through a statistical test. The resulting optimization is based on the Generalized Likelihood Ratio test as an objective function and uses its 95 per cent quantile as a measure of closeness for a stopping criterion for the optimization. Moreover, the large size of the finite element model to optimize compared to the low instrumentation has to be taken into account by clustering the parameter space. This clustering is proceeded using the well known stochastic subspace-based damage localisation method. The proposed framework is validated on simulations of a simple mechanical system.

Résumé : Abstract : Resumen : Damage localization and quantification constitute different aspects of structural damage diagnosis, which are of particular interest in the Structural Health Monitoring field. Therein, a classical solution is model updating, where the parameters of a finite element model of the possibly damaged structure are optimized to match with the corresponding parameters estimated from its vibration responses. To avoid ill-posedness of the classical finite element updating problem, damage localization and quantification can be treated separately. First, the information about regions or clusters of possibly damaged elements in the structure is obtained by a damage localization method. Then, this information is used to reduce the number of parameters for damage quantification. A framework combining the advantages of methods for damage localization with model optimization is proposed in this paper. For the exploration of the clustered physical model space, a stochastic optimization algorithm is coupled with the evaluation of the statistical properties of the MAC and frequency differences between the numerical model and the estimated modes for an adequate treatment of the data-based uncertainties. Herein, the development of the statistical properties of the MAC estimate is an important step, which is based on a recent quadratic framework that is adapted to the context of the inner product between an estimated mode shape and a numerical mode shape. This statistical information is used in the formulation of the objective function as well as in a data-driven stopping criterion for the optimization search. The proposed framework is validated on numerical simulations of a beam model, where damage at multiple locations is quantified up to the clustering precision.

Résumé : Abstract : Resumen : The Stochastic Dynamic Damage Locating Vector (SDDLV) method is an output-only damage localization method based on both a Finite Element (FE) model of the structure and modal parameters estimated from output-only measurements in the damage and reference states of the system. A vector is obtained in the null space of the changes in the transfer matrix from both states and then applied as a load vector to the model. The damage location is related to this stress where it is close to zero. In previous works, an important theoretical limitation was that the number of modes used in the computation related to the transfer function could not be higher than the number of sensors located on the structure. It would be nonetheless desirable not to discard information from the identification procedure. In this paper, the SDDLV method has been extended with a joint statistical approach for multiple mode sets, overcoming this restriction on the number of modes. Another problem is that the performance of the method can change considerably depending of the Laplace variable where the transfer function is evaluated. Particular attention is given to this choice and how to optimize it. The new approach is validated in numerical simulations and on experimental data, where the outcomes for multiple mode sets are compared with only using a single mode set. From these results, it can be seen that the success rate of finding the correct damage localization is increased when using multiple mode sets instead of a single mode set.

Résumé : Abstract : Resumen : The monitoring of mechanical systems aims at detecting and diagnosing damages, in general by using output-only vibration measurements under ambient excitation. In this paper, a method is proposed for the localization of stiffness changes in a structure. Based on mechanical grounds, damage is located in elements of a structure with zero stress when a load is applied that is in the null space of the transfer matrix difference between the nominal reference and the damaged state. This load vector is estimated from system identification in both reference and damaged states, and the stress is computed based on a finite element (FE) model of the structure in the reference state. In this work, we address two sources of errors in this computation that lead to stress that is only approximately zero in the damaged elements, which are (1) estimation errors due to noise and finite data, and (2) modal truncation errors due to a limited number of identified modes in comparison to the number of modes present in the FE model that characterizes the structural behavior. To address (1), we propose a statistical evaluation of the stress estimates for a decision on the damaged elements, by propagating the covariance from system identification results to the covariance of the stress. To address (2), several stress estimates are obtained for different mode sets and Laplace variables in the evaluation of the transfer matrices, and jointly evaluated in a hypothesis test. Damage localization results are presented in a simulation study and on experimental data from a damaged beam in the lab.

Résumé : Abstract : Resumen : Damage detection and damage localization constitute two pillars of Structural Health Monitoring that are highly relevant for applications to large-scale structures. Damage detection is usually achieved through statistical tests of data-driven residuals that monitor changes of a structure from its baseline behaviour. Damage localization investigates changes in damage residuals with respect to parameterized structural models through sensitivity vectors. Among the classic damage-sensitive features used for residual generation are subspace angles and principal components obtained from data spaces, whose evaluation for a decision about damage often boils down to novelty analysis, or statistical likelihood ratio tests. Modal parameter estimates are also employed for this purpose; however, most of the existing approaches appear to neglect the uncertainties related to their estimation. This paper fills this gap and presents a residual for damage detection and damage localization that is based on the difference of modal parameters obtained from data collected in some baseline and some test state of the structural system. The proposed scheme is evaluated in numerical simulations validating its robustness for damage detection and damage localization.

Résumé : Abstract : Resumen : The French metropolis, Rouen Normandie, has a project of a new bridge requiring temporary pier in the river Seine during the building phase. The location of this pier in the river is constrained by mechanical reasons related to the construction of the bridge. The purpose of this study is to find a position of this pier in the mechanically constrained area which minimizes vessel traffic obstruction and therefore collision risk. This type of study is classically carried out by using complex and multiple vessel dynamics simulation software in order to assess the risk for a given vessel to crash into the pier. The novelty of this study is to propose a statistical study based on the database of Automatic Identification System (AIS) of the Vessel Traffic Service (VTS) that is an automatic tracking system relying on ships transceivers. The technical objective is to identify low risk areas according to vessel speeds and sizes. Both factors should have an impact on the maneuverability of ships to avoid pier collision risk. Among all trajectories, straight line trajectories are selected based on statistical methods. The computation of prediction intervals of these trajectories delimits navigation zone. If all the straight trajectories are taken into account, the navigation zone extends to the whole river surface, which is not an helping result. However, by focusing on large and high speed vessels trajectories the navigation zone of these weak maneuverable ships is more centered in the middle of the river and represents only 25% of the river area. The complement of this area delineates possible locations of the temporary pier of the bridge in the river that do not disrupt vessel traffic.

Résumé : Abstract : Resumen : The paper presents both the modeling and the experiment to measure the longitudinal static strain over the inner perimeter of a tire. These measurements are expected to help at updating some unknown geometrical and mechanical parameters of tires for achieving more accurate simulations under conventional CAO software (namely, Solidworks). Compared to the literature, a distributed fiber optic sensing is used to measure the inner liner tire strain profile along the perimeter. Based on the Rayleigh scattering, this technology provides a fine spatial resolution, namely, less than 1 cm. The preliminary results show the typical Mexican-hat-like circumferential strain distribution and the contact patch length. Both quantities are shown to be related to the static load.

Résumé : Abstract : Resumen : In this paper are reported the results of an experimental campaign carried out on a post tensioned concrete beam with the aim of investigating the possibility to detect early warning signs of deterioration basing on static and/or dynamic tests. The beam was tested in several configurations aimed to reproduce several different phases of the 'life' of the beam: the original undamaged state, increasing loss of tension in the post tensioning cables, a strengthening intervention carried out by means of a second tension cable, formation of further cracks on the strengthened beam. Responses of the beam were measured by an extensive set of instruments consisting of accelerometers, inclinometers, displacement transducers, strain gauges and optical fibres. The paper discusses the tests program and the dynamic characterization of the beam in the different damage scenarios. The modal properties of the beam in the different phases were recovered basing on the responses recorded on the beam during sine-sweep and impact hammer tests. The variation of the first modal frequency was studied to investigate the sensitivity of this parameter to both the cracking of the concrete section and the tension in the cables and also to compare results given by different types of experimental tests.

Résumé : Abstract : Resumen : Building performance simulation often fails to predict accurately the real energy performance, mostly due to great uncertainties in the input data. Errors in computed performance are particularly significant in the case of existing buildings, for which the amount of information about intrinsic characteristics is low. However, efficient energy retrofit operations make necessary an accurate understanding of the initial state of a building using a calibrated prediction model. Several works have investigated the use of identification techniques for model calibration. The present paper investigates the use of such techniques to derive an energy audit procedure suitable to be an efficient aid for retrofit. In particular, we study here the possibility to determine the unknown thermal conductivity of the envelope and the internal gains based on temperature measurements only. We show how the adjoint method can be used to solve efficiently the inverse problem, while providing a fast method for computing model's sensitivities.

Résumé : Abstract : Resumen : This paper investigates thermography and shearography couplings, using feasibility trials and numerical simulations, for non-destructive control evaluations of bonding of carbon fiber-reinforced polymer plates glued over concrete structures. Those are well-known methods in non-destructive testing (NDT) applied to civil engineering, but in this context, they are seen as paired because they use the same excitation source: square-pulsed optical heating. Furthermore, because both methods are based on different properties, the detection of defects is optimised regardless of its nature or type. The combination of the methods allows the measurement of a thermal as well as a thermomechanical response from the structure at the same time. A quick review of those methods and their respective advantage and inconvenient is mentioned. An in-depth study of the interpretation of the thermal and mechanical responses is carried out in relation to the thermal excitation. Then, the thought process behind the conception of the finite element model and its limitation is discussed. The experimental setup, used for feasibility testing, is described as well as a thorough analysis of the experimental and simulated results. Finally, the pairing of both methods is discussed regarding the evaluation of the bond quality, as well as the similitude of the sample and its numerical model.

Résumé : Abstract : Resumen : We present in this paper the concept of solar hybrid road and the numerical model studied and develop to compute its thermal state at any time step. The aim of these new structures is to collect part of the solar radiation during the summer period, to prevent from icing at the surface during the winter period. As it is reversible, it will help also to prevent from a too high structure temperature (in particular closed to the surface) in summer season. Two types of modifications, compared to traditional structures are presented. The first one concerns the insertion of a porous layer allowing a heat fluid to exchange thermal energy. The second one concerns the use of a semi-transparent material at pavement surface allowing the solar radiation to penetrate deeper in the structure. The numerical model of this multi-physics problem develop with the finite element method is presented and discussed. A validation on two test cases is proposed. First results on energy harvesting evaluation for few locations (i.e. climatic conditions) in France are presented and discussed. Finally, conclusion and perspectives are proposed.

Résumé : Abstract : Resumen : Background and objective: Contrary to flows in small intracranial vessels, many blood flow configurations such as thosefound in aortic vessels and aneurysms involve larger Reynolds numbers and, therefore, transitional or turbulent conditions. Dealing with such systems require both robust and efficient numerical methods.Methods: We assess here the performance of a lattice Boltzmann solver with full Hermite expansion of the equilibriumand central Hermite moments collision operator at higher Reynolds numbers, especially for under-resolved simulations.To that end the food and drug administration’s benchmark nozzle is considered at three different Reynolds numberscovering all regimes: 1) laminar at a Reynolds number of 500, 2) transitional at a Reynolds number of 3500, and 3)low-level turbulence at a Reynolds number of 6500.Results: The lattice Boltzmann results are compared with previously published inter-laboratory experimental data obtained by particle image velocimetry. Our results show good agreement with the experimental measurements throughout the nozzle, demonstrating the good performance of the solver even in under-resolved simulations.Conclusion: In this manner, fast but sufficiently accurate numerical predictions can be achieved for flow configurationsof practical interest regarding medical applications.

Résumé : Abstract : Resumen : In a context of climate change, lowering road vehicles consumption is a key point to meet CO2 reduction requirements. In addition to car technological advances, eco-driving is part of the solution but the road infrastructure should ensure its development. In a previous study, a gain of 5% in the spent energy was estimated on specific route by slightly moving some speed signs, but under the assumptions that drivers practice eco-driving and the traffic is free-flow. This paper deepens and widens these first results. The base of this research is to provide a simulation model to study the impact of traffic and speed-sectioning on the environment. Inside this model, the impact of different approach speeds to a speed-sectioning is assessed. The simulation is conducted within the Trafficware Synchro environment where parameters according to road infrastructure, vehicle and driver are based on real traffic data. Moving a speed limitation sign can contribute to a reduction of fuel consumption up to 8% depending on driver structure. This new methodology improves the accuracy of our first results and detects adverse effects as the possible emergence of congestion due to the modification of speed sectioning. In perspective this methodology represents a significant argument in road managers strategy. In addition it also represents an orienting point to investigate different action scenarios and a first step to a global optimization policy in managing road infrastructure.

Résumé : Abstract : Resumen : Thermal performances of building walls are significant for energy conservation. However, very few non-destructive evaluation methods exist to quantitatively diagnose the building walls in situ due to the walls’ large thickness. Moreover, most of the existing methods are inconvenient to implement in situ and take a long characterization time. This paper studies transient heat transfer to estimate the wall's thermal properties based on the thermal quadrupoles modelling. Semi-infinite boundary condition is assumed at the rear face of the wall. With this assumption, only the front face response of the wall is considered. The evaluation time is then effectively reduced within a few hours, and the diagnosis in situ is simplified without the measurement on the rear face of the wall. Experiments are carried out on two traditional multi-layered building wall cases using heating lamps. With the measured surface temperatures and heat fluxes, the unit-pulse response and unit-step response at the front surface of the investigated wall are reconstructed through a deconvolution approach and a TSVD (Truncated Singular Value Decomposition) inversion. The unit-step response curve is directly characterized by the thermal resistance, thermal effusivity and heat capacity of the wall, thus allowing us to estimate the wall properties. The characterization time for the two cases is less than 10 hours.

Résumé : Abstract : Resumen : This paper deals with the parametric shape optimization of a simplified model of brake system under squeal noise criteria. As brake squeal phenomenon induces under-quality perception for industrial structures such as cars and trains, its understanding and management are important challenges for future systems design. Hence, we expose an optimization methodology based on meta-model for a proposed computationally expensive stability criteria representing the squeal noise. Sensitivity analysis is first conducted to assess and validate the chosen geometrical parameters. Then, a Pareto front is obtained through optimization of the system, leading to a set of optimal solutions for theconsidered multi-objective case.

Résumé : Abstract : Resumen : Friction dampers are classically used in turbomachinery for bladed disks to control the levels of vibrations at resonance and limit the risk of fatigue failure. It consists of small metal components located under the platforms of the blades, which dissipates the vibratory energy through friction when a relative displacement between the blades and the damper appears. It is well known that the shape of such component has a strong influence on the damping properties and should be designed with a particular attention. With the arrival of additive manufacturing, new dedicated shapes for these dampers can be considered, determined with specific numerical methods as topological optimisation (TO). However, the presence of the contact nonlinearity challenges the use of traditional TO methods to minimise the vibration levels at resonance. In this work, the topology of the damper is parametrized with the Moving Morphable Components (MMC) framework, and optimised based on meta-modelling techniques: here kriging coupled with the Efficient Global Optimisation (EGO) algorithm. The level of vibration at resonance are computed based on the harmonic balanced method augmented with a constraint to aim directly for the resonant solution. It corresponds to the objective function to be minimised. Additionally, a mechanical constraint based on static stress analysis is also considered to propose reliable damper designs. Results demonstrate the efficiency of the method and show that dampers geometries that meet the engineers' requirements can be identified.

Résumé : Abstract : Resumen : This paper considers the problem of set-membership estimation for discrete-time linear time-varying descriptor systems subject to unknown but bounded disturbance and noise. We propose a set-membership estimation method based on a descriptor system observer and a zonotopic estimator of the observer error bounds. The observer parameters are optimized in order to minimize the sizes of the zonotopes enclosing all admissible state trajectories. Finally, two simulation results are provided to demonstrate the effectiveness of the proposed method.

Résumé : Abstract : Resumen : This paper considers set-membership estimation for discrete-time linear parameter-varying descriptor systems. Ellipsoid bundle, a new set representation tool combining certain characteristics of ellipsoids and zonotopes, is used to design a setmembership estimation method for the considered systems. We use the L∞ technique to design the estimator parameters in order to optimize estimation accuracy. This paper also studies the stability problem of the proposed method and establishes an offline sufficient stability condition. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.

Résumé : Abstract : Resumen : Damage diagnosis based on global structural vibrations critically depends on the sensor layout, in particular when a small number of sensors is used for large structures under unknown excitation. This paper proposes a sensor placement strategy that yields an optimized sensor layout with maximum damage detectability in selected structural components. The optimization criterion is based on the Fisher information, which quantifies the information that the damage-sensitive feature carries on the design parameters of structural components, such as material constants or cross-sectional values. It is evaluated using a finite element model, and considers the statistical uncertainties of the damage-sensitive feature. The methodology is shown for the stochastic subspace-based damage detection method, but can be applied to any damage-sensitive feature whose distribution can be approximated as Gaussian. It is suitable to find the optimal layout for a fixed number of sensors and to choose an appropriate number of sensors. Since the Fisher information is defined component-wise, the sensor layout can be tuned to become more sensitive to damage in local structural components, such as damage hotspots, non-inspectable components, or components that are critical for the safety and serviceability of the structure. For proof of concept, the sensor layout on a laboratory beam is optimized based on numerical simulations, and it is showcased that the optimal sensor layout leads to the highest damage detectability for experimental data.

Résumé : Abstract : Resumen : In this paper we focus on sensor placement for output-only modal analysis, where the objective is to choose those sensor locations yielding a minimal variance in the identification of modal parameters from measurement data. It is heuristically shown that the variance of modal parameters estimated with data-driven subspace identification can be approximated solely based on the process and the measurement noise properties with the Kalman filter and the underlying system model, and is independent of data which are not available at the experimental design stage. The performance of the proposed approach is illustrated on an extensive Monte Carlo simulation for an illustrative example of a mechanical chain system

Résumé : Abstract : Resumen : This paper presents an ultra-flexible piezoelectric air flow energy harvester capable of powering a wireless sensor. The method to easily adapt the aero-electric generator to the wind is presented. In the wind tunnel, different configurations have been tested to determine the best one for energy harvesting at low wind speed. In particular, the galloping configuration, with the addition of a bluff body at the free end of the cantilever which allows to improve the performance of the micro-generator by coupling the vibrations induced by the vortices and the galloping phenomena. In this study, we also present a method to optimize the energy harvesting without increasing the volume of the device. The effects of mechanical and electrical coupling of several generators on the performance of energy harvesting are presented. Thus, with the electrical parallel coupling of four generators, we obtained a maximum power of 60 mW instead of 30 mW with two generators for a wind speed of about 6 m/s. The mechanical coupling of the micro-generators allowed the device to keep the same volume (z540 cm3), however the threshold wind speed to increase (>6 m/s). The harvested energy was then used to operate a wireless sensor.

Résumé : Abstract : Resumen : The first phase of each structural monitoring project is the operational evaluation. Its purpose is to define relevant damage mechanisms and environmental conditions, to consider the data acquisition limitations on site, and to justify the investment. Subsequently, relevant measurement quantities and damagesensitive features are selected, but very few systematic approaches exist in the literature on how to select the most appropriate features. The presented paper fills this gap and develops an approach to select damage-sensitive features based on probability of detection (POD) curves. The POD curves are generated based on a novel method for statistical damage detection tests that requires a finite element model and vibration data from the undamaged structure. However, no data is required from the damaged state, making it particularly suited for unique or large and complex engineering structures. The approach explicitly considers the uncertainties in the features due to unknown loads, measurement noise, and short measurement durations. Although global damage-sensitive features are considered, such as modal parameters and subspace-based residuals, the detectability is evaluated for local structural components. The paper includes a proof of concept study on a laboratory structure. The results demonstrate that the developed method successfully finds the feature with the highest damage detectability for a chosen damage scenario, and that the detectability varies depending on the monitored local component.

Résumé : Abstract : Resumen : Standard filtering techniques for structural parameter estimation assume that the input force either is known exactly or can be replicated using a known white Gaussian model. Unfortunately for structures subjected to seismic excitation, the input time history is unknown and also no previously known representative model is available. This invalidates the aforementioned idealization. To identify seismic induced damage in such structures using filtering techniques, a novel algorithm is proposed to estimate the force as additional state in parallel to the system parameters. Two concurrent filters are employed for parameters and force respectively. For the parameters, interacting Particle-Kalman filter [1] is employed targeting systems with correlated noise. Alongside a second filter is employed to estimate the seismic force acting on the structure. The proposal is numerically validated on a sixteen degrees-of-freedom mass-spring-damper system. The estimation results confirm the applicability of the proposed algorithm.

Résumé : Abstract : Resumen : The present work offers a comprehensive overview of methods related to condition assessment of bridges through Structural Health Monitoring (SHM) procedures, with a particular interest on aspects of seismic assessment. Established techniques pertaining to different levels of the SHM hierarchy, reflecting increasing detail and complexity, are first outlined. A significant portion of this review work is then devoted to the overview of computational intelligence schemes across various aspects of bridge condition assessment, including sensor placement and health tracking. The paper concludes with illustrative examples of two long-span suspension bridges, in which several instrumentation aspects and assessments of seismic response issues are discussed.

Résumé : Abstract : Resumen : New technologies such as GNSS-based positioning solutions will contribute to the modernization and efficiency enhancement of the railway system. Its capacity to provide a global absolute position without any infrastructure to be supported by the user at reasonable cost makes GNSS a game changer for rail. However, in order to reach the high-level performance requirements needed to apply these technologies to safety-critical applications, and in particular, for the use of virtual balises, some solutions need to ensure their accuracy, robustness and safety. Coming from aeronautics experience, the RAIM (Receiver Autonomous Integrity Monitoring) can help reducing inaccuracy by detecting and excluding faulty measurements and bounding residual errors. In this paper, we intend to demonstrate how the combination of weighting schemes and FDE (Fault Detection and Exclusion) can help the system to enhance GNSS performance in a railway environment where multipath, non-line of sight signals and interferences can occur. Some results based on real data are presented in order to quantify the benefit. Application of such techniques will help designing future on-board location units by evaluating their potential performance before deciding the level of hybridization that will be mandatory to ensure continuity of service and compensate the drawbacks of GNSS in harsh environments.

Résumé : Abstract : Resumen : Within the scope of pavement monitoring, the use of Ground Penetrating Radar (GPR) methods, especially in the detection of emerging cracks is of greater importance in order to predict the sustaining life period of a pavement structure. However, suitable processing techniques can be used to improve the operator’s interpretation of the pavement conditions in a more efficient way. This matter has motivated the development of specific signal processing methods to conduct early detection of defects such as thin interlayer debondings. The robustness of such signal processing methods depends on their ability to adapt to variations in the GPR data sizes and configurations (e.g., pavement layer geometry and permittivity). The lack of labeled and controlled field data however, demands the need for numerically modeled GPR data to assess the robustness of these methods. Therefore, the numerical analysis is carried out on the EM wave propagation in the pavement data created using the FDTD-based 2D GprMax software. This data can be used to evaluate the influence of pavement characteristics on SVM’s performance. The debonding detection efficiency is susceptible to the pavement layer characteristics, especially the top layer and the debonding layer. Thus, the objective of this paper is to study the influence of top pavement layer characteristics on the debonding detection rate by implementing on independent 1D GPR data (namely, A-scans) using time domain signal features. The use of local features provides the required refined signal analysis and reduces the computational burden. The detection efficiency over larger data sets indicated SVM’s adaptability. On the other hand, the performance over various top pavement layer configurations demonstrated its robustness.

Résumé : Abstract : Resumen : In the robust shape optimization context, the evaluation cost of numerical models is reduced by the use of a response surface. Multi-objective methodologies for robust optimization that consist in simultaneously minimizing the function and a robustness criterion (the second moment) have already been developed. However, efficient estimation of the robustness criterion in the framework of time-consuming simulation has not been greatly explored. A robust optimization procedure based 15 on the prediction of the function and its derivatives by kriging is proposed. The second moment is replaced by an approximated version using Taylor expansion. A Pareto front is generated by a genetic algorithm named NSGA-II with a reasonable time of calculation. Seven relevant strategies are detailed and compared with the same calculation time in two test functions (2D and 6D). In each case, we compare the results when the derivatives are observed and 20 when they are not. The procedure is also applied to an industrial case study where the objective is to optimize the shape of a motor fan.

Résumé : Abstract : Resumen : Sensor types and their positioning is a major factor in structural health monitoring (SHM) to ensure certainty in estimation. While acceleration has predominantly been employed for damage detection, they are known to be costly and not frame invariant (except for moderately accurate GPS based accelerometers). A thorough monitoring of a real life structure requires dense instrumentation which might become expensive with costly sensor types. Further, damages mostly occur at rare events, like seismic base excitation, for which typical accelerometers are not proper. This study employs strain as a cheaper alternative for damage sensitive measurement that is also frame invariant. An interacting filtering approach with particle and Kalman filters is employed that estimates structural health from measured dynamic strains. Further to account for extreme non-stationary events like seismic excitation, robustness against uncertain inputs is induced in the filtering environment following an output injection approach. The proposed algorithm is tested on a seven story-one bay frame model and a real experimental beam structure.

Résumé : Abstract : Resumen : Road safety relies mostly on available tire to road grip regarding to the forces required by a vehicle in a given dynamic situation. For example safety issues can occur when deceleration required forces exceeding the tire/road grip potential. Issues are much critical while traveling in a curve with a coupled longitudinal/transverse grip demand. Instrumented vehicles can be used in order to evaluate the available tire to road grip in rolling situations, but it remains linked to a dedicated vehicle and models have to be use to extrapolate these evaluations to various vehicles. The aim of this work is to propose a sensor embedded in the road infrastructure to evaluate the longitudinal and transverse grip demand of any traveling vehicle. A 6 axis sensor is embedded in a road test track, under a piece of the real road upper layer. Measurement are made at a acquisition rate of 2500 Hz and forces measuring ranges are of 2500 daN (vertical axis) and 750 daN (tangential). Measurements are compared to on-board measurement with a vehicle instrumented with dynamometric wheels. Three situations are experienced in a 100 meters curve: traveling at a given speed and traveling while accelerating or braking moderately, and for three vehicle speeds of 40, 60 and 80 km/h. Force evaluation from the two systems are differing of only 5% for the vertical force and 10% for the tangential forces. The differences are lower for the higher grip demands. For example moderate braking from 70 km/h in curve lead to 0.23 and 0.25 longitudinal friction coefficients (LFC) for road sensor and dynamometric wheel, and to 0.17 and 0.19 transversal friction coefficients (TFC). In perspectives, evaluations of an excessive grip demand could result in solutions as lowering the designed speed or improving the road surface layer.

Résumé : Abstract : Resumen : In this study the authors propose to take into account the nonlinear effects induced by the presence of a transverse crack to carry out vibratory monitoring and detect transverse cracks in rotating systems subject to model uncertainties. More precisely, we focus more particularly on the global complexity of the nonlinear dynamic behaviour of cracked rotors and the evolution of their harmonic components as a function of the parameters of a transverse breathing crack (its position and depth) when numerous uncertainties are considered. These random uncertainties correspond to random geometric imperfections (two disc thicknesses), random material properties (Young modulus and material density) and boundary conditions uncertainty (two bearing stiffnesses). The objective of the present work is to identify robust indicators capable of determining the presence of a crack and its status even though numerous uncertainties are present. To conduct such a study, an advanced surrogate modelling technique based on kriging and Polynomial Chaos Expansion (PCE) is proposed for the prediction of both the critical speeds and the harmonic components × during passage through sub-critical resonances. An extensive study to ensure the validation of the surrogate models and a relevant choice of both the parametric and random Design of Experiments (i.e. kriging DoE and PCE DoE) is proposed. The proposed methodology is applied on a flexible rotor with a transverse breathing crack and subjected to random geometric imperfections and fluctuations in material properties of the rotor system.

Résumé : Abstract : Resumen : Face à un faible flux de construction neuve en France, d'importantes économies d'énergie peuvent être réalisées par la rénovation des bâtiments existants. Une stratégie numérique fondée sur la modélisation inverse, i.e. interaction entre modèle thermique de bâtiment et mesures, est développée afin de réaliser un bilan énergétique détaillé d'un bâtiment existant avant et après rénovation. La première étape consiste à recaler les paramètres du modèle thermique à partir de mesures in-situ par un algorithme itératif. Ensuite, ce modèle recalé est exploité pour estimer l'ensemble des flux énergétiques. Cette stratégie est appliquée aux chalets de l'Equip Ex Sense-City. Les échanges convectifs entre la paroi et l'extérieur ont été réduits de 75% suite à l'ajout d'un isolant.

Résumé : Abstract : Resumen : In the field of Geophysics and civil engineering applications, Ground Penetrating Radar (GPR) technology have become one of the emerging Non-Destructive Testing (NDT) methods for its ability to perform tests without damaging structures. In this context, applications like concrete rebars assessments, utility networks surveys or precise localisation of embedded cylindrical pipes still remain challenging. Inversion of geometrical parameters such as depth and radius of embedded cylindrical pipes and dielectric parameters of its surrounding material are of great importance for preventive measurements or quality control. Innovative signal processing techniques associated with GPR could perform physical and geometrical characterisation. In this paper, Performances of supervised machine learning method on GPR data are evaluated. Support Vector Machines (SVM) classifications, Support Vector Machines regression (SVR) and Ray-based methods are used in order to correlate information about radius and depth of the embedded pipes with the velocity of stratified media, in various numerical configurations. The approach is based on the hyperbola trace emerging in a set of B-scans, whereas the shape of hyperbola highly varies with depth and radius of the pipe as well as the velocity of the medium. In the ray-based method, inversion of the wave velocity and the pipe’s radius was performed through an appropriate nonlinear least mean squares inversion technique. The features selection within machine learning models also performed on the information picked from observed hyperbola’s travel times. Simulated data are obtained by the Finite-Difference Time-Domain (FDTD) method with the numerical tool 2D GprMax. The study is carried out at mono-static, ground coupled configuration. A parametric comparison is also included in the analysis of performances of the mentioned techniques in terms of relative errors estimation against designed parameters.

Résumé : Abstract : Resumen : Accelerated pavement testing (APT) is well known as a very effective way to investigate the actual behaviour of pavement structures. Feedback from the test can be obtained in a couple of months through measurements and monitoring made during the experiment. Among them, pavement surface cracking is one of the most important parameters for the evaluation of experimental pavement performance. Generally, crack monitoring during APT tests is still carried out manually for every specific loading period. This classical approach is time-consuming and interesting information may be lost if a measurement is missed. For this reason, a Rapid and Continuous Imaging (RCI) technique has been developed and tested at IFSTTAR, for the monitoring of crack development on the pavement surface during APT experiments. The principle of this technique consists in taking images of the experimental pavement surface continuously along the test track, at intervals depending on the moving speed of the heavy traffic simulator, i.e. the road fatigue carrousel. A crack map, representing an overview of visible cracks on a pavement section can then be rapidly created using an ad hoc image processing tool. The application of this pavement crack mapping technique for crack monitoring on an asphalt pavement during a recent APT experiment showed interesting results.

Résumé : Abstract : Resumen : This database was collected over narrow artificial disbonded areas during an accelerated pavement testing at univ. Gustave Eiffel's carousel. GPR data have been collected over tenartificial defects (tack-free, geotextile and sand-based), which were embedded between the top and the base layers. The data collection was organized in a two-stage experiments and covers the full life-cycle of the pavement structure. During the first stage that took place in 2012-13, data were collected at different stages from 0k to 300k loading cycles. The second measurement campaign was performed in 2019-2020 and lasted up to 800k loading cycles. This database completes a first one dedicated to three largest defects, and presented in " Radar database over large debonded areas into pavement structures

Résumé : Abstract : Resumen : This database was collected over artificial disbonded areas during an accelerated pavement testing at IFSTTAR's carousel. GPR data have been collected over three artificial defects (tack-free, geotextile and sand-based), which were embedded between the top and the base layers. The data collection was organized in a two-stage experiments and covers the full life-cycle of the pavement structure. During the first stage that took place in 2012-13, data were collected at different stages from 0k to 300k loading cycles. The second measurement campaign was performed in 2019-2020 and lasted up to 800k loading cycles.

Résumé : Abstract : Resumen : Data interpretation over disbonded pavement structures still remains an open problem for the scientific community. In this paper, the details of a groundpenetrating radar (GPR) database, collected over artificial disbonded areas during an accelerated pavement testing at IFSTTAR's carrousel, are presented. The database will be made available to the scientific communities. It may serve as a reference benchmark for both developing and testing the performance of various processing techniques for either interface detection and characterization, or monitoring purposes. In practice, GPR data have been collected over three artificial defects (tack-free, geotextile and sand-based), which were embedded between the top and the base layers. The data collection was organized in a two-stage experiments and covers the full life-cycle of the pavement structure. During the first stage that took place in 2012-13, data were collected at each of 10k, 50k, 100k, 200k, 250k and 300k loading cycles. The second measurement campaign was performed in 2019 and lasted up to 720k loading cycles. The database merges two types of existing radar technologies and configurations. Two stepped-frequency radar with 1.5 and 4.5 GHz as center frequency and two impulse radar systems, working at 2.6 and 1.5 GHz, were tested during this experiment.

Résumé : Abstract : Resumen : Data interpretation over disbonded pavement structures still remains an open problem for the scientific community. In this paper, the details of a ground-penetrating radar (GPR) database, collected over artificial disbonded areas during an accelerated pavement testing at IFSTTAR’s carrousel, are presented. The database will be made available to the scientific communities. It may serve as a reference benchmark for both developing and testing the performance of various processing techniques for either interface detection and characterization, or monitoring purposes. In practice, GPR data have been collected over three artificial defects (tack-free, geotextile and sand-based), which were embedded between the top and the base layers. The data collection was organized in a two-stage experiments and covers the full life-cycle of the pavement structure. During the first stage that took place in 2012–13, data were collected at each of 10k, 50k, 100k, 200k, 250k and 300k loading cycles. The second measurement campaign was performed in 2019 and lasted up to 720k loading cycles. The database merges two types of existing radar technologies and configurations. Two stepped-frequency radar with 1.5 and 4.5 GHz as center frequency and two impulse radar systems, working at 2.6 and 1.5 GHz, were tested during this experiment.

Résumé : Abstract : Resumen : Modal parameters are estimated from vibration data, thus they are inherently afflicted with statistical uncertainties due to the unknown ambient excitation and measurement noise. While the point estimates of the modal parameters can be obtained with several system identification methods, only few of them also provide the associated uncertainties. The quantification of these uncertainties is important for many applications, since they are a means to assess the precision of the estimates, and to evaluate if changes between different datasets are statistically significant or not. As such, they are an added value in modern modal analysis practice and used in applications to e.g., damage detection and localization, reliability analysis, modal tracking and model calibration. For subspace-based system identification, efficient methods for uncertainty quantification have been developed for the last 15 years, yielding reliable estimates of the uncertainties at reasonable computational cost. They cover a wide range of subspace methods and their application areas. In this paper, an overview of the developments is given and the importance of the knowledge of the uncertainties is illustrated.

Résumé : Abstract : Resumen : Even under normal service loads, reinforced concrete structures in the field of civil engineering are full of micro cracks. More than twenty years of development of distributed fibre optic sensing techniques in terms of accuracy and spatial resolution made them capable of not only monitoring strain and temperature changes, but also detecting and localizing cracks. In order to detect safety-related issues and better maintenance and to offer better maintenance and management strategies, continuous monitoring of the crack width is also paramount. The paper focuses on the application of a theoretical mechanical strain transfer model in concrete substrate. The experimental setup involved employment of the Optical Frequency Domain Reflectometry (OFDR) technique with high spatial resolution. Three-point bending tests were performed on 1m length reinforced concrete beams instrumented with embedded and surface attached fibre optics cables. Results showed that the Crack Opening Displacement (COD) in single and multiple neighboring micro cracks cases can be well estimated.

Résumé : Abstract : Resumen : Pour une gestion durable et sûre des infrastructures de génie civil et pour en prolonger la durée d’exploitation, les gestionnaires d’ouvrages requièrent des informations qualifiées et quantitatives sur l’évolution continue des indicateurs de performance, en particulier, la résistance, le module, la porosité et la teneur en eau des bétons. Le projet ANR-SCaNING a pour objectif de développer une approche systémique du suivi de santé des structures neuves ou existantes en béton armé comprenant : la validation de capteurs noyés (électriques, électromagnétiques et ultrasonores), le traitement de la mesure et l’extraction d’observables qualifiées, découplées des principaux facteurs d’influence, la combinaison et la conversion des observables en indicateurs pour le diagnostic, ainsi que la plate-forme de supervision connectée.

Résumé : Abstract : Resumen : This paper summarizes the development of Value of Structural Health Monitoring (SHM) Information analyses and introduces the development, objectives and approaches of the COST Action TU1402 on this topic. SHM research and engineering has been focused on the extraction of loading, degradation and structural features for damage detection and condition assessment, system identification and model updating. However, there is an actual challenge to establish a better understanding of the value of SHM before its implementation in terms of its utility in conjunction with practically applicable methods for its quantification. This challenge can be met with Value of SHM Information analyses facilitating that the SHM contribution to substantial benefits for life safety, economy and beyond can be may be quantified, demonstrated and utilized. However, Value of SHM Information analyses involve complex models encompassing the infrastructure and the SHM systems, their functionality and thus require the interaction of several research disciplines. For progressing on these points, a scientific networking and dissemination project namely the COST Action TU1402 has been initiated.

Résumé : Abstract : Resumen : The paper gives an overview of the ongoing experiment to survey debonding areas within pavement structure during accelerated pavement testing on the Ifsttar's fatigue carrousel. Several defects have been embedded during the con- struction phase and have been probed by different NDT techniques. Among them, the paper focuses on radar NDT&E techniques which have been used to detect and locate the artificial defects at the early stage of the experiment and then to perform the survey at different loading cycles. Besides, the test-site has been used to test different GPR materials, including the 3D GPR technology. The experiment has also motivated some related studies in the field of GPR data modelling and data processing, which are summarized in the paper. The experiment is expected to be pursued beyond 300 loading kcycles to reach larger pavement degradations.

Résumé : Abstract : Resumen : The paper gives an overview of the ongoing experiment to survey debonding areas within pavement structure during accelerated pavement testing on the Ifsttar's fatigue carrousel. Several defects have been embedded during the construction phase and have been probed by different NDT techniques. Among them, the paper focuses on radar NDT&E techniques which have been used to detect and locate the artificial defects at the early stage of the experiment and then to perform the survey at different loading cycles. Besides, the test-site has been used to test different GPR materials, including the 3D GPR technology. The experiment has also motivated some related studies in the field of GPR data modelling and data processing, which are summarized in the paper. The experiment is expected to be pursued beyond 300 loading kcycles to reach larger pavement degradations.

Résumé : Abstract : Resumen : This paper develops a model-assisted approach for determining predictive probability of detection curves. The approach is “model-assisted,” as the damage-sensitive features are evaluated in combination with a numerical model of the examined structure. It is “predictive” in the sense that probability of detection (POD) curves can be constructed based on measurement records from the undamaged structure, avoiding any destructive tests. The approach can be applied to a wide range of damage-sensitive features in structural health monitoring and non-destructive testing, provided the statistical distribution of the features can be approximated by a normal distribution. In particular, it is suitable for global vibration-based features, such as modal parameters, and evaluates changes in local structural components, for example, changes in material properties, cross-sectional values, prestressing forces, and support conditions. The approach explicitly considers the statistical uncertainties of the features due to measurement noise, unknown excitation, or other noise sources. Moreover, through confidence intervals, it considers model-based uncertainties due to uncertain structural parameters and a possible mismatch between the modeled and the real structure. Experimental studies based on a laboratory beam structure demonstrate that the approach can predict the POD before damage occurs. Ultimately, several ways to utilize predictive POD curves are discussed, for example, for the evaluation of the most suitable measurement equipment, for quality control, for feature selection, or sensor placement optimization.

Résumé : Abstract : Resumen : l’instrumentation des chaussées sur site représente un moyen pour mieux suivre le comportement des structures de chaussées en temps réel, prévenir leurs dégradations et améliorer leur gestion. Cela nécessite de développer des méthodes d’instrumentation présentant des caractéristiques adaptées aux structures de chaussées. Les fibres optiques, caractérisées par leur faible dimension, leur insensibilité aux interférences électromagnétiques et à la corrosion et leur capacité à mesurer à la fois les déformations et les températures, représentent une solution prometteuse pour répondre à ces nouveaux besoins. Ce projet présente des premiers résultats de mesures réalisées au moyen de fibres optiques continues, dans des structures de chaussées bitumineuses, testées sur le manège de fatigue de l’Université Gustave Eiffel. La technologie utilisée (méthode Rayleigh) permet de mesurer les déformations de manière continue, sur une longueur de fibre de 10m, avec une résolution de l’ordre de 10-6 m/m, à plusieurs niveaux dans la chaussée. Cela permet de caractériser de façon beaucoup plus précise les champs de déformations longitudinales ou transversales sous passage des charges roulantes, que les capteurs traditionnels, tels que les jauges de déformation, qui ne permettent que des mesures ponctuelles.

Résumé : Abstract : Resumen : L’instrumentation des chaussées sur site représente un moyen pour mieux suivre le comportement des structures de chaussées en temps réel, prévenir leurs dégradations et améliorer leur gestion. Cela nécessite de développer des méthodes d’instrumentation présentant des caractéristiques adaptées aux structures de chaussées : bonne précision, compatibilité avec l’hétérogénéité et la rigidité des matériaux de chaussés, faible encombrement, résistance durant la construction et la phase de service. Les capteurs fibre optique, caractérisés par leurs faibles dimensions, leur insensibilité aux interférences électromagnétiques et à la corrosion et leur capacité à mesurer à la fois les déformations et les températures, constituent une solution prometteuse pour répondre à ces nouveaux besoins. Ce projet présente des premiers résultats de mesures réalisées au moyen de capteurs à fibre optique continus, dans des structures de chaussées bitumineuses, testées sur le manège de fatigue de l’Université Gustave Eiffel. La technologie utilisée (basée sur la retrodiffusion Rayleigh) permet de mesurer les déformations de manière continue, sur une longueur de fibre de 10 m, avec une résolution de l’ordre de 10-6 m/m, à plusieurs niveaux dans la chaussée. Cela permet de caractériser de façon beaucoup plus précise les champs de déformations longitudinales ou transversales sous passage des charges roulantes, que les capteurs traditionnels, tels que les jauges de déformation, qui ne permettent que des mesures ponctuelles.

Résumé : Abstract : Resumen : The inherent modelling of the operational wind turbines and rotating machines do not agree in general with the assumptions of the operational modal analysis (OMA) methods developed for civil engineering, where time invariant systems are considered. Current OMA methods for rotating machines introduce datapre-processing to adapt classical identification methods. However, they show strong limitations and rely on strong assumptions, such as the isotropy of the rotor, making them hardly applicable in practice. To overcome these limitations, this paper proposes to employ the Floquet theory of periodic system to approximate rotating systems as time invariant systems. Thus, classical identification methods can be used to retrieve the parametric signature of the periodic systems. This Floquet-based approximation gives a physical meaning to the identified eigenmodes. The proposed approach is validated on both a small numerical model and an aero-servo-elastic numerical model of a rotating 10MW wind turbine, with isotropic and anisotropic rotors, using the stochastic subspace identification to retrieve the modes and their uncertainty.

Résumé : Abstract : Resumen : In the field of pavement monitoring, Ground Penetrating Radar (GPR) methods are gaining prominence due to their ability to perform non-destructive testing of the subsurface. In this context, the detection and characterization of subsurface debondings at an early stage is recommended to avoid further degradation and to maintain the lifespan of these structures. To mitigate the limited time resolution of the conventional GPR devices, this paper develops the detection of thin debonding (of millimeter-order) by monitoring small changes in the time domain GPR data by specific data processing techniques (with certain automatic capabilities). In this paper, we propose to use the supervised machine learning method, namely Two-class Support Vector Machines (SVM) to achieve the objectives. In addition, by means of time domain GPR signal features, we aim at reducing the computational burden and also increase the efficiency of SVM. The method is implemented to process independent 1D GPR A-scan data. Furthermore, the performance assessment of Two-class SVM is carried out on both simulated and field data by means of Sensitivity Analysis to identify the parameters that affect its performance. While simulated data is generated using the analytic Fresnel data model, the field data are UWB Stepped-Frequency GPR (SF-GPR) data which were collected over artificially embedded debondings. The data was acquired during the Accelerated Pavement Tests (APTs) conducted at the IFSTTAR's fatigue carousel to survey debonding growth in the defect-affected zones at various stages of fatigue. Two-class SVM presented the ability to detect thin millimetric debondings. Whereas, sensitivity analysis demonstrated a quick and efficient way to assess the pavement conditions.

Résumé : Abstract : Resumen : This paper presents an overview of a National project carried out in France since 2014. The project aimed assessing the feasibility of using high-speed WIM systems for direct enforcement of overloads, and to prepare their certification. Specifications are proposed for a type-approval procedure, taking into account the requirements of the Ministry of Transport. They follow the International Recommendation R-134 of the OIML, with a few adaptations and derogations. Field tests were carried out over 3-4 years on a motorway with two WIM systems and more than 1,500 trucks and 330 vans from the traffic flow. The accuracy of these systems was assessed both by a statistical approach (COST323) based on tolerance intervals and confidence levels, and a metrological approach based on maximum permissible errors (OIML). Both WIM systems meet the COST323 accuracy class A(5) for trucks and class B(10) for vans, all with fully loaded vehicles. Therefore, the feasibility of using high-speed WIM for direct enforcement was shown. The next step will be the type-approval of the instruments. Finally, a closed test track (Transpolis, near Lyon) was proposed to carry out type-approval tests. Measurements with two instrumented vehicles were done in 2019-2020, in order to assess the maximum variations of the axle impact forces, and to compare them with the measurements on the motorway and with the tolerances of the expected accuracy classes. The closed test site is technically qualified to welcome type-approval tests of WIM systems or direct enforcement. The project paves the way for direct enforcement by WIM.

Résumé : Abstract : Resumen : The world energy consumption is constantly increasing and the research point towards novel energy harvesting technologies. In the field of pavement engineering, the exploitable sources are the solar radiation and the vehicle load. At present, these systems are able to convert the sunlight into electricity thanks to some solar cells placed under a semi-transparent layer (photovoltaic roads), or they can harvest thermal heat by means of solar thermal systems. The thermal gradient of the pavement can be exploited by thermoelectric generators, by heat pipes or by heat-transfer fluids (i.e. water) pumped into a medium (asphalt solar collectors, porous layer or air conduits). The traffic load can be exploited by piezoelectric materials, able to convert the vehicle load into an electrical charge. The aim of this paper is to describe the main pavement energy harvesting technologies, pointing out positives and negatives and providing indications for further optimizations. Finally, the systems are compared in terms of initial cost, electrical output, efficiency and technology readiness level.

Résumé : Abstract : Resumen : The objective of the work is to detect anomalies in waterproof membranes in bridges using ground-penetrating radar (GPR). Defects are determined indirectly by detecting the presence of water (variation of complex permittivity) under the damaged layer. In a first step of the research, Ultra-Wide Band GPR technology is used with a Full-Waveform Inversion (FWI) approach as a punctual and calibration method before the use of deep learning methods for global inversions. This allows them to extract the dielectric and geometric parameters of the sandwich structure and to evaluate the moisture content of concrete. We have used the FWI approach, using gprMax software as a numerical forward model to the multi-layer configuration, to perform parametric study in variations such as: the approximate parameters are known with low accuracy (within large regions). There are some additional complexities we optionally add to the model: noise; some additional layers; a situation with the influence of the antenna factor on the sandwich structure. The modified and extended Nelder-Mead method Shuffled Complex Evolution (SCE), is a robust and model-independent global optimization approach used to optimize the model parameters. It permits us to avoid the inversion being trapped at local minima, so that the global minimum can always be found. Here, instead of the compression step of the Nelder-Mead algorithm, random points are found. After every few cycles, the worst points are replaced with random points in the amount of 33%. FWI was developed and performed for a 2D model using the method described above. The considered sandwich structure is one-dimensional. Thus, we have proved that the method is applicable for various structures (these are layers of different materials). The method allows to restore with good accuracy all the parameters of the structure according to the temporal signal (A-scan), including the dielectric permittivity of concrete. In consequence, we determine whether the concrete is wet or not.

Résumé : Abstract : Resumen : The aim of this work is to optimize the parameters of a mechanical system in order to force fold bifurcation points to appear at targeted frequencies. To this end, an original harmonic balance-based optimization procedure is developed. Functions similar to those employed during bifurcation tracking analyses are used to characterize fold bifurcations in the objective function. The proposed approach is illustrated on a Duffing oscillator with cubic nonlinearity.

Résumé : Abstract : Resumen : GNSS, for many very good reasons among which continuity, is hybridized for land positioning. Indeed, GNSS outages remain frequent in the core of modern cities, despite satellite multi-constellation inter-operating today. Urban positioning is known as a difficult problem, in which satellite measurements, if not occulted, suffer from multipath caused by the receiver local building environment. In Intelligent Transportation Systems and mobility in general, many solutions, applications, innovations rely on satellite positioning. Hybridization with inertial measurements, but also other proprioceptive sensors like odometer/podometer, as well as exteroceptive devices such as cameras, lidars, radars… enable advantages and drawbacks to complement each other leading to improved performances. In the automotive sector, where one's location as well as that of many surrounding objects (infrastructure, other vehicles, pedestrians…) is a key technical component, standardization efforts have been initiated. This article will give an overview of which standards have been produced so far in terms of positioning performance, and will outline the specific issues raised by the performance assessment of hybridized GNSS positioning devices.

Résumé : Abstract : Resumen : In this paper, principal-singular-vector utilization for modal analysis (PUMA) was adaptedto perform time delay estimation on ground-penetrating radar (GPR) data by taking into accountthe shape of the transmitted GPR signal. The super-resolution capability of PUMA was used toseparate overlapping backscattered echoes from a layered pavement structure with some embeddeddebondings. The well-known root-MUSIC algorithm was selected as a benchmark for performanceassessment. The simulation results showed that the proposed PUMA performs very well, especiallyin the case where the sources are totally coherent, and it requires much less computational time thanthe root-MUSIC algorithm.

Résumé : Abstract : Resumen : Evaluating natural frequencies for damage detection and localization is a standard procedure in non-destructive testing (NDT) and structural health monitoring (SHM). In particular, for cables and other prestressed tendons, natural frequencies exhibit high sensitivities to structural changes, which is often demonstrated by comparing the frequencies before and after damage occurred, e.g., using probability of detection (POD) or probability of localization (POL) curves. In this paper, an approach is developed to predict POD/POL curves without any data from the damaged state. The method is based on data from the undamaged state and a numerical model, which is utilized to obtain sensitivity vectors that linearize the relation between frequency changes and changes in structural parameters. At the same time, statistical uncertainties in the frequency estimation process are considered. Based on this method, a cable monitoring strategy is suggested, where sensitivity vectors are first used to calibrate decisive cable properties using model updating, followed by a performance assessment through POD/POL curves, and a continuous damage detection and localization based on statistical tests. The synergic effects of the presented methods are demonstrated by means of a numerical case study on a prestressed cable, where data from a single uni-axial vibration sensor is evaluated. The results indicate that changes in stiffness and axial forces can be distinguished using localization tests, but additional sensors and features are necessary for damage localization along the cable.

Résumé : Abstract : Resumen : Automated pavement distress detection systems have become increasingly sought after by road agencies to increase the efficiency of field surveys and reduce the likelihood of insufficient road condition data. However, many modern approaches are developed without practical testing using real-world scenarios. This study addresses this by practically analysing Deep Learning models to detect pavement distresses using French Secondary road surface images, given the issues of limited available road condition data in those networks. The study specifically explores several experimental and sensitivity-testing strategies using augmentation and hyperparameter case studies to bolster practical model instrumentation and implementation. The tests achieve adequate distress detection performance and provide an understanding of how changing aspects of the workflow influence the actual engineering application, thus taking another step towards low-cost automation of aspects of the pavement management system.

Résumé : Abstract : Resumen : L’objectif de ce travail est d’optimiser la topologie d’amortisseurs de vibrations par frottement sec afin de maximiser leurs propriétés amortissantes. Une méthode couplant l’équilibrage harmonique pour le calcul de la réponse dynamique non-linéaire avec les moving morphable components (MMC) et l’algorithme EGO pour l’optimisation est développée. Une stratégie de clustering est aussi proposée afin de réaliser une analyse de l’impact de la géométrie sur les propriétés amortissantes. L’application à un cas 2D permet de démontrer le fort potentiel de ce types d’approches.

Résumé : Abstract : Resumen : Energy consumed by road vehicles has a high impact on climate changes; indeed this energy use accounts for 23% of total energy-related Green House Gases (GHG) emissions of 2014 global GHG emissions. GHG emissions are growing constantly year after year, in spite of global objectives (COP) and researches on vehicle efficiency and modal shift. The contribution of the infrastructure to lower this energy is less studied, since it is often seen as immuable or too costly. This paper aims to demonstrate that simple and low-cost solutions exist for that purpose. Particularly a methodology has been developed, based on an optimization of the speed layout over an itinerary in order to improve the eco-driving potential of a given road infrastructure. The key point of this work is that inconsistency often exists between vehicle dynamics, road longitudinal profile and changes in regulation speeds. These changes in speed are defining the speed-sectioning of a route, and an optimization of this speed-sectioning can be easily carried out while displacing or modifying speed signs. The objective of this study is to build an optimized speed sectioning which minimizes the fuel consumption for realistic traffic and various driver behaviours, while maintaining the required safety levels. A progressive optimization loop has been worked out with a Python script including an embedded microscopic road traffic simulator. As a result an optimized speed-sectioning is leading to a gain of 227 ml for 60 minutes of simulated flow of 100 veh/h/lane, for a modification of a single speed changing point. The overall benefits are reduced energy consumption, air pollution and noise which otherwise would have been produced by braking. This work brings an effective optimization tool for road managers and its practical application is passive and inexpensive. This methodology is suitable for rural and urbanized territories and easily adaptable to any type of traffic in various countries. In perspectives, the optimization process could be extended to a full road route and to a wide range of different speed-sectioning layouts.

Résumé : Abstract : Resumen : In energy-efficient buildings, the interactions and coupling effects between the building, its environment and its conditions of use play an important role on the energy balance. Recent development in information and communication technologies enable to have real time information about current and future environmental conditions, energy price or CO2 concentrations. Thus, it becomes possible to design building management systems that exploit these data in real time in order to optimize occupants comfort and energy performance. Model predictive control relies on a numerical model and real time measurements to compute an optimal strategy. This paper shows an example of application on a experimental building where both heating and ventilation are simultaneously controlled. Model predictive control is here computed so as to minimize a criterion based on operative temperature and energy consumption. The computation uses data collected on-site by temperature and power sensors, as well as weather data collected online through web-services. We describe here the deployment phase which includes a model calibration process in order to ensure optimality of the results. Both model calibration and optimal management are computed using a multizone thermal model. During optimization phases, the adjoint method is employed to derive efficiently descent algorithms. These choices make the whole software part of the system flexible and fast enough to be embedded on-board on a domestic building management system.

Résumé : Abstract : Resumen : In this paper, we present a processing method to detect millimeter interlayer debondings from Ground Penetrating Radar (GPR) B-scan images. The method is matched to carry out rapid debonding detection at the operational level. A machine learning based outlier-detection strategy namely, One-class Support Vector Machines (OCSVM) is proposed to detect A-scan data vectors which differ from a reference data set collected over a known healthy pavement area. OCSVM is tested on both simulated and experimental data representing GPR data over various artificial millimetric debondings at 2.6 GHz and 4.2 GHz from respectively ground-coupled and air-coupled radar configurations. The experimental data were collected at the Accelerated Pavement Test site located in the Nantes campus of Université Gustave Eiffel. The simulated models on the other hand were generated using a numerical EM solver based on Finite Difference Time Domain (FDTD) method namely, GprMax. Simulation tests allow to conduct sensitivity analysis to determine the robustness of the detection method at various signal-to-noise ratios (10 dB to 60 dB). The proposed OCSVM method demonstrated high performance on both simulated and experimental data to detect thin interlayer debondings over various GPR configurations.

Résumé : Abstract : Resumen : The on-site assessment of dynamic properties of building envelopes is often necessary for accurate analysis of building performance. The main difficulty is that the experiment has to be carried out with unknown thermal loadings on the wall under test. We present a methodology able to address this difficulty: it consists in identifying all-at-once both the sought parameters; i.e., the heat conductivity and capacity, and the unknown thermal loadings. They are obtained as solutions of an inverse problem using only standard temperature measurements as input data. The numerical performance of the methodology, applied to homogeneous walls, is assessed.

Résumé : Abstract : Resumen : As a natural extension of the Kalman filter to systems subject to arbitrary unknown inputs, the Kitanidis filter has been designed by one-step minimization of the trace of the state estimation error covariance matrix. In this technical communiqué, it is shown that the Kitanidis filter is also optimal for the whole gain sequence in the sense of matrix positive definiteness, which notably implies that the Kitanidis filter minimizes not only the trace criterion, but also the matrix spectral norm criterion.

Résumé : Abstract : Resumen : Digital image correlation techniques are well known for motion extraction from video images. Following a two-stage approach, the pixel-level displacement is first estimated by maximizing the cross-correlation between two images, then the estimation is refined in the vicinity of the cross-correlation peak. Among existing subpixel refinement methods, quadratic surface fitting (QSF) provides good performances in terms of accuracy and computational burden. It estimates subpixel displacement by interpolating cross-correlation values with a quadratic surface. The purpose of this paper is to analytically investigate the QSF method. By means of counterexamples, it is first shown in this paper that, contrary to a widespread intuition, the quadratic surface fitted to the pixel-level cross-correlation values in the neighborhood of the cross-correlation peak does not always have a maximum. The main contribution of this paper then consists in establishing the mathematical conditions ensuring the existence of a maximum of this fitted quadratic surface, based on a rigorous analysis. Algorithm modifications for handling the failure cases of the QSF method are also proposed in this paper, in order to consolidate it for subpixel motion extraction. Experimental results based on two typical types of images are also reported.

Résumé : Abstract : Resumen : Surrogate models are data-based approximations of computationally expensive simulations that enable efficient exploration of the model’s design space and informed decision making in many physical domains. The usage of surrogate models in the vibroacoustic domain, however, is challenging due to the non-smooth, complex behavior of wave phenomena. This paper investigates four machine learning (ML) approaches in the modelling of surrogates of sound transmission loss (STL). Feature importance and feature engineering are used to improve the models’ accuracy while increasing their interpretability and physical consistency. The transfer of the proposed techniques to other problems in the vibroacoustic domain and possible limitations of the models are discussed. Experiments show that neural network surrogates with physics-guided features have better accuracy than other ML models across different STL models. Furthermore, sensitivity analysis methods are used to assess how physically coherent the analyzed surrogates are.

Résumé : Abstract : Resumen : Wireless Sensors Networks (WSN) are more and more used in structural health monitoringapplications since they represent a less expensive and non-invasive way to monitorinfrastructures. Most of these applications work by merging or comparing data fromseveral sensors located across the structure. These data often comprise measurementsof physicals phenomenons evolving with time, such as acceleration and temperature.To merge or compare time-dependent data from different sensors they need to be synchronizedso all the samples are time-stamped with the same time reference. An initialsynchronization of the sensors is needed because sensors are independent and thereforecan not be all started at the same time. Subsequent re-synchronizations are also neededsince the sensors keep track of time using their imperfect local clock. A quartz clock willdrift in time due to the sensitivity of the quartz oscillator to its environmental conditions ;thus, synchronization accuracy depends on the quality of the oscillator, environmentalconditions, re-synchronization frequency and time reference quality. The required accuracyof the synchronization depends on applications, for instance, one needs millisecondaccuracy to analyze vibration data, microsecond for acoustic data and nanosecond totime-stamp electromagnetic propagation. Sensors can be synchronized by exchangingtiming information as in the RBS [1], TPSN [2] and FTSP [3] protocols or through anexternal timing reference such as the PPS signal transmitted by the GPS as in [4] and [5].While the first option might be less power hungry, our work in this paper focus on thesecond option as it allows for a better synchronization accuracy. This paper presents asmart-sensor able of time-stamping samples as well as measuring its clock offset andfrequency from a noisy PPS signal. We implemented it on an FPGA to get high speedcounters without software overhead.We then used a Kalman filter to track the offset withmore accuracy and to adjust the sample time-stamps of the sensors. This work is aimingat having the highest time accuracy as possible while minimizing its consequence onsensor power-consumption.

Résumé : Abstract : Resumen : Optimal control techniques can actively maximize buildings efficiency by a smarter HVAC (Heating, Ventilation and AirConditioning) systems operation. All these techniques involve a model of the controlled system and an optimization process based on a cost function. The main difficulty with these methods is to find an accurate model of a system with the right data for training and on-line operation. Our work introduces an ad-joint based method aimed at efficiently computing an optimal predictive command law using a descriptive thermal model of a test case. Our approach has the advantage to enable fast analysis in order to identify the most influential inputs and parameters with respect to the final performance. In this paper, we present numerical results concerning a simple two-room test case.

Résumé : Abstract : Resumen : PEGASE (generic expert platform for embedded wireless applications) is the trade name of a generic wireless sensor platform designed and built by University Gustave Eiffel since 2008. The PEGASE concept is essentially based on a generic vision of its hardware and software capabilities. Hardware genericity is ensured by a principle of plug-in motherboards and daughterboards. The PEGASE motherboard integrates the most common functions of typical data logger systems with specific wireless capabilities and robustness for outdoor field applications: providing computing, power management, multiple I/O and wireless communications, time synchronization. This first-generation PEGASE has been designed in house and sold by a third-party industrial company in thousands of units since 2008. As electronics is a fast-moving field, a second version in 2016 was designed to mitigate the problems of computing power (ram, storage, etc.) and a third one in 2018 incorporating absolute time-stamping of acquisitions has been industrialized. Time-stamping enables data acquired by different sensors to be merged and flight times to be calculated. They are therefore used in a wide range of SHM applications, such as acoustic monitoring of bridge cables, strain gauge monitoring, vibration monitoring, etc. In 2023, the fourth generation of the PEGASE was developed, its electronics not only more powerful, with the addition of a real-time core, a new generation of wi-fi, more storage... But software's improvements have also enabled it to go even further in the field of synchronization. In fact, in addition to absolute time stamping of acquisitions, the PEGASE 4 platform enables in-phase acquisitions. As a result, 2 PEGASE cards with nothing in common will acquire data with an offset of less than a hundred nanoseconds. This new hardware and software design is also accompanied by a new daughter board. The addition of these, together with new synchronization and phase acquisition methods, are used in fields such as guided waves and acoustic emission. Finally, the BSP (board support package) and the software to be installed on the PEGASE board (driver for the various daughter boards, tools, sdk...) are intended to become open source. In this way, third parties can use the boards and the software embedded on them to carry out their own instrumentation cases. In this paper we will present and discuss the new functionalities of this fourth generation. Perspectives will also be addressed.

Résumé : Abstract : Resumen : Track circuits play a major role in railway signaling. In some exceptional conditions, poor rail/wheel contact conditions may lead to a non-detection of the train on the zone. A presentation of the principle of detection by track circuits is proposed to introduce the existing detection criterion. The aim of the paper is first to present new detection approaches based on signal processing on an experiment with a dedicated train running on a track equipped with a track circuit. The second objective is to present a strategy to test new detection criteria on commercial zones over a long period of time (a few months) with the help of the PEGASE acquisition board. PEGASE has been developed by IFSTTAR and the presented work is the result of SNCF/IFSTTAR collaboration.

Résumé : Abstract : Resumen : Noise, Vibration, and Harshness (NVH) performance is a key aspect to evaluate passengers’ comfort in vehicles. At the gearbox level, the gear tooth profile deviations give rise to vibrations during the gear meshing process, which is the source of gear whine noise. Therefore, an NVH design should account for the uncertainties at the gear micro-geometry level, demanding several evaluations of the gearbox model. Our study introduces a gearbox surrogate model based on Neural Networks (NN) to create a fast and accurate copy of the static and dynamic gearbox simulations made in Romax software. An accurate surrogate model was built, enabling a reduction of uncertainty propagation analyses time by a factor of 380, compared with traditional modeling by Romax.

Résumé : Abstract : Resumen : Afin d'assurer l'intégrité des machines tournantes, il est nécessaire de prédire les vitesses critiques et les amplitudes vibratoires associées. Le dimensionnement de telles structures nécessite de prendre en compte la variabilité d'un grand nombre de paramètres de différentes natures. Ce travail propose de prédire le comportement dynamique d'un rotor modélisé par un modèle éléments finis soumis à de nombreux paramètres incertains. Le but est de réaliser de façon efficace une étude paramétrique du système stochastique. Pour ce faire, une méthode de méta-modélisation hybride couplant krigeage et chaos polynomial est utilisée. L'efficacité de la méthode est augmentée par l'introduction des propriétés de symétrie du problème mécanique dans la partie krigeage. Les résultats permettent de prédire avec précision le comportement dynamique du rotor et de réaliser une étude de sensibilité montrant les phénomènes complexes étant mis en jeu.

Résumé : Abstract : Resumen : This work aims to investigate the interest in multi-scale uncertainty quantification for nonlinear dynamic systems with friction interfaces. Indeed, such structures experience uncertainties at different time and space scales due to the friction interface. The focus of this work is to quantify and link the uncertainties from friction interfaces at different scales to the nonlinear dynamic response of the structure. A multi-scale kriging approach is employed to propagate the uncertainty. An industrial test rig for dovetail joints will be used as a test case to demonstrate the proposed methodology.

Résumé : Abstract : Resumen : Many nonlinearities and uncertainties emerge from friction interfaces present in large structural assemblies. They impact significantly the dynamic response and require specific attention. Usually, a macroscopic modelling of the contact surface is employed, coupled with a contact friction law. The latter depends only on a few parameters experiencing large variability leading to uncertain predictions of the dynamic response. Many works have been dedicated to the uncertainty propagation and quantification in friction interfaces using macro-scale modelling. But, it appeared from recent works that the macroscale modelling is not able to capture the physics taking place at the friction interface and that the micro-scale contact model must be considered. Therefore, it is required to develop an efficient multi-scale modelling approach to propagate friction contact uncertainties from the mesoscale to the macro-scale to improve the prediction of the full nonlinear dynamic response. In this context, this work aims to investigate the interest in multi-scale uncertainty quantification for nonlinear dynamic systems with friction interfaces. The focus of this work is to quantify and link the uncertainties from friction interfaces at different scales to the nonlinear dynamic response of the structure. The test case is based on a fan blade root test rig setup, illustrated in Fig. 1(a). The friction interfaces are at the function between the blades and the discs. The nonlinear dynamic response is characterised by the computation of the nonlinear normal modes (NNM) of the mechanical structure. First, the pressure and gap distributions at the contact interfaces are obtained accurately introducing mesoscale considerations. Then, using these real pressure and gap distributions, the NNMs are computed. Uncertainties on mesoscale parameters controlling the surface shape are considered. This uncertainty is propagated through the different scales to obtain the random contact gap and pressure distribution as well as NNMs. Multiscale PCE is exploited in this work for this propagation and is compared to kriging. Results show that such an approach allows getting deep insights into the system understanding for a reduced numerical cost compared to Monte Carlo simulations.

Résumé : Abstract : Resumen : In the context of light aviation, airborne communication between pilots and Air Traffic Control (ATC) is at present only ensured orally via a radio channel. To provide safer and more accessible communications and based on a FANS4ALL initiative, we are developing a multimodal Human-Machine Interface (HMI) combining the sight and touch. The device consists of a tablet placed close to the cockpit and a vibrating vest worn by the pilot. The goal is to enable pilots to stay informed, perceive new instructions and exchange feedback with ATC without a considerable increase in their mental workload or a degradation of their situational awareness that would degrade flight safety. Our application case is centered around deaf & hard of hearing pilots, with the collaboration of FANS4ALL members.

Résumé : Abstract : Resumen : We present in this paper the concept of solar hybrid road and focus on the thermal performances of such system. Main differences between these multi-layer structures with traditional road structures come from the pavement surface, which can be opaque or semi-transparent and the porous sub-layer, submitted to fluid flow. These structures aim at collecting solar energy during the summer season, what helps also to prevent from a too high temperature and urban heat island effect. A finite element model is presented to couple thermal diffusion, hydraulic convection and radiative transfer. This numerical model allows to compute the temperature field for different weather conditions and also to evaluate the thermal performances of the system. Annual simulations are performed and a comparison between two surface layer solutions for different locations and climates is presented and discussed.

Résumé : Abstract : Resumen : Bifurcations organise the dynamics of many natural and engineered systems. They induce qualitative and quantitative changes to a system's dynamics, which can have catastrophic consequences if ignored during design. In this paper, we propose a general computational method to control the local bifurcations of dynamical systems by optimizing design parameters. We define an objective functional that enforces the appearance of local bifurcation points at targeted locations or even encourages their disappearance. The methodology is an efficient alternative to bifurcation tracking techniques capable of handling many design parameters (>10²). The method is demonstrated on a Duffing oscillator featuring a hardening cubic nonlinearity and an autonomous van der Pol-Duffing oscillator coupled to a nonlinear tuned vibration absorber. The finite element model of a clamped-free Euler-Bernoulli beam, coupled with a reduced-order modelling technique, is also used to show the extension to the shape optimization of more complicated structures. Results demonstrate that several local bifurcations of various types can be handled simultaneously by the bifurcation control framework, with both parameter and state target values.

Résumé : Abstract : Resumen : The multi-mode propagation and diffusion properties are crucial informations when studying complex waveguides. In this paper, firstly, the three-dimensional modeling of micro-sized structures is introduced by using the second strain gradient theory. The constitutive relation is deduced while the six quintic Hermite polynomial shape functions are employed for the displacement field. The weak formulations including element stiffness and mass matrices and the force vector are calculated through the Hamilton's principle and the global dynamic stiffness matrix of a unit cell is assembled. Then, free wave propagation characteristics are analyzed by solving eigenvalue problems within the direct wave finite element method framework. The dispersion relations of positive going waves considering the size effects are illustrated. Furthermore, the effects of higher order parameters on the dispersion curves are discussed and the forced responses with two boundary conditions are expounded. Eventually, the wave diffusion including reflection and transmission coefficients are illustrated through simple and complex coupling conditions, respectively. The dynamic analysis of coupled waveguides through the wave finite element method equipped with the second strain gradient is a novel work. The results show that the proposed approach is of significant potential for investigating the wave propagation and diffusion characteristics of micro-sized structures.

Résumé : Abstract : Resumen : Hot boxes, which refer to overheated railroad car wheels and bearings, pose a significant threat to railway operations. Failure to detect and address hot boxes promptly can lead to catastrophic accidents such as derailments and fires. Current wayside hot box detectors operate on the principle that an axle bearing will emit a large amount of heat when it is close to failing. They require principally an infrared (IR) sensor mounted at specific locations along the track, and a signal source coming from a wayside detectors or track circuits to detect if a train is approaching. The IR sensors scanning location, however, should be carefully selected to avoid under/over predicting the operating temperature of the axle bearings and wheels. The dependency of a signal source to activate the system may be problematic as well, not to mention its implementation and maintenance costs. The main contribution of this paper lies with the development of an automatic hot box detection, tracking and counting method by only using the IR cameras. The method combines the YOLO algorithm with the Kalman filter as a tracker. The method was tested with original datasets built with IR images taken from two wayside camera models, cooled and uncooled cameras. The experiments have been conducted on both freight and passenger trains at different times of the day, under clear weather conditions. Apart from the promising results obtained by YOLO, it is found that the Kalman filter further improves the tracking and thus the detection performance, minimizing thereby the incorrect detection or missed detection.

Résumé : Abstract : Resumen : Ballast deterioration, under dynamic loads, remains an important issue on high-speed tracks that can lead to high maintenance costs. This ballast deterioration leads to settlements. Several studies have shown that these settlements were linked to high accelerations produced in the ballast by high-speed train (HST) passages. The solution with bituminous underlayment was used since 1980s in several countries like United States, Italy, Spain, especially on high-traffic and high-speed lines (HSL). In France, the interest in this technique is recent. Following the East European HSL satisfactory behavior, a layer of asphalt concrete was used under the ballast layer of the Bretagne-Pays de la Loire (BPL) HSL. It is intended, in addition to the schedule savings and the protection of the subgrade during the construction phase, to reduce acceleration amplitudes produced at the passage of HST, to ensure moisture stability in the subgrade and thereby to decrease the maintenance costs of the tracks. BPL HSL includes 105 km of innovative track with an asphalt concrete (GB) ballast sublayer, and 77 km with a granular layer under the ballast (UGM). Out of the instrumented sections of the BPL track, 3 sections are constructed with GB subballast layer and one with a layer of UGM as a subballast layer. A total of 127 sensors that includes accelerometers, anchored displacement sensors, temperature and humidity probes, and extensometers are used. Sensors are placed at various positions and depths in the track structures. Data were first acquired during a speed up test phase, under controlled conditions, with the same train passing at speeds ranging from 160 to 352 km/h. This paper presents the different sensors used for the instrumentation as well as the acquisition system installed to collect all measurements. Data treatment and processing is explained in details. Finally, results obtained for different speeds are presented, with a focus on accelerometer and anchored displacement sensor measurements, on two sections, allowing, among others, comparisons between the response of structures with and without asphalt concrete. The role of the GB, as a subballast layer, in damping the vertical displacement of the sub ballast structure and reducing the accelerations peaks in the ballast layer for ballasted tracks is demonstrated.

Résumé : Abstract : Resumen : The phenomena of packing and wear of ballast, under dynamic stresses lead to high maintenance frequencies and high maintenance costs. Several studies have shown that these settlements were linked to the high accelerations produced in the ballast by the passage of highspeed trains. Bituminous sublayers are used since the 1980s in several countries like the United States, Italy, Spain, especially on high-traffic and high-speed lines, to increase the stiffness of the track structure, and reduce these high acceleration levels. Recently in France, this technique attracted interest following the satisfactory behavior of the East European HSL. A high scale project with an asphalt concrete sublayer on the "Bretagne-Pays de la Loire" (BPL) high speed line, was launched. The innovative underlayment is intended, among other things, to reduce the amplitude of the accelerations produced at the passage of high-speed trains. HSL BPL has 105 km of innovative track with an asphalt concrete (GB) sublayer under the ballast, and 77 km with untreated granular (UGM) underlayment. In order to study the dynamic responses of these different structures and to understand the effect of the different layers on the dynamic response, four sections were instrumented (3 sections with an asphalt concrete track structure, and one with a standard granular structure) using, among others, accelerometers, strain gauges, temperature probes, etc. More than 100 sensors have been installed in the railway infrastructure at different positions and depths. Data acquisition has been performed during the speed up test phase , under controlled conditions; the same train crossing the line with speeds ranging from 160 to 352 km/h. Commercial traffic has been traveling on the BPL line since July 2017. In this paper, we will present the instrumentation as well as the acquisition system installed to collect all the measurements. Different results obtained during the speed up test phase are drawn, with a focus on comparisons of measurements between the different sections with UGM and GB layers.

Résumé : Abstract : Resumen : The phenomena of packing and wear of ballast, under dynamic stresses lead to high frequencies and high costs of maintenance. To mitigate this problem, an innovative track structure, with an asphalt concrete layer under the ballast was built on the Bretagne-Pays de la Loire high-speed line (BPL HSL). It is intended, among other things, to reduce the amplitude of the accelerations produced at the passage of High-Speed Trains (HST), major cause of ballast settlements. BPL HSL includes 105 km with an asphalt concrete sub-layer under the ballast, and 77 km with a granular sub-layer. In order to study the dynamic responses of these different structures, four track sections were instrumented using, among others, accelerometers, strain gauges, temperature probes, etc. In this paper, we present the tracks' instrumentation, the acquisition system installed to collect all the measurements, as well as comparative results of dynamic and mechanical behavior between structures since July 2017, the inauguration of the BPL HSL to commercial traffic.

Résumé : Abstract : Resumen : La formation de pelotons de véhicules au sein du trafic routier constitue un élément sensible sur le plan sécuritaire. Intrinsèquement, de part leur densité spatiale, les pelotons représentent une configuration de trafic augmentant le risque d'occurrence d'accidents. Nous proposons une étude du facteur de sur-risque inhérent à l'hétérogénéité des capacités de freinage d'urgence des véhicules qui constituent un peloton. Un modèle d'évolution et une étude statistique sont proposés ; ils sont alimentés par des données mesurées : relevés de pelotons sur le réseau routier d'une part et mesure de lois de décélération de véhicules constituant un panel large du parc automobile actuel d'autre part. Pour une configuration géométrique de peloton donnée, différents tirages aléatoires de véhicules mettent en évidence l'impact de l'hétérogénéité des capacités de freinage des véhicules sur l'occurrence des accidents.

Résumé : Abstract : Resumen : Le développement de méthodes de détection de défauts « hybrides », c’est-à-dire combinant des modèles de simulation physiques et des modèles d’apprentissage basés sur les données, offre de nouvelles perspectives en termes d’évaluation non-destructive et de surveillance vibratoire (SHM). L’utilisation de données virtuelles (i.e. issues de simulations physiques) se heurte souvent à la complexification croissante des structures et matériaux, lesquels nécessitent d’importants moyens de calculs pour générer des données précises, souvent multi-échelles, en quantité suffisante. Ce travail porte sur un formalisme ondulatoire permettant d’effectuer des simulations intensives d’interactions ondes-défauts dans des structures périodiques soumises à des sollicitations dynamiques et modélisées avec un haut niveau de résolution.

Résumé : Abstract : Resumen : The article aims at detecting and quantifying early structural damages using deterministic and probabilistic model updating techniques. To achieve this purpose, local information in a form of optical strain measurement is employed. The strategy consists in updating physical parameters associated to damages, such as Young’s modulus, in order to minimize the gap between the numerical strain obtained from finite element solves and the strain sensor outputs. Generally, the damage estimation is an ill-posed inverse problem, and hence requires regularization. Herein, three model updating techniques are considered involving different type of regularization: classical Tikhonov regularization, Constitutive Relation Error based updating method and Bayesian approach. An illustration of these three approaches is proposed for localizing and quantifying an early damage in a real 8 meter post-tensioned concrete beam. Numerical results show that all the methods properly localize the damaged area and give similar estimation of the damage level

Résumé : Abstract : Resumen : Although several uncertainty quantification algorithms have gained widespread use in applications, recent work suggests that the resultant uncertainty estimates are inaccurate when the model order of the dynamic system is misspecified. In practice, the choice of the model order is either based on heuristics, or it relies on procedures assessing the fit of the identified model to data, disregarding the statistical information content in the obtained estimates. In this paper we go back to the roots of the uncertainty propagation in subspace methods and revise it to account for the erroneously chosen model order. The performance of the proposed approach is illustrated on real data collected from a full-scale wind turbine blade.

Résumé : Abstract : Resumen : Fault detection by modal analysis is a highly developed field in civil engineering. For wind turbines, a loss of isotropy for the rotor can be the consequence of a defect in the angle of attack (pitch) of the blades, or the accumulation of ice, or else the presence of structural defects resulting in a loss of stiffness on one or more blades. It is highly desirable to apply classical OMA techniques, and this despite the rotation of the blades. It is shown in this paper that it is possible to apply LTI approaches on wind turbines similarly to the methodology usually applied to standard civil engineering structures using an approximate Fourier modeling of the eigenmodes. The monitoring of anisotropy using the mode shapes of the estimated modes is validated with an example where a global loss of stiffness of 5% of a rotor blade is simulated.

Résumé : Abstract : Resumen : Subspace-based fault detection methods are widely used for linear time-invariant systems. For linear time-periodic systems, those methods cannot be theoretically used, due to the intrinsic assumptions associated with those methods in the context of linear time-invariant models. Based on the approximation of time-periodic systems as time-invariant ones, those methods can still be applied and adapted to perform change detection for time-periodic systems, through a Gaussian residual built upon the identified modal parameters and their estimated variances. The proposed method is tested and validated on a small numerical model of a rotating wind turbine, with detection and isolation of a blade stiffness reduction leading to rotor anisotropy.

Résumé : Abstract : Resumen : Detecting small and local damages on structures based on ambient vibrations is a major challenge in structural health monitoring. However, being able to identify the minimum damage is essential for quantifying the effectiveness of the instrumentation and for defining the limitations of low-frequency vibration monitoring in general. This paper shows how subspace-based methods could be used by engineers to predict the minimum damage that can be detected. The method employs a Gaussian subspace-based residual vector as a damage-sensitive criterion and evaluates its deviation from zero mean through two different statistical hypothesis tests, a parametric version and a non-parametric one. A sensitivity analysis is carried out to parametrize the deviation from the nominal state, and link it to physical parameters in a finite element model through the Fisher information matrix. This link can also be used to predict the minimum detectable damage, e.g. by prescribing a minimum probability of detection based on code-based reliability concepts. Ultimately, the developed theory is verified by means of a numerical example.

Résumé : Abstract : Resumen : This article describes an approach to evaluate the minimum localizable damage for stochastic subspace-based damage diagnosis. Localizability is defined as the sensitivity to small and local damages (detectability), the ability to narrow down the exact damage location (localization resolution) and the test response of undamaged parameters (false localization alarms). For the analysis, damage is defined as a change in model-based design parameters, for example, material constants or cross-sectional values in a finite element model. Subsequently, the parameter changes are linked to changes in the global damage-sensitive features using sensitivity vectors, and inherent uncertainties (due to stochastic loads and measurement noise) are quantified. This way, local structural parameters can be tested for changes using statistical hypothesis tests, such as the general likelihood ratio and the statistical minmax localization test. Due to the numerical conditioning of the damage localization problem, the sensitivity vectors have to be clustered before damage can be localized. Sensitivity clustering corresponds to a substructuring of the finite element model, where the number of clusters (the localization resolution) is a user-defined input parameter. The main results of this paper are mathematical criteria to calculate the damage detectability and the false alarm susceptibility for different localization resolutions. Moreover, an automated substructuring routine is described that finds the optimal substructure arrangement as a compromise between high damage detectability, high localization resolution, and low false alarm susceptibility. For proof of concept, a numerical case study is presented, where the damage localizability is determined and validated for a cable-stayed bridge.

Résumé : Abstract : Resumen : In recent years, there has been growing interest in the development of reversible thermal storage systems for urban development. The present work deals with one of these systems, which consists of a fluid flow carrying microcapsules containing a phase-change material (mPCM, cf. [1]) circulating in a porous layer integrated into the urban structure. It focuses on the the melting process occurring in the fluid-driven encapsulated phase change material. The fluid equations inside and outside the capsule are solved using the lattice-Boltzmann method on a two-dimensional simulation. A collision operator based on the partial saturated method ensures the boundary conditions at the interfaces between fluid and solid phases. A second set of distribution functions on the lattice is used to solve heat transfer, while an enthalpy-based model provides a realistic solution for the phase change, by means of an enhanced multi-relaxation-time collision operator. The results are detailed and investigated in order to understand the impact of several parameters (Reynolds number of the fluid, Stefan number of the phase-change material) on the phase change kinetics. The effect of the angular velocity of the shell with respect to its content is evaluated in particular.

Résumé : Abstract : Resumen : Les travaux menés dans le cadre du projet ANR-SCaNING visent à développer des capteurs noyés dans le béton afin de suivre l'évolution d'indicateurs de durabilité du béton dans le temps. En effet, pour évaluer les indicateurs avec précision, il est nécessaire de combiner des mesures ultrasonores, résistives et électromagnétiques, ce qui implique une organisation complexe dans la structure et des systèmes de pilotage différents. L'objectif de cet article n'est pas de décrire les capteurs mais de présenter l'architecture de la maquette en béton armé instrumentée et pilotée à distance en justifiant les choix par rapport aux besoins de l'évaluation non destructive des indicateurs de performance du matériau (résistance et porosité) et des profils de suivi de l'état du béton notamment de teneur en eau. Tout d'abord, la maquette est dimensionnée et chaque type de capteur positionné. Ensuite, les systèmes de génération, pilotage des mesures et communication avec le serveur de contrôle sont détaillés. Enfin, les recommandations des projets de recherche précédents relatives à l'évaluation non destructive des indicateurs de durabilité du béton ouvriront vers une discussion sur les besoins spécifiques du suivi en continu de ces indicateurs pour les structures en béton armé.

Résumé : Abstract : Resumen : Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle’s technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

Résumé : Abstract : Resumen : Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle's technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too. In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network. As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.

Résumé : Abstract : Resumen : Damage localization based on ambient vibration data in combination with finite element models can be challenging, in particular due to the large number of parameters in the model and noisy measurement data. Changes in different structural parameters can cause similar changes in datadriven features, and vice versa, it can be challenging to identify which parameter caused the deviation in the data. The problem is ill-conditioned and slight variations in the features, due to inherent statistical uncertainty, can lead to significant errors in the result interpretation. A possible solution is sensitivity-based statistical tests in combination with a parameter clustering approach that considers the uncertainties of data-driven features. In this context, this paper introduces the concept of damage localizability, and provides a framework to evaluate it based on the minimum detectable parameter changes, possible false alarms in unchanged parameters, as well as the achievable damage localization resolution. Since clustering approaches depend on user-defined hyperparameters, such as the number of clusters, the second objective of this paper is to optimize the performance of the damage localization, by adjusting the hyperparameters for clustering. A particular strength of the approach is that the analysis can be conducted based on data and a numerical model from the undamaged structure alone, making it a suitable approach to assess and to optimize the diagnosis performance before damage occurs. For proof of concept, a laboratory case study on a simply-supported steel beam is presented, where the localizability of mass changes is analyzed and optimized.

Résumé : Abstract : Resumen : L’article porte sur la R&D menée à l’Université Gustave Eiffel sur le thème de la localisation pour la conduite automatisée et plus généralement les systèmes de transport intelligent. Nous présentons quelques améliorations imaginées et testées au sein du département Composants et Systèmes en collaboration avec nos partenaires. Ces améliorations illustrent l’intérêt de combiner différentes sources d’informations : plusieurs types de capteurs placés à différents endroits, différentes cartes globales ou locales contenant des informations statiques et dynamiques, certaines solutions basées sur les communications véhicules-infrastructure et inter-véhiculaire. La présentation est organisée en quatre parties : la localisation embarquée (§1), la localisation depuis le bord de voie (§2), le tri des satellites par vision grand angle de l’environnement et le tri des satellites par la carte de l’environnement (§3), la localisation coopérative des véhicules connectés (§4).

Résumé : Abstract : Resumen : The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage lo-calization method based on both a finite element model of a structure and modal parameters estimated from output-only measurements in the damage and reference states. A statistical version of the approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.

Résumé : Abstract : Resumen : Operational Modal Analysis (OMA) identifies modal properties of mechanical structures from vibration data collected from a few sensors under operation conditions. These methods are widely used to monitor civil engineering structures that are modeled as time-invariant systems. However, when dealing with wind turbines and rotating machines, many dedicated OMA techniques were developed to deal with the time-periodic behavior. Existing methods pre-process the data to adapt them to classical identification techniques. Yet, these methods present limitations as either requiring a high number of measured rotation periods, assuming the assumption of an isotropic rotor (i.e. undamaged), or the knowledge of the rotational speed. This work proposes to lift these difficulties by proving that the application of the classical system identification methods can produce meaningful estimates for anisotropy monitoring. This observation is based on directly approximating the time-periodic dynamic behavior of the wind turbine as a properly defined time-invariant system under periodic inputs. It results in the possibility of using classical identification methods without modification to retrieve the system matrices of the approximated time-invariant system. This approach does not require knowing the rotor speed, requiring relatively fewer measurements and it is not restricted to isotropic rotors. The identified modes can be used reliably for the monitoring of operating wind turbines and more especially for fault detection, at the expense of losing a part of the complete description of the periodic system. The resulting anisotropy monitoring approach and its capacities are illustrated in two cases. Firstly, on an academic model of a wind turbine and then on an aero-servo-elastic numerical model of a rotating 10MW wind turbine to demonstrate the ability of the method to deal with realistic and representative data. It is shown for the latest case, from sensors located on the blades of the wind turbine, the approach is able to identify correctly the system properties (frequencies and mode shapes) and is also able to detect efficiently a fault on a blade.

Résumé : Abstract : Resumen : In this paper, subspace identification for wind turbines and more generally rotating periodic systems are investigated. Previous works have stressed the difficulty of modeling such systems as Linear Time Invariant and thus to apply classical Stochastic Subspace Identification. Such works plead for periodic or augmented theories. In this paper, the classical SSI can be applied to recover modal information that is related to the eigenstructure of the instrumented system despite the system excitation being modeled as non-stationary.

Résumé : Abstract : Resumen : The LBM (Lattice Boltzmann Method) is often used in CFD (Computational Fluid Dynamics) for efficient fluid flow simulations. Computation of the permeability of a porous media from direct simulations is a common application which benefits from the ability of the LBM (Lattice Boltzmann Method) to embed porosity parameters. The MM (Mathematical Morphology) is widely used in image processing as the theoretical aspects guaranty robust algorithms for geometrical characterization of shapes appearing in images. The MM is commonly used to compute porosity from porous media images. The union of these two methods has been recently done through the LB3M (Lattice Boltzmann Method for Mathematical Morphology). The present work extends the LB3M to the extraction of porosity and pores segmentation from images. In order to benefit from the full capacity of the LB3M, it is necessary to reformulate and adjust the algorithms in a new paradigm. Thus, the underlying concept and algorithms required for computing the different previous information are detailed. Moreover, a comparison is provided between the permeability resulting from the CFD and MM both implemented by using the LBM. To sum up, this work emphasizes the full capacity of the LB3M to obtain complex transformations and operations issued from the MM theory through completely new and innovative algorithms. The herein challenge is to highlight the abilities of the LB3M to match with physical phenomenons. Indeed, the LB3M keeps the advantages from the MM such as a complete theory, fast convergence, scalability, robustness, etc. while adding the power of the LBM: statistical physics origins, partial differential equation solver, intrinsic properties of parallelization, efficiency, etc.

Résumé : Abstract : Resumen : L’intelligence artificielle (IA) affecte profondément et durablement tous les domaines d’activité, et ceux liés à la route n’y font pas exception. Cet atelier a mis en perspective les attentes métier face à l’IA et donné une part significative au partage d’expériences sur l’entretien des infrastructures comme sur la conduite (plus) autonome. Il a été aussi l’occasion d’une prise de recul sur ce sujet, en mettant dos à dos les besoins métier récurrents et les verrous scientifiques actuels.

Résumé : Abstract : Resumen : For mechanical system structural health monitoring, a new residual generation method is proposed in this paper, inspired by a recent result on subspace system identification. It improves statistical properties of the existing subspace residual, which has been naturally derived from the standard subspace system identification method. Replacing the monitored system state-space model by the Kalman filter one-step ahead predictor is the key element of the improvement in statistical properties, as originally proposed by Verhaegen and Hansson in the design of a new subspace system identification method.

Résumé : Abstract : Resumen : The modes of linear time invariant mechanical systems can be estimated from output-only vibration measurements under ambient excitation conditions with subspace-based system identification methods. In the presence of additional unmeasured periodic excitation, for example due to rotating machinery, the measurements can be described by a state-space model where the periodic input dynamics appear as a subsystem in addition to the structural system of interest. While subspace identification is still consistent in this case, the periodic input may render the modal parameter estimation difficult, and periodic modes often disturb the estimation of close structural modes. The aim of this work is to develop a subspace identification method for the estimation of the structural parameters while rejecting the influence of the periodic input. In the proposed approach, the periodic information is estimated from the data with a non-steady state Kalman filter, and then removed from the original output signal by an orthogonal projection. Consequently, the parameters of the periodic subsystem are rejected from the estimates, and it is shown that the modes of the structural system are consistently estimated. Furthermore, standard data analysis procedures, like the stabilization diagram, are easier to interpret. The proposed method is validated on Monte Carlo simulations and applied to both a laboratory example and a full-scale structure in operation.

Résumé : Abstract : Resumen : This article concerns the determination of the directional emissivity of materials. Several materials (conducting materials or dielectrics) are investigated and the influence of surface roughness is also considered. The experimental method used for the determination is based on the use of a periodic excitation and the recording of the surface temperature variations of the sample using infrared thermography. Several consecutive measurements are performed for emission angles varying from 0° (for the determinat ion of normal emissivity) to 85°. The experimental device developed (SPIDER instrument) is simple compared to existing devices but the variation of directional emissivity is limited to the spectral bandwith of the camera used.

Résumé : Abstract : Resumen : The present work aims to propose the use of Peltier modules for the superficial heat flux measurement, as an alternative to conventional heat flux sensors. In this study, the function of Peltier modules (TEM) as heat flux sensors is compared to the Captec® heat flux sensors (FGT), based on the premise that conventional heat flux sensors such as Captec® have been proven to have acceptable performance for the heat flux measurement, i.e., conduction, convection and radiation. A simple measurement device and a simple general formulation for decoupling the convective and radiative parts from the heat flux measurement are proposed. The latter are implemented in an experimental case presenting weak convective and radiative heat fluxes, using a black-shiny couple of Peltier modules and a black-shiny couple of Captec. The radiative part was found to be the same when comparing FGT and TEM measurements. However, the convective part when using TEM measurements was found to be around two times larger than when using FGT measurement. It has been encountered that this difference is better explained by the geometrical and thermal properties of both sensors.

Résumé : Abstract : Resumen : Air quality monitoring as well as comfort or overall energy performance require accurate information on airflow patterns, although they are particularly difficult to assess in existing buildings. We present an innovative instrumentation system using gas tracers, based on the combined use of several highly sensitive emerging micro-gas chromatographs ($\mu$GC) as pollutant sensors and an identification method for data processing. The strategy used is based on the optimal control theory in which only the time evolution of the components of the velocity field needs to be reconstructed thanks to the use of a proper orthogonal decomposition (POD) method. We present numerical results showing evidence of the performance of the approach in the case of a unimodal flow.

Résumé : Abstract : Resumen : Lately, there has been a growing interest in applying Machine Learning and Digital Twins for the speed-up of acoustic simulations. However, the lack of interpretability and physics foundation inhibit the widespread usage of these black-box models by the scientific community. In this article, global sensitivity analysis and feature engineering techniques are leveraged to improve the interpretability and physical consistency of MLbased simulations of the Sound Transmission Loss problem for a variety of plate materials. Computationally efficient sensitivity analysis is obtained via the Mean Decrease in Impurity, which is the byproduct of the training of the Random Forest surrogate models. The resulting sensitivity indices were shown to be similar to the traditional Sobol indices and more accurate than Fourier amplitude sensitivity testing for small datasets. Moreover, introducing basic expert knowledge into the ML inputs helped reduce the surrogate prediction error and interpret the physical meaning of sensitivity indices throughout the frequency spectrum.

Résumé : Abstract : Resumen : Ces travaux sont menés en collaboration entre l’IFSTTAR, RAILTECH et COLAS et concernent une stratégie de surveillance ayant pour objectifs de garantir la sécurité et de prolonger la durée de vie des structures de génie civil (SHM). Le laboratoire IFSTTAR a avons choisi de tester la technologie Rayleigh pour détecter l'apparition de fissures dans des chaussées bitumineuses et dans des dalles en béton d'une voie ferroviaire sans ballast. Ce choix de technologie s’explique par une excellente résolution spatiale (de l'ordre du centimètre) bien que la portée de mesure soit limitée à 70m. Les tests ont été effectués en laboratoire sur des maquettes à l'échelle 1 qui ont été soumises à des essais de fatigue. Ces tests ont permis de valider l'intégration d'un capteur à fibre optique dans une structure en béton (voie ferroviaire sans ballast) et dans une chaussée bitumineuse, ainsi que d’évaluer la faisabilité et la pertinence de cette technique de détection in-situ de fissures. Les résultats exposés sont prometteurs puisqu'ils permettent d'envisager réellement le développement d'un système de SHM intégré à la chaussée. Certaines questions relatives à la durabilité sur le long terme des câbles optiques insérés à cœur et à la décorrélation des mesures en température et déformation seront étudiées dans un futur proche.

Résumé : Abstract : Resumen : While relatively expensive to build, ballastless track structures are presently seen as an attractive alternative to conventional ballast. Firstly, they are built quickly since the slabs can be cast in place in an automated fashion by a slipform paver. Secondly, with its service life of at least 60 years, they requires little maintenance and hence they offers great availability. Other reasons for using ballastless tracks instead of ballasted tracks are the lack of suitable ballast material and the need of less noise and vibration for high-speed, in particularly. In the framework of a FUI project (n • 072906053), a new ballastless track structure based on concrete slabs was designed and its thermal-mechanical behavior in fatigue under selected mechanical and thermal conditions was tested on a real scale mockup in our laboratory [1,2]. By applying to the slabs both together mechanical stresses and thermal gradients, finite elements simulation and experimental results show that the weather conditions influence significantly the concrete slabs curvatures and by the way, the contact conditions with the underlaying layers. So it is absolutely necessary to take into account this effect in the design of the ballastless track structures in order to guarantee a long target life of at least of 50 years. After design and experimental tests in laboratory, a real ballastless track structure of 1km was built in France at the beginning of year 2013. This structure has 2 tracks on which several trains circulate every day since the beginning of year 2014. Before the construction, it was decided to monitor this structure to verify that the mechanical behavior is conform to the simulations. One part of the instrumentation is dedicated to monitor quasi-continuously the evolution of the curvature of a concrete slab. For this, 2 accelerometers were fixed on the slab under the track. One was placed on the edge and the other in the middle of the slab. The acquisition of the signals by a nano computer (called Pegase and developed at Ifsttar for data acquisition [3]) were performed automatically every time that a threshold is exceeded due to the passage of a train. These data are then send to a web server via a 3G Wireless Network. Many data was thus stored daily for several months. Moreover, several thermocouples were embedded at different depths in order to measure thermal gradients into the track slab.

Résumé : Abstract : Resumen : An infrared system has been developed to monitor transport infrastructures in a stand-alone configuration. It is based on low cost infrared thermal cameras linked with a calculation unit in order to produce a corrected thermal map of the surveyed structure at a selected time step. With the inline version, the data collected feed simplified radiative models running a GPU. With the offline version, the thermal map can be corrected when data are collected under different atmospheric conditions up to foggy night conditions. A model for radiative transmission prediction is proposed and limitations are addressed. Furthermore, the results obtained by image and signal processing methods with data acquired on the transport infrastructure opened to traffic are presented. Finally, conclusions and perspectives for new implementation and new functionalities are presented and discussed.

Résumé : Abstract : Resumen : The present study addresses the thermal behaviour of a modified pavement structure to prevent icing at its surface in adverse winter time conditions or overheating in hot summer conditions. First a multi-physic model based on finite elements method was built to predict the evolution of the surface temperature. In a second time, laboratory experiments on small specimen were carried out and the surface temperature was monitored by infrared thermography. Results obtained are analyzed and performances of the numerical model for real scale outdoor application are discussed. Finally conclusion and perspectives are proposed.

Résumé : Abstract : Resumen : The mobility during winter season in France mainly relies on the use of de-icers, with an amount ranging from two hundreds thousands tons up to two millions tons for the roads only. Besides the economic impact, there are many concerns on their environmental and infrastructure, both on roads and on airports. In such context and in the framework of the R5G (5th Generation Road) project driven by IFSTTAR, investigations were carried out on the way to modify the infrastructure to maintain pavement surface at a temperature above water freezing point. Two distinct approaches, that can could be combined, were selected. The first one consisted in having a heated fluid circulating in a porous layer within an asphalt concrete pavement sample. The second one specifically relied on the use of paraffin phase change materials (PCM) in cement concrete pavement ones. Experiments on enhanced pavement samples were conducted in a climatic chamber to simulate winter conditions for several continuous days, including wind and precipitations, and monitored by infrared thermography. Studies concerning the first approach consisted in identifying the temperature range of the fluid to maintain asphalt concrete surface freezing-free. Both experimental and numerical approaches were conducted showing the importance of the role of the hydraulic conductivity of the porous layer. The analysis of infrared images indicated a surface temperature above freezing excepted in one situation, for which cold air convection and precipitations were combined at pavement surface. A temperature gradient along the surface was also observed. A good agreement was found between numerical and experimental results. To moderate the effect of precipitation, several PCM insertions were chosen and inserted at different depths, with various volumes and packaging (liquid, or powder of encapsulated liquid paraffin). At this stage of the study, rather mixed results were obtained. Delay in the surface ice formation was not conclusive, probably due to deeper location and an unsufficient amount of PCM used. Further investigation to carry out by coupling numerical and experimental approaches would help in refining the use of PCM for this application. The proposed paper will address the presentation of infrared monitoring developed during these studies. (a) (b) (c) (d)

Résumé : Abstract : Resumen : Being able to perform full field easily noninvasive diagnostics for surveillance and monitoring of transport infrastructures and structures is a major preoccupation of many technical offices. Among all the existing electromagnetic methods, active infrared thermography [1] up to long-term thermal monitoring using uncooled infrared cameras is a promising technique [2]. Anyway, except for vision applications [3], there is few results available in literature (mainly on buildings) for outdoor measurements by infrared thermography. So, to complete, a review of specificities and constraints for in situ measurements on large scale structures is proposed. Key points identified are analyzed versus infrared system technological potential solutions available on the shelf or at laboratory level. To introduce transfer from laboratory conditions to real field, we will lean on some laboratory works on active thermography applied to quality control of reinforcement operations by gluing composite (CFRP) plates or tissues on concrete structure [4] or voids in pavement [5]. First, we will introduce and discuss the benefit of using numerical heat transfer modeling to optimize the control process [6,7] or generate virtual thermal image sequences to test post-processing methods [8_,9]. It will be followed by presentation and discussion on experiments carried out using laboratory specimen. Then, some post-processing analysis approaches will be discussed. Finally, considerations on requirements to move from laboratory conditions to real site field measurements will be proposed. Following the laboratory level presentation, a review of various experiments carried out, with an adapted infrared system, on different transport infrastructures or large scale element of Civil Engineering structures in outdoor conditions is given [10,11]. Raw results analysis is proposed. Processed data, obtained from few thermal images [12] to few days of experiments [10-11,13] up to several month of experiments, are presented and discussed. Lessons learned from in situ outdoor experiments are then addressed. In particular, field expertise acquired was used to initiate the development of a new infrared system architecture " Cloud2IR " dedicated to long term monitoring [14]. An overview of this new architecture is proposed and discussed. In particular, benefit of using standards for measured data, but not only, is addressed. Finally, a summary of results obtained and current limitations of studied solutions [15] is given. Perspectives in term of in-situ inspection solutions by active infrared thermography (i.e. under natural solicitations) or by coupling techniques [16] are proposed .

Résumé : Abstract : Resumen : Long term monitoring of transport infrastructures by infrared thermography has been studied and tested on different structures. A first standalone infrared system architecture developed is presented and discussed. Results obtained with such system on different Civil Engineering structures are presented. Some data processing approaches and inverse thermal model for data analysis are introduced and discussed. Lessons learned from experiments carried out in outdoor with such system are listed and analyzed. Then, a new generation of infrared system architecture is proposed. Finally, conclusions and perspectives are addressed.

Résumé : Abstract : Resumen : The phenomena of settlement and wear of the ballast under dynamic stresses lead to high frequencies and high maintenance costs on high-speed railway lines. Studies have shown that these settlements are linked to high accelerations produced in the ballast by the passage of high-speed trains (HST). A layer of asphalt concrete (GB) was introduced under the ballast layer on the high-speed line Bretagne-Pays de Loire (BPL HSL). It is intended, among other things, to reduce the amplitude of accelerations produced at the passage of the HST and thus improve the durability of the track. The BPL HSL spans 105 km, with a sublayer of asphalt concrete under the ballast and 77 kmwith a granular sublayer (UGM). To evaluate the performance of the structures with bituminous sublayer and to compare it with traditional structures with granular sublayer, four track sections have been instrumented during construction. This article presents the different sensors of the instrumentation, as well as the acquisition system installed to collect measurements. The focus, in this study, concerns the temperature, water content, and vertical settlement measurements made on the instrumented sections. Temperature variations recorded during two years on the railway structure with bituminous sublayer were analyzed and compared with those measured on a classical bituminous pavement. Influence of the bituminous layer on water infiltration and track settlements has also been studied.

Résumé : Abstract : Resumen : In order to ensure safe driving without human supervision the autonomous vehicles are using a wide range of sensors as cameras, lasers, lidar to evaluate the road scene and to measure the vehicle trajectory. The vehicle weight is of critical importance since it affects both braking dynamics and stability in curves. This total weight depends on the number of occupants and goods or luggage, so it has to be dynamically estimated, at least at each traveling start. The literature review indicates that some infrastructure-based sensors exist but tire related systems are preferable if the vehicles can start routes at indefinite points. In this work an experimental system is developed to estimated the load applied to a non rolling tire with several concurrent sensors. First the elongation of the tire to road contact patch is estimated by the means of an internal optical fiber sensor based on Rayleigh scattering interferometry, since this elongation is related to the applied load according to literature results. A laser sensor situated inside the tire is giving the tire sidewalls deflection which is related to applied load too. At last tire to road contact patch length and width are estimated by using Fuji pressure sensible paper. As a results for loads of 2.8 to 4.8 kN the optical sensor and the laser sensor are leading to load estimation error lower than 3%. Moreover the estimated tire contact patch is confirming the tire belt elongation estimated by the optical fiber sensor. In perspective the two measurements from optical fiber and laser could be used by autonomous vehicles in order to have a redundant load estimation for one or several wheel, under vehicle symmetry hypothesis.

Résumé : Abstract : Resumen : Modern vehicles are using control and safety driving algorithms fed by various evaluations such as wheel speeds or road environmental conditions. Wheel load evaluation could be useful for such algorithms, particularly for extreme vehicle loading or uneven loads. For now, smart tires are only equipped by tire pressure monitoring systems (TPMS) and temperature sensors. Manufacturers are still working on in-tire sensors, such as load sensors, to create the next generation of smart tires. The present work aims at demonstrating that a static tire instrumented with an internal optical fiber allows the wheel load estimation for every wheel angular position. Experiments have been carried out with a static tire loaded with a hydraulic press and instrumented with both an internal optical fiber and an embedded laser. Load estimation is performed both from tire deflection and contact patch length evaluations. For several applied loads from 2800 to 4800 N, optical fiber load estimation is realized with a relative error of 1% to 3%, almost as precisely as that with the embedded laser, but with the advantage of the load estimation regardless of the wheel angular position. In perspective, the developed methodology based on an in-tire optical fiber could be used for continuous wheel load estimation for moving vehicles, benefiting control and on-board safety systems.

Résumé : Abstract : Resumen : In the construction sector, most of the measurements carried out from IR camera devices are exploited in a qualitative way (e.g. observation of thermal bridges). However, unless a quantitative analysis is realized, it is not possible to assess the impact of the observed phenomena. Most of research efforts and proposed solutions to identify quantified thermal properties (e.g. U-values) have to be completed, adapted to the built environment and validated in experimental and real conditions to allow quantified assessment of materials thermal properties thanks to IR camera devices [1]. We still need several steps in terms of scientific and technical developments for such technological progress. The H2020 European Built2Spec research project (http://built2spec-project.eu/) aims at giving highlights on that. Heat transfer through the walls are generally model by 1D heat equation in the wall depth. The built is composed by a multilayer domain representing the construction process. In this context, the thermal parameters of the wall are piecewise constant space functions. We propose a methodology to recover the vector of the wall thermal properties (conductivity and capacity) from boundary measurements obtained from an IR camera. It formulates as an inverse problem where the unknown are sought as minimizers of a cost function evaluating the gap between the measures and the model response. This optimization problem is non linear, and we solve it with the Levenberg-Marquardt algorithm coupled with the conjugate gradient method [2-3]. To shorten the time of the identification process, we use the adjoint method coming from the control theory [4]. This method fasten the gradient computation by solving an associated model, named the adjoint model. We study the ability of the procedure to reconstruct internal wall constitution from different environmental conditions. Furthermore, we propose a controlled experimental test to evaluate the method in laboratory conditions. References [1] L. Ibos, J-P. Monchau, V. Feuillet, Y. Candau, A comparative study of in-situ measurement methods of a building wall thermal resistance using infrared thermography, in

Résumé : Abstract : Resumen : This paper presents a method to identify wave equations' parameters using wave dispersion characteristics (k-space) on two-dimensional domains. The proposed approach uses the minimization of the difference of an analytic formulation of the dispersion relation to wavenumbers calculated from solution fields. The implementation of partial differential equations (PDE) resolution on finite element software is explained and tested with analytic solutions in order to generate the test solution fields for the identification process. The coefficient identification is tested on solution fields generated by finite element solver for some 2 ndand 4 th-order equations. In particular the test cases are the equations at different frequencies of deflection of isotropic and orthotropic membrane, flexion of isotropic and orthotropic plate and an original model of orthotropic plate equivalent to a bi-directional ribbed plate. In the limits of the spatial sampling rate and the domain size, the process allows an accurate retrieval of the wave equation parameters.

Résumé : Abstract : Resumen : Les procédures d’audit actuelles ne parviennent pas à prédire les consommations réelles des bâtiments existants. Cet écart entre les prédictions et les mesures s’explique par les grandes incertitudes présentes dans les données d’entrée des logiciels de simulation thermique des bâtiments. Parmi les incertitudes, on trouve les paramètres physiques du bâtiment, ainsi que les conditions d’usage et les données météo. Nous proposons une méthode d’audit qui identifie la donnée météo de la température du ciel, la conductivité des parois, et les gains internes à partir de seulement trois capteurs de température. De plus, nous démontrons la possibilité de séparer deux composantes constitutives d’une source (les gains internes) lorsque celles-ci possèdent des dynamiques différentes.

Résumé : Abstract : Resumen : Subspace system identification methods are widely used in output-only vibration analysis of civil structures, known as operational modal analysis. With the advent of new sensor technologies, such as video camera-based full field displacement or velocity measurements, the number of measured outputs is quickly increasing. In this paper, we propose principal component analysis-based data size reduction methods for efficient application of subspace methods, while preserving the high spatial resolution of the identified mode shapes for detailed modal analysis.

Résumé : Abstract : Resumen : Two additive thermal sources are generally not simultaneously distinguishable from the only observation of their effect on the heat balance. However, there are cases where information about the variation regularity of these sources is known. This is typically the case of convective internal gains in the building, for which the use scenarios create discontinuous inputs while heat gains relating to the air leakage are regular in time. In the present paper, we introduce a method aiming to distinguish heat sources using this a priori knowledge about their dynamics. We provide numerical and experimental evidence that the method succeeds in separating/distinguishing these kind of sources. This method could be applied to the identification of the occupancy rate for measurement and verification (M&V) plans or smart home systems such as learning thermostats.

Résumé : Abstract : Resumen : Statistical subspace-based change detection residuals have been developed to infer a change in the eigenstructure of linear systems. Their statistical properties have been properly evaluated in the case of a known reference and constant noise properties. Previous residuals have favored the family of null space-based approaches, whereas the possibility of using other metrics such as the Mahalanobis distance has been omitted. This paper investigates the development and study of such a norm under the premise of a varying noise covariance. Its statistical properties have been studied and tested on a numerical example of a mechanical system.

Résumé : Abstract : Resumen : In the context of detecting changes in structural systems, multiple vibration-based damage detection methods have been proposed and successfully applied to both mechanical and civil structures over the past years. One of the popular schemes is based on a robust subspace-based residual and enjoys favorable statistical and computational properties, like invariance to changes in the excitation covariance and numerical stability. This paper presents an alternative Gaussian residual that is based on the difference of normalized Hankel matrices between reference and damaged states, which can be easily computed. The statistical properties of the residual are reported and used for efficient hypothesis testing. Its robustness to excitation changes is shown. The proposed scheme is evaluated in numerical simulations, validating its robustness, and tested on real data sets from a full scale bridge.

Résumé : Abstract : Resumen : This database was collected using several ground-penetrating radar (GPR) systems over hot-mix multi-layer samples, designed under controlled conditions. The experimentation campaign was conducted during the French research project ACIMP (ANR-18-CE22-0020), funded by the French National Research Agency (ANR). One of the project’s objective was the detection of debonded asphalt layers. The database has been extended by hot-mix asphalt samples featuring varying tack coat dosages.

Résumé : Abstract : Resumen : Integrally bladed disks (blisk) have been widely used in the turbo-machinery industry due to its high aerodynamic performance and structural efficiency. A friction ring damper (FRD) is usually integrated in the system to improve its low damping. However, the design of the geometry of this FRD become complex and computationally expensive due to the strong nonlinearities from friction interfaces. In this work, we propose an efficient modelling strategy based on advanced nonlinear modal analysis and Kriging surrogate models to design and optimize the geometry of a 3D FRD attached to a high fidelity full-scale blisk. The 3D ring damper is parametrised with a few key geometrical parameters. The impact of each geometric parameter and their sensitivities to nonlinear dynamic response can be efficiently assessed using Kriging meta-modelling based on a few damped nonlinear normal modes. Results demonstrate that the damping performances of ring dampers can be substantially optimized through the proposed modelling strategy whilst key insights for the design of the rings are given. It is also demonstrated that the distribution of the contact normal load on the contact interfaces has a strong influence on the damping performances and can be effectively tuned via the upper surface geometry of the ring dampers.

Résumé : Abstract : Resumen : This paper presents the numerical method GPILE to calculate the scattered EM field by any stratified 1D medium composed of three random rough interfaces separating homogeneous media. GPILE is an extension of the PILE (Propagation Inside-Layer-Expansion) method, which considers only twointerfaces. Both methods rely on the rigorous implementation of the Maxwell equations, with a simple matrix formulation and has a straightforward physical interpretation. In particular, this method allows us to distinguish the primary echo of the upper surface, and also, the multiple echoes arising from the intermediate and lower interfaces. This method is applied in this paper to simulate the ground penetrating radar (GPR) signal atnadir. The simulated signals are analyzed to study the sensitivity of the GPR signal to any material debonding within the pavementlayered structure.

Résumé : Abstract : Resumen : The paper gives an overview of a ground penetrating radar (GPR) experiment to survey debonding areas within pavement structure during accelerated pavement tests (APT) conducted on the university Gustave Eiffel’s fatigue carrousel. Thirteen artificial defect sections composed of three types of defects (Tack-free, Geotextile, and Sand-based) were embedded during the construction phase between the top and the base layers. The data were collected in two stages covering the entire life cycle of the pavement structure using four GPR systems: An air-coupled ultra-wideband GPR (SF-GPR), two wideband 2D ground coupled GPRs (a SIR-4000 with a 1.5 GHz antenna and a 2.6 GHz-StructureScan from GSSI manufacturer), and a wideband 3D GPR (from 3D-radar manufacturer). The first stage of the experiments took place in 2012–2013 and lasted up to 300 K loadings. During this stage, the pavement structure presented no clear degradation. The second stage of experiments was conducted in 2019 and continued until the pavement surface demonstrated a strong degradation, which was observed at 800 K loadings. At the end of the GPR experiments, several trenches were cut at various sections to get the ground truth of the pavement structure. Finally, the GPR data are processed using the conventional amplitude ratio test to study the evolution of the echoes coming from the debonded areas.

Résumé : Abstract : Resumen : Global Navigation Satellite System (GNSS) integrity is defined as a measure of trust that can be placed in the correctness of the information supplied by the total system. Initially developed for safety critical applications in the aeronautic domain, this concept has attracted more and more attention from terrestrial GNSS-based applications in recent years. The main problem of integrity monitoring for urban transport applications is related to GNSS signal degradation due to local effects such as multipath and non-line-of-sight reception. This article proposes two integrity monitoring schemes with two classes of approaches, based on either the snapshot weighted least-squares residual or sequential weighted extended Kalman filter innovation. The integrity monitoring schemes are mainly realized by two modules: accuracy enhancement, in which measurement errors are better characterized, and integrity monitoring, in which one of the fault detection and exclusion techniques, i.e., the Danish reweighting method, is applied. The results with real GPS data collected in urban canyons show that the proposed system can effectively improve positioning accuracy and guarantee system integrity.

Résumé : Abstract : Resumen : The conversion of vibrations into electrical energy for powering low-power small electronic components has been investigated by researchers from different disciplines in the last decade. Among the possible mechanisms, piezoelectricity has received particular attention. In the field of low frequency cantileverbased vibration energy harvesters, the proof mass is essential in order to reduce the resonance frequency and increase the stress along the beam to increase the output power. In this work, a manufacturing process of a micro generator is proposed to easily modify and increase the dimensions of the cantilever, and thus tune its resonance frequency. The effect of the position of the mass on the performances of this flexible piezoelectric energy harvester is also studied. For a proof mass at 8 cm from clamping, we obtain a resonance frequency of 9.9 Hz, a maximum power of 127 W against a resonance frequency of 16 Hz and a maximum power of 72 W with a mass at 4 cm. This shows that the maximum power extracted varies in ?= 1/fR for a constant acceleration of 1 g (9.81 m/s2), as expected theoretically. These promising results show that the prototype can be considered for a low power application as an energy harvesting-based micro-generator.

Résumé : Abstract : Resumen : In the topic of the development of the market of flexible electronic, piezoelectric lead zirconate titanate (PZT) thin film have been elaborated using a Chemical Solution Deposition (CSD) process and a commercial aluminum (Al) foil as substrate. Despite of the low fusion temperature of Al, PZT thin films can be crystallized in the perovskite structure without pyrochlore phase at 650 °C. Due to the flexibility of the aluminium foil, very original forms have been obtained. Dielectric, ferroelectric and piezoelectric properties have been improved by the use of a conductive electrode of dioxide of ruthenium (RuO2), resulting in an Al/RuO2/PZT/Al capacitor. For energy harvesting applications, experiments have shown that the conductive oxide layer downgrade the harvested power because of the rise of the relative permittivity. However, the use of Interdigited Electrodes (IDE) structure instead of Metal-Insulate-Metal (MIM) structure allows to increase the harvested power up to 8 μW@4 Hz.

Résumé : Abstract : Resumen : Dans le cadre des projets N-air-J, MIGAC et Airbivore, financés respectivement par la région Pays de la Loire, le RFI WISE et le CNRS, des films piézoélectriques flexibles de zircono-titanate de plomb (PZT) ont été développés sur substrat flexibles au sein de l’Institut d’Électronique et de Télécommunications de Rennes (IETR). L’objectif principal de ces projets est d’étudier la possibilité de récupérer l’énergie mécanique de courants d’air grâce à l’utilisation de micro-générateurs piézoélectriques flexibles. Les couches minces de PZT, lorsque elles sont électriquement polarisées, possèdent en effet des propriétés piézoélectriques macroscopiques leur permettant de convertir l’énergie mécanique en énergie électrique, et inversement. De par le budget thermique élevé nécessaire à la cristallisation du PZT (autour de 650 °C), ces couches minces sont généralement déposées sur des substrats rigides de silicium, de saphir ou encore de MgO. Dans cette présentation est décrit le procédé de fabrication par Chemical Solution Deposition (CSD) de films de PZT flexibles déposés sur feuille d’aluminium en structure Métal-Isolant-Métal (MIM)1, ainsi que les caractérisations ferroélectriques et piézoélectriques des condensateurs obtenus. De par leur faible épaisseur (20 µm) et la conformabilité de l’aluminium, les films réalisés sont facilement découpables et permettent d’obtenir des géométries originales. Ces films, étant réalisés pour des applications de récupération d’énergie, ont été caractérisés sur un banc mécanique à des fréquences d’excitations forcées très basses (dans la gamme de l’Hertz). Du fait de la forte permittivité du PZT et de sa faible épaisseur, le générateur piézoélectrique présente une forte capacité (autour de 200 nF), ce qui limite la tension de sortie du générateur à quelques centaines de millivolts. Afin d’augmenter cette tension de sortie, et par conséquent la puissance du générateur, le film de PZT est transféré par voie chimique sur un film polymère de polytéréphtalate d’éthylène (PET). La suppression du plan de masse, allié à une structure d’électrodes interdigitées (IDE) permet d’obtenir des tensions de sortie supérieures à 30V.

Résumé : Abstract : Resumen : Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models { each estimated from data measured in a reference state { are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex whenthe different points of interpolation correspond to dierent noise conditions. Then conicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to dierent noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.

Résumé : Abstract : Resumen : This paper studies interval estimation for discrete-time linear systems with unknown but bounded disturbances. Inspired by the parity space approach, we propose a point estimator with fixed-time convergence property. The estimator is combined with the zonotope-based interval analysis to achieve fast interval estimation. The parameter matrix in the estimator is optimized by minimizing the length of the edges of the outer box of the error zonotope. It is formulated as L1 optimization problem and can be efficiently solved by linear programming. Comparison studies illustrate the superiority of the proposed method over existing techniques.

Résumé : Abstract : Resumen : The sun is by far the largest source of clean energy and the road network is daily exposed to this big amount of radiation. At present, the solar radiation can be directly converted into electrical power thanks to the photovoltaic effect, or harvested by means of a heat-transfer fluid. This paper deals with the second solution, proposing a multilayer road system able to exploit the thermal gradient of the pavement. The system is composed of a porous core, sandwiched between two layers. The base layer is waterproof and it contributes to the mechanical performance of the entire system; the core is a porous concrete mixture for the circulation of the heat-transfer fluid and it works as a solar collector and the top layer is a semi-transparent material designed to support the traffic vehicles, guarantee the skid resistance and maximize the harvested energy. At first, the authors worked on the mix-design of the porous core and of the semi-transparent layer. Secondly, they built a working prototype in order to evaluate harvested heat energy in labcondition. In comparison to the state-of-art, the results show a clear improvement in terms of energy harvesting, leading the way for the construction of a full-scale prototype and a comprehensive evaluation in-situ conditions.

Résumé : Abstract : Resumen : Global Navigation Satellite Systems (GNSS) have continually involved in our daily life in the past decades. Among all these GNSS-based applications, there is an increasing number of GNSS-based urban transport applications, especially the critical liability ones, such as the Electronic Toll Collection (ETC) and the Intelligent Transport System (ITS). For these GNSS-based applications, not only positioning accuracy but also its reliability is required. Latter has attracted more and more attention from urban GNSS users. Yet urban environments present great challenges for common commercial GNSS receivers since the existence of local effects such as multipath and the Non-Line-of-Sight (NLOS) receptions. The main objective of this paper is to investigate the integrity performance one can expect from a lowcost common GNSS receiver. Under this framework, this paper proposes an innovation-based integrity monitoring scheme by using an Extended Kalman Filter (EKF) with the help of carrierpower-to-noise ratio (C/N0) weighting. The derivations of the Horizontal Protection Level (HPL) for the EKF innovation-based integrity monitoring is also presented in detail. The accuracy and integrity performances are evaluated with real GPS data collected in urban environments. Compared to the classic residual-based snapshot Receiver Autonomous Integrity Monitoring (RAIM), the innovation-based EKF integrity monitoring scheme presents more advantages in terms of accuracy and integrity. With the real dataset collected in urban canyon of Nantes center, the results show that the average size of horizontal position error has been reduced by 1.15 meter with the proposed approach compared to the classic weighted RAIM, the median size of HPL has been reduced by 7.5 meters and the algorithm availability is 100% instead of 98.57%.

Résumé : Abstract : Resumen : In relation to the sudden and generalized occurrence of potholes observed on pavements subsequently to rainfalls and freezing temperatures, this paper is focused on studying the behavior of partially-water-saturated asphalt concrete (AC) under freezing conditions. Most of previous work on that topic has been devoted to the damaging effect of repeated frost/thaw cycles on wet AC, viewed through the loss of stiffness of the material. The novel aspect presented in this paper deals with the characterization and modeling of the swelling strain effect induced by solidification of pore water at negative temperatures. Transposed to the case of a pavement, we believe indeed that this effect is prone to generate tensile stress at interfaces between AC layers and to generate delamination at short term, ending up into potholes. The present research is a first step towards assessment of this assumption by means of future experimental and numerical analyses at the structural level. Investigations reported in this paper rely on two types of experimental test carried out in the laboratory. The first is performed under free stress condition while the other is subjected to restrained strain. The experimental results from these two tests show the development of significant swelling strains and induced stresses in the partially saturated asphalt specimens, respectively. These two effects are attributed to the phase change of pore water from liquid to solid. A constitutive law taking into account viscoelasticity of AC, thermal expansion and swelling induced by frost is elaborated. This law is implemented in a numerical program and validated against the experimental results. In particular, it is shown that this law is able to make the connection between the magnitudes of the swelling strain and the frost-induced stress stemming from the two tests.

Résumé : Abstract : Resumen : This paper aims to experimentally evaluate a simplified vision-based method for structural health monitoring (SHM). Contrary to conventional solutions that rely on extracting motions through image processing, this paper proposes to conduct the SHM analysis by the direct processing of pixel brightness without extracting the motion signals beforehand. After some pre-processing steps, it is shown that the brightness data reveal essential information about the dynamic characteristics of the monitored vibrating structure. Furthermore, the low-level information of the pixel is compensated by an efficient selection of the so called "active pixels" throughout the image time flow. Finally, a subspace system identification-based method is applied to the brightness data, so that the modal parameters with uncertainty bounds are estimated within a large range of model orders displayed in a stabilization diagram. The experiment database consists of image time flows of a cantilever beam excited by a shake table driven by a band limited random noise. Modal vibrations range from 1 to 173 Hz.

Résumé : Abstract : Resumen : Abstract This study explores the variation in mechanical properties of additively manufactured composite structures for robotic applications with different infill densities and layer heights using fused deposition modelling (FDM). Glass fibre-reinforced polyamide (GFRP), and carbon fibre-reinforced polyamide (CFRP) filaments are used, and the specimens are printed with 20%, 40%, 60% and 100% infill density lattice structures for tensile and three-point bending tests. These printed samples are examined in the microscope to gain more understanding of the microstructure of the printed composites. To characterise the mechanical properties, a set of tensile and three-point bend tests are conducted on the manufactured composite samples. Test results indicate the variations in tensile strength and Young’s modulus of specimens based on the printing parameters and reveal the tensile and bending behaviour of those printed composite structures against varying infill ratios and reinforcing fibres. The experimental findings are also compared to analytical and empirical modelling approaches. Finally, based on the results, the applications of the additively manufactured structure to the robotic components are presented.

Résumé : Abstract : Resumen : An UWB ground-coupled radar has been designed to operate from 460 MHz to beyond 4 GHz and essentially for civil engineering applications. Full-wave modeling using the FDTD approach has allowed to study in details the antenna radiation characteristics in air, in the presence of a soil and as a constituent in a bistatic GPR system. The polarization diversity in the E and H-planes is an important aspect which has been studied in order to further detect the orientation of damages (cracks or delaminations) in civil engineering structures. The analysis of the hyperbola signatures has allowed to evaluate the ability of the radar to detect small canonical buried objects.

Résumé : Abstract : Resumen : An in situ measurement device based on an active approach is under development within the scope of the RESBATI Project. The implementation strategy will consist of determining the thermal resistance of several types of solid walls at various scales: _ Reference methods using a guarded hot plate (basic LNE instrument) will serve to characterize this parameter at the material level under laboratory conditions; _ Use of climate-controlled chambers (i.e. REBECCA at the LNE facility), for which environmental conditions and thermal constraints are perfectly controlled and known, will yield the thermal resistance of building walls at the laboratory scale; _ The prototype, based in an active mode, _ The research prototype, is controlled by an in-house low-cost data logger. It is coupled to data processing by inverse methods; _ The guarded hot box at CSTB was also use to make cross characterization of instrumented walls used in the present study. This paper will present the development of a test method to determine heat loss through a wall installed in an energy room by an active method compared to referenced methods.

Résumé : Abstract : Resumen : Dans cette étude numérique nous présentons une approche permettant d'introduire des informations a priori dans une méthode d'identification des champs de propriétés thermiques internes d'une paroi épaisse à partir de mesures obtenues par thermographie infrarouge. Elle s'appuie sur un couplage avec une méthode de reconstruction de données électromagnétiques issues de mesures obtenues à l'aide d'un radar géophysique (géoradar). Cette nouvelle approche a pour but d'améliorer la précision des reconstructions effectuées à l'aide de la seule méthode d'identification thermique sous sollicitation naturelle quasi périodique. Nomenclature c V capacité thermique volumique f fréquence du signal électromagnétiquêélectromagnétiquê f (u) réponse thermique associée à u aux points de mesure k conductivité thermique q source volumique de chaleur r point du domaine r m point de mesure t temps u = {c v , k}vecteur paramètre thermique u n , v n vecteurs singuliers u 0 estimation a priori des paramètres ther-miques J fonctionnelle à minimiser pour la reconstruction thermique T température B, Ddensités de flux magnétique et électrique E, Hchamps électrique et magnétique J c , J s densités de courant induites par le champ électrique et la source électrique C espace des contraintes F ensemble des fréquences analysées M ensemble des points de mesure (électroma-gnétisme) ou espace des mesures (thermique) U espace des paramètres thermiques A DB opérateur liant les variations des paramètres électriques au champ électrique diffus paramètre de Tikhonov r permittivité électrique relative b permittivité électrique relative du domaine sans défaut χ variation de la permittivité électrique µ paramètre de pénalisation des contraintes ω pulsation ϕ retard de phase ρ densité électrique de charge ρ m densité magnétique de charge σ conductivité électrique σ n valeurs singulières θ p température dans la paroi p Γ frontière supérieure du domaine Γ 0 frontières inférieure et verticales du domaine Ω d ensemble des points du domaine discrétisé φ s flux solaire a , c indices relatifs à l'air et au ciel conv indice relatif aux phénomènes convectifs ray indice relatif aux phénomènes radiatifs

Résumé : Abstract : Resumen : Cette étude porte sur l'´evaluation simultanée de l'émissivité et de la température de surface d'objets observés par thermographie infrarouge in-situ. La mesure de la température par thermographie infrarouge se heurte au manque de connaissances des propriétés radiatives de la scène réelle. Une cible virtuelle composée de quatre matériaux différents est définie. L'éclairement reçu depuis cette cible par une caméra infrarouge est estimé par la méthode des radiosités progressives mise en oeuvre sur carte graphique. Ces simulations nous permettent d'évaluer la sensibilité de quatre méthodes de séparation de l'émissivité et de la température.

Résumé : Abstract : Resumen : Although Kalman filter (KF) was originally proposed for system control i.e. steering a system as desired by monitoring the system states, its application for parameter estimation problems is widespread because of the excellent similarity between these two apparently different problem types in state space description. In standard Kalman filter, system dynamics is described through the dynamics of certain internal variable, termed as states, evolving over time as defined by an assumed process model, while a measurement model maps these states to measurements. In some parameter estimation problems, the system is replaced by a state space formulation of the dynamic model with parameters appended in the unobserved states and collectively observed through the response measurements. Filtering based parameter estimation problems are thus inherently nonlinear due to the required nonlinear mapping of parameters to the corresponding observations. Being a linear estimator, Kalman Filter (KF) cannot be employed for such nonlinear system estimation and alternative filtering algorithms (eg. Particle filter) are therefore generally used. However, being model based, these filters optimally estimate the parameters of a quasi-static model of the real dynamic system. Consequently, any time variation in the system dynamics may completely diverge the estimation yielding a false or infeasible solution. By decoupling the estimation of system states and parameters, and applying concurrent filtering strategy that attempts conditional estimation of states based on parameters and vice versa, time varying systems can be estimated. This article attempts to combine KF with Particle filter (PF) and apply them for estimation of states and system parameters respectively on a system with correlated noise in process and measurement. The idea is to nest a bank of linear KFs for state estimation within a PF environment that estimates the parameters. This facilitates employing relatively less expensive linear KF for linear state estimation problem while costly PF is employed only for parameter estimation. Additionally, the proposed algorithm also takes care of those systems for which system and measurement noises are not uncorrelated as it is commonly idealized in standard filtering algorithms. As an example, for mechanical systems under ambient vibration it happens when acceleration response is considered as measurement. Thus the process and measurement noise in these system descriptions are obviously correlated. For this, an improved description for the Kalman gain is developed. Further, to enhance the consistency of particle filtering based parameter estimation involving high dimensional parameter space, a new temporal evolution strategy for the particles is defined. This strategy aims at restricting the solution from diverging (up to the point of no return) because of an isolated event of infeasible estimation which is very much likely especially when dealing with high dimensional parameter space.

Résumé : Abstract : Resumen : Tensegrities form a special case of truss, wherein compression members (struts/bars) float within a network of tension members (cables). Tensegrities are characterized by the presence of at least one infinitesimal mechanism stabilized with member pre-stress to ensure equilibrium. Over prolonged usage, the cables may lose their pre-stress while the bars may buckle, get damaged, or corrode, affecting the structural stiffness leading to change in the measured dynamic properties. Upon loading, a tensegrity structure may change its form through altering its member pre-stress affecting its global stiffness, even in the absence of damage. This can potentially mask the effect of damage leading to a false impression of tensegrity health. This poses the major challenge in tensegrity health monitoring especially when the load is stochastic and unknown. Present study proposes an output-only time-domain method that makes use of tensegrity vibrational responses within a Bayesian filtering-based approach to monitor the tensegrity health in the presence of uncertainties due to ambient force, model inaccuracy, and measurement noise. For this, an interacting strategy combining Particle Filter (PF) and Ensemble Kalman Filter (EnKF) has been adopted (Interacting particle-Ensemble Kalman Filter, IP-EnKF) in which the EnKF estimates the response states as ensembles while running within a PF envelop that estimates a set of location-based health parameters as particles. Furthermore, for a cheaper damage detection procedure, strain responses are used as measurements. The efficiency of the proposed methodology in terms of accuracy, computational cost, and robustness against noise contamination has been demonstrated using numerical experiments performed on two tensegrity modules: a simplex tensegrity and an extended-octahedron tensegrity.

Résumé : Abstract : Resumen : Tensegrity is a network of bars and cables that maintains its structural integrity with tension present in its cables. Other than typical structural failure mechanisms, tensegrity may fail due to slacking of cables or buckling of bars. Reallife tensegrities are an assemblage of component modules. Large tensegrities require excessive computation for model-based structural health monitoring (SHM), which may sometimes make the problem ill-posed. Instead of the entire domain, only a substructure can be investigated explicitly. Substructures decouple the structure into independent components that can be monitored individually, provided the sub-domain interface is measured. Yet the integration of substructures within predictor-corrector model-based SHM algorithms needs special investigation from consistency, stability, and accuracy perspectives. To consider system uncertainties Bayesian filtering-based SHM approaches have been employed in this study. The need for interface measurement has been circumvented through an output injection approach. To increase computational efficiency, the domain decomposition approach is coupled with an interacting filtering-based approach that employs Ensemble Kalman filter (for state estimation) within an envelope of Particle filter (for health parameter estimation). This facilitates simultaneous estimation of state and parameters while enabling full parallelization capability. The proposed approach is tested on a six-stage tensegrity tower made of component simplex modules.

Résumé : Abstract : Resumen : Energy moderation of the road transportation sector is required to limit climate change and to preserve resources. This work is focused on the moderation of vehicle consumption by optimizing the speed policy along an itinerary while taking into account vehicle dynamics, driver visibility and the road's longitudinal profile. First, a criterion is proposed in order to detect speed policies that are impeding drivers' eco-driving ability. Then, an energy evaluation is carried out and an optimization is proposed. A numerical application is performed on a speed limiting point with 20 usage cases and 5 longitudinal slope values. In the hypothesis of a longitudinal slope of zero, energy savings of 27.7 liter per day could be realized by a speed sign displacement of only 153.6 m. Potential energy savings can increase to up to 308.4 L per day for a −4% slope case, or up to 70.5 L per day for an ordinary −2% slope, with a sign displacement of only 391.5 m. This results in a total of 771,975 L of fuel savings over a 30 year infrastructure life cycle period. Therefore a methodology has been developed to help road managers optimize their speed policies with the aim of moderating vehicle consumption.

Résumé : Abstract : Resumen : Synchronization is a challenging problem for wireless nodes, especially for applications demanding good synchronization accuracy over wide areas. In that case, the GPS is a valuable solution as the nodes can independently synchronize to UTC. However, the energy consumption of a GPS receiver (over 100 mW when switched on) is not sustainable on a wireless node. Therefore, in this work, we developed a synchronization scheme based on periodic extinctions of the GPS receiver. The goal is to study the GPS power switching effect on the synchronization accuracy.To do so, a node with dedicated timestamping hardware was designed. Two clock models were compared to predict the node time when the GPS is off and the impact of a Kalman filter, to remove the GPS noise, was evaluated. From experimental data, we show that the choice of the clock model depends on the accuracy needed and that the Kalman filter improves the estimation of the clock frequency for both models. In our design, the GPS can be off from 60% up to 95% of the time for mean synchronization errors of 20 ns to 420 ns, respectively. This work demonstrates that GPS power switching is an efficient solution to reduce energy costs while maintaining a high synchronization accuracy.

Résumé : Abstract : Resumen : This paper studies set-membership estimation for discrete linear time-varying systems subject to unknown disturbance and noise, which are bounded by ellipsoids. To improve the existing ellipsoid-based set-membership estimation methods, we propose a new set representation tool, called ellipsoid bundle, which combines the advantages of ellipsoids and zonotopes for uncertainty set representation and computation. Then, ellipsoidal bundles are used to design a new set-membership estimation method.

Résumé : Abstract : Resumen : Since the discovery of electricity, electric cables have become ubiquitous in human constructions, from machines to buildings. Insulators play a crucial role in ensuring the proper functioning of these cables, so it is important to monitor their possible damage, which can be caused by environmental contamination, severe temperature variations, and electrical and mechanical stress. While shunt conductance is a direct health indicator of cable insulation, measuring the cable average shunt conductance is not sufficient for the detection of localized insulator damage, since localized conductance variations are diluted over a long cable length in such measurements. The objective of this paper is to assess the feasibility of reflectometry techniques for the monitoring of insulator damage in electric cables. To this end, the estimation of localized conductance variations is investigated based on electrical measurements made at one end of a cable. To avoid estimating a large number of discretized conductance values along a long cable, the proposed method relies on sparse regression, which automatically focuses on localized conductance variations at unknown positions caused by accidental insulator damage. In order to efficiently apply sparse regression techniques, the telegrapher's equations describing electric wave propagation in cables are transformed through several steps into a simple linear regression form. Then, Lasso (Least Absolute Shrinkage and Selection Operator) regression is applied to process the voltage and current data collected at a single end of the monitored cable. Numerical simulations show the potential of this method for fast estimation of localized shunt conductance variations.

Résumé : Abstract : Resumen : Flutter is one of the most important aeroelastic instability phenomena that arises from the interaction between the structural dynamics of the mechanical airfoil system and the surrounding airflow. This instability phenomenon can lead not only to a reduction in aircraft performance but also to catastrophic structural failure. Therefore, one of the major challenges is to perform parametric and sensitivity studies on the stability behavior of a wing system subject to many random uncertainties in order to achieve a thorough understanding and reliable estimation of the role played by each parameter in the flutter phenomenon. To carry out such a study, an advanced surrogate modeling technique based on kriging and polynomial chaos expansion (PCE) is proposed for the prediction of flutter instability. In addition, a methodology based on hybrid surrogate modeling with advanced automatic kriging construction is discussed to promote an efficient parametric study of the airfoil system with uncertainties subjected to flutter. The Sobol indices highlight that the role played by each random parameter depends strongly on the flow speed and airfoil geometry with complex behaviors, giving valuable insights into the physics and the complexity of flutter.

Résumé : Abstract : Resumen : Computer vision-based vibration measurement methods are contactless and offer advantages over traditional sensor measurements like accelerometers that have to be installed on the investigated structure. In particular, measurements with a high spatial resolution are obtained at relatively low cost. When processing such measurements for modal analysis with system identification methods, the high dimensional data corresponding to thousands of traditional sensors pose a challenge regarding the computational complexity and the memory requirements of the identification algorithm. In this paper, strategies for dimension reduction in subspace-based modal analysis are implemented and evaluated with regards to the obtained modal parameter uncertainties. In particular, the high spatial resolution of the mode shapes is preserved, while computation time and memory requirements are drastically reduced. The proposed method is applied to numerical and experimental data of a beam.

Résumé : Abstract : Resumen : Rail breaks can be a source of dramatic accidents or service interruptions with huge economic and social impacts. Conventional inspection of rails is generally performed through manual inspection devices or inspection vehicles equipped with ultrasonic or electromagnetic sensors able to check surface and internal defects along the rail in either contact or noncontact manner. Guided elastic waves are one of the most promising technology for Structural Health Monitoring of elongated structures thanks to their capability to propagate over large distances and their sensitivity to critical defects such as cracks or corrosion. Piezoelectric transducers that are permanently and regularly spaced on the rail can be used to emit and receive such waves. Specific signal processing of the measured signals can detect, locate and characterize a rail damage before it reaches critical size. This type of system is able to send real time alert for safety issue and anticipate maintenance operations minimizing thus service interruptions. We present here the recent development, in a collaboration between CEA, UGE (formerly IFSTTAR) and Alstom, of guided waves based rail-monitoring system composed of permanent piezoelectric transducers placed every kilometers on the rail and driven by electronic nodes. This system relies on the generic PEGASE motherboard developed by UGE and its GPS-based time synchronization solution that ensures that distant electronic nodes share a common clock with an accuracy below tenths of nanoseconds, sufficient to capture guided waves phenomena. A specific daughter board able to drive up to 8 ultrasonic transducers in the frequency range of 10 – 200 kHz has been specifically designed for the node. It includes an FPGA that ensures low-level signal processing of measurements. The local diagnosis of each node are then transmitted to a remote server (using wireless protocols such as WiFi or 3G/4G depending on the application) that aggregates the information coming from the different nodes and send an alarm in case of rail damage detection. The presentation will describe the global SHM system (ultrasonic node and remote server operation) developed for rail monitoring and on-field applications of the solution.

Résumé : Abstract : Resumen : La détection de défaut par analyse modale est un domaine très développé dans le génie civil. Malgré la rotation des pales, il est possible de l'appliquer et de développer des approches similaires pour les éoliennes en utilisant une modélisation des modes propres en base de Fourier. Une perte d'isotropie du rotor peut être la conséquence d'un défaut d'angle d'attaque (pitch) des pales, de l'accumulation de glace ou bien de la présence de défauts structurels entraînant une perte de raideur sur une ou plusieurs pales. La surveillance de ce phénomène à partir des déformées des modes estimés est validée avec un exemple où une baisse globale de raideur de 5% d'une pale du rotor est simulée.

Résumé : Abstract : Resumen : Accurate building performance assessment is necessary for the design of efficient energy retrofit operations and to foster the development of energy performance contracts. An important barrier however is that simulation tools fail to accurately predict the actual energy consumption. We present a methodology combining thermal sensor output and inverse algorithms to determine the key parameters of a multizone thermal model. The method yields calibrated thermal models that are among the most detailed ones in the literature dealing with building thermal identification. We evaluate the accuracy of the resulting thermal model through the computation of the energy consumption and the reconstruction of the main energy flux. Our method enables one to reduce standard uncertainties in the thermal state and in the quantities of interest by more than 1 order of magnitude.

Résumé : Abstract : Resumen : Dynamic system fault diagnosis is often faced with a large number of possible faults. The purpose of this paper is to propose an efficient method for such situations. To avoid intractable combinatorial problems, sparse estimation techniques appear to be a powerful tool for isolating faults, under the assumption that only a small number of possible faults can be simultaneously active. However, sparse estimation is often studied in the framework of linear algebraic equations, whereas model-based fault diagnosis is usually investigated for dynamic systems modeled with state equations involving internal states. The main contribution of this paper is a link between these two formalisms through efficient and reliable algorithms, mainly relying on advanced analyses of residuals generated with the Kalman and Kitanidis filters. Based on these results, it becomes straightforward to solve fault diagnosis problems by applying well known sparse estimation techniques, in the framework of general time varying state-space systems involving unknown inputs.

Résumé : Abstract : Resumen : The Éric Tabarly bridge in Nantes is a 210m long cable-stayed road bridge crossing the Loire River, that was inaugurated in 2011. It is composed of a 27 m wide steel deck divided into two spans by a 57 m high steel pylon, being the main span 143m long. In the context of the European Research Project DESDEMONA (DEtection of Steel DEfects by Enhanced MONitoring and Automated procedure for self-inspection and maintenance), the bridge has been equipped with a dynamic monitoring system, constituted of 16 uniaxial accelerometers installed both on the deck and on the Pylon, with accelerations being recorded with a sampling rate of 100 Hz. This paper describes the dynamic monitoring system installed in the bridge and the results achieved during the first months of operation, including the characterization of vibration levels (maximum and effective values) as well as the automatic identification of the bridge modal properties. Finally, the effects of operational and environmental conditions on modal properties are studied.

Résumé : Abstract : Resumen : Distributed Optical Fiber Sensors (DOFS) are gaining interest for structural health monitoring applications. Recently, they have been successfully used to monitor the strain profiles at the interface between concrete and steel or composite rebars during pullout tests. In the framework of durability studies on Glass Fiber-Reinforced Polymer reinforcing bars (rebars), this method offers interesting perspectives for monitoring the evolution of the concrete/rebar bond behavior under accelerated ageing conditions. However, the durability of the bonded DOFS instrumentation itself should be investigated in a preliminary stage, to assess possible alteration of its performance over aging, which would raise questions about the validity of strain measurements in the long term. This article presents the first results of an experimental program aiming to address this specific issue. In this work, steel rebars were equipped with bonded optical fibers. Half-length of the instrumented rebars was subjected to hydrothermal ageing by immersion in an alkaline solution, while the remaining length was exposed to standard laboratory conditions. After exposure, the rebars were tested in tension and the DOFS strain profiles were simultaneously measured. These strain profiles were then compared to reference measurements performed before ageing, providing insights on the influence of the ageing conditions on the response of the DOFS.

Résumé : Abstract : Resumen : Overloaded road vehicles induce road unsafety, deterioration of infrastructure and unfair competition in freight transport. The European Directive 96/53 (revised 2015/719) regulates commercial vehicle weights and dimensions for international traffic and requires Member States to carry out checks and report on them. Weigh-in-motion (WIM) systems currently detect overloaded vehicles to screen them prior enforcing them on approved static scales. The work carried out since 2015 in France paves the way for direct enforcement of overloads by WIM, which would make it possible to enforce 200 times more of overloaded vehicles, with less staff and resources. This will ensure a better compliance, and ensure a greener and fairer transport market, and increased road asset durability and road safety. The French Ministry of Transport is in charge of the deployment of direct enforcement, in partnership with the Ministry of the Interior for legal issues, and with the Legal Metrology (Ministry of Economy) and its National Metrology and Testing Laboratory (LNE) for certification. The Université Gustave Eiffel and the Cerema carried out research and development works and tests, on open road and on a closed test site, to prove the feasibility of direct enforcement by WIM and prepare a type-approval procedure. The work has focused on assessing the accuracy and reliability of marketed WIM systems. The paper summarizes the main results obtained both with reference and instrumented vehicles and with vehicles from the traffic flow. The aim is to get a right balance between almost no false positive, which would lead to wrong fining, and the lowest tolerance on overloads. The impact of the heavy vehicle dynamics on weighing was assessed, by testing with an instrumented truck, to confirm physical modelling and check that the certification in the required accuracy classes could be achievable.. Extensive tests have been carried out over more than 4 years on the motorway A4 (operated by SANEF) in eastern France. Static weighs were used as references to assess the accuracy of WIM systems. WIM manufacturers providing systems based on piezoquartz sensors by Kistler were pre-qualified, with respect to the accepted tolerances and levels of confidence. A certification procedure including type-approval, initial and in-service verification, has been developed, based on the OIML recommendation R-134, with a few proposed and justified derogations. A test site, Transpolis near Lyon, was pre-qualified for the typeapproval tests. The results show that marketed WIM systems meet the OIML class 10, for fully loaded or overloaded trucks, and the class 5 is achievable for the heaviest trucks. The class 10 is also achievable for the gross weights of the light commercial vehicles (LCVs, below 3.5 t). The certification procedure is now being approved by the LNE.

Résumé : Abstract : Resumen : Heavy commercial vehicle overloads contribute to deterioration of infrastructure and increase road unsafety and unfair competition between transport modes and operators. An efficient enforcement system of weights and dimensions at an affordable cost is therefore required. A large scale project was launched by the French Ministry of Transport in 2014 in France, led by IFSTTAR, in cooperation with the Cerema, to demonstrate the feasibility of using high speed weigh-in-motion (HS-WIM) systems for direct enforcement of overloads. This ambitious challenge requires overcoming technological and metrological gaps, and modifying the current legislation. The required tolerances are ±5% for the gross vehicle weight, and ±10% for axle loads for 100% of the vehicles. The methodology is to develop sorting criteria and algorithms, eliminating the outliers, that is to say the weighing data outside these tolerances. The project organization and management is described and the first results are presented in this paper.

Résumé : Abstract : Resumen : L’Ifsttar mène des recherches avec le Réseau Scientifique et Technique du Ministère français des Transports pour favoriser l’émergence de solutions innovantes exploitant les caméras pour évaluer et améliorer la visibilité routière. Cet article passe en revue les méthodes de vision par ordinateur qui ont été développées dans le cadre de ce travail. Les trois principaux domaines d’application de ces outils sont couverts : les aides à la conduite, la régulation du trafic et l’inspection de la route. La validation des outils est également abordée.

Résumé : Abstract : Resumen : The number of floating production, storage and offloading units (FPSO) around the globe is in continuous increase and a relatively high number of them are now almost 20 years aged. The general geographical layout, being in tropical area makes the corrosion a fundamental ageing problem of the steel structures in structural area, like decks or side shell but also inner structure. Therefore, there is a strong need for proposing repair solutions having low impact on their exploitation. Such repair solutions (“cold repair” in contrast with “hot works”), like adhesively bonded FRP (Fiber Reinforced Polymer) requires additional development, in particular in the preliminary characterization and design step, and regarding the durability issues. Use of composite to build onsite repair seems adequate to solve this issue as they require limited heat (80°C) and can easily be installed on various shape, position and surfaces. However, the lack of application cases and design method lead to limited references on the best way to install composite patch repair. By design, the stress concentration at the border of the patch tends to decrease the overall strength and failure load that adhesives can sustain. Therefore, patch geometry must be addressed with care to obtain high performance patches. The overall capacity of the patch is highly related to the energy that can withstand the bonded interface with the steel adherent, and so, a particular attention to the surface preparation must be taken. Finally, the patch layup controls the overall stiffness and strains in the patch, which must lead to a particular design to obtain the required properties. This paper presents the design methodology, the surface preparation protocol study and the manufacturing protocol of a composite patch developed during the Joint Industrial Project Strength Bond Offshore. The results of the static and fatigue test campaign in tension and bending are also presented. The assessment of the overall capacities of the composite patch repair are compared to a simpler bonded steel repair. The use of distributed strain measurement optical fiber as the new patch monitoring technique applied to composite patch are developed and highlighted.

Résumé : Abstract : Resumen : A method to determine the influencing parameters of a structural and Damage Detection System (DDS) is proposed based on the Value of Information (VoI) analysis. The VoI analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of DDS for the structural integrity management during service life. First the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the DDS performance, including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes' theorem to update the prior system model with the damage indication information. Finally, the value of DDS is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative VoI over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative VoI; only specific sensor locations near the highest utilized components lead to a high relative VoI; measurement noise and the Type I error should be controlled and be as small as possible. An optimal sensor employment with highest relative VoI is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies-before implementation-for similar bridges and to optimize the DDS settings and sensor configuration for minimum expected costs and risks.

Résumé : Abstract : Resumen : In the field of civil engineering, Ground Penetrating Radar (GPR) is the most widely used method of Non-Destructive Testing (NDT). Using supervised learning methods or signal processing methods, it is possible to analyze the sub-surface defects in pavement. In this paper, we propose to use a machine learning method called Support Vector Machines (SVM) to detect the presence of debondings within the pavement. Here, the ground-coupled GPR in quasi mono-static configuration along with SVM is used to detect debondings. The experiments are done on bituminous concrete pavements with various material characteristics. The classification results are good and show the efficiency of the detection process.

Résumé : Abstract : Resumen : This work deals with the detection of non-emergent small structures like mosaic, hidden under a plaster layer, with various spatial layout and nature. A first feasibility study using a unique sample for one type of defective patchworks was presented in [1]. In this previous study analysis was mainly focused on thermal contrast [2]. In the present study, square pulse thermography experiments were carried out, in laboratory conditions, on different samples. Figure 1 show a view of the hidden structures and the laboratory set up. Figure 1 View of some samples and of experimental set up in laboratory At the final 9 different samples were studied. For 8 configurations thermal numerical simulations were also realized under FLUENT™. They were used to generate simulated infrared thermal sequences. Three post processing approach [3-5] by PPT, SVD and Polynomial analysis were conducted on this experimental and simulated data set. Results obtained are analyzed and discussed. Finally, influence of IR camera used will be also addressed and discussed in the dissertation.

Résumé : Abstract : Resumen : Evaluation of bridge deck waterproofing membrane is essential to assess the durability of the whole structure from the surface (pavement) to the subsurface (bridge structure). Maintenance, rehabilitation and redesign strategies require road surface information for decisive actions by profound analysis. The objective of this project is to develop an innovative 3D electromagnetic mapping showing accurately water leakage in concrete layers of the bridge deck. Non-Destructive Testing (NDT) can detect critical damages that cannot be detected using visual inspection. In this scope, due to their sensitivity to water content, Electromagnetic waves, especially Ground Penetrating Radar (GPR) may provide a strong means to evaluate the safety and reliability of a bridge. The aim of the present work is to detect and characterize water leakage in a concrete bridge deck using detailed analysis of the radar signal from a Stepped-frequency Radar (SFR). We use an approach based on the coupling between the Full-Waveform Inversion (FWI) and a supervised learning method applied in local and global approaches to C-scans, obtained at first from SFR output data modelling.

Résumé : Abstract : Resumen : The enlargement of the cracks outside the permitted dimension is one of the main causes for the reduction of service life of Reinforced Concrete (RC) structures. Cracks can develop due to many causes such as dynamic or static load. When tensile stress exceeds the tensile strength of RC, cracks appear. Traditional techniques have limitations in early stage damage detection and localisation, especially on large-scale structures. The ultrasonic Coda Wave Interferometry (CWI) method using diffuse waves is one of the most promising methods to detect subtle changes in heterogeneous materials, such as concrete. In this paper, the assessment of the CWI method applied for multiple cracks opening detection on two specimens based on four-point bending test is presented. Both beams were monitored using a limited number of embedded Ultrasonic (US) transducers as well as other transducers and techniques (e.g., Digital Image Correlation (DIC), LVDT sensors, strain gauges, and Fiber Optics Sensor (FOS)). Results show that strain change and crack formation are successfully and efficiently detected by CWI method even earlier than by the other techniques. The CWI technique using embedded US transducers is undoubtedly a feasible, efficient, and promising method for long-term monitoring on real infrastructure.

Résumé : Abstract : Resumen : Following the significant improvement in their properties during the last decade, Distributed Fiber Optics sensing (DFOs) techniques are nowadays implemented for industrial use in the context of Structural Health Monitoring (SHM). While these techniques have formed an undeniable asset for the health monitoring of concrete structures, their performance should be validated for novel structural materials including Ultra High Performance Fiber Reinforced Cementitious composites (UHPFRC). In this study, a full scale UHPFRC beam was instrumented with DFOs, Digital Image Correlation (DIC) and extensometers. The performances of these three measurement techniques in terms of strain measurement as well as crack detection and localization are compared. A method for the measurement of opening and closing of localized fictitious cracks in UHPFRC using the Optical Backscattering Reflectometry (OBR) technique is verified. Moreover, the use of correct combination of DFO sensors allows precise detection of microcracks as well as monitoring of fictitious cracks' opening. The recommendations regarding use of various SHM methods for UHPFRC structures are given.

Résumé : Abstract : Resumen : Structural health monitoring is a promising technology to automatically detect structural changes based on permanently installed sensors. Vibration-based methods that evaluate the global system response to ambient excitation are suited to diagnose changes in boundary conditions, i.e., changes in member prestress or imposed displacements. In this paper, these changes are evaluated based on sensitivity-based statistical tests, which are capable of detecting and localizing parametric structural changes. The main contribution is the analytical calculation of sensitivity vectors for changes in boundary conditions (i.e., changes in prestress or support conditions) based on stress stiffening, and the combination with a numerically efficient algorithm, i.e., Nelson's method. One of the main advantages of the employed damage diagnosis algorithm is that, although it uses physical models for damage detection, it considers the uncertainty in the data-driven features, which enables a reliabilitybased approach to determine the probability of detection. Moreover, the algorithm can be trained and the probability of detecting future damages can be predicted based on data and a model from the undamaged structure, in an unsupervised learning mode, making it particularly relevant for unique structures, where no data from the damaged state is available. For proof of concept, a numerical case study is presented. The study assesses the loss of prestress in a two-span reinforced concrete beam and showcases suitable validation approaches for the sensitivity calculation.

Résumé : Abstract : Resumen : Electrical resistivity is sensitive to various properties of concrete, such as water content. Usually used on the surface of old structures, devices for measuring such properties could also be adapted in order to be embedded inside the constitutive concrete of the linings of new tunnels or in new bridges, to contribute to structural health monitoring. This paper introduces a novel multi-electrode embedded sensor for monitoring the resistivity profile over depth in order to quantify concrete durability. The paper focuses on the design of the sensor as a printed circuit board (PCB), which brings several advantages, including geometric accuracy and mitigation of wiring issues, thus reducing invasiveness. The study also presents the numerical modeling of the sensor electrical response and its ability to assess an imposed resistivity profile, together with experimental validations using (i) saline solutions of known conductivity and (ii) concrete specimens subjected to drying. The results demonstrate the capability of the sensor to evaluate resistivity profiles in concrete with centimeter resolution.

Résumé : Abstract : Resumen : Permanent monitoring of the structural behavior of civil infrastructures require robust and reliable data acquisition systems. In this study, we present the dynamic monitoring of the Éric Tarbarly bridge in Nantes, France and its related acquisition system. This system enables to follow the temporal evolution of the modal parameters of the structure by storing accelerometers data, external environmental data and the associated metadata thanks to the HDF5 file format.

Résumé : Abstract : Resumen : The French national radioactive waste management agency (Andra) aims to insure the durability of thick concrete structures used for waste repository. To this end, concrete water content is one of the main parameters governing the long-term durability of these structures, therefore an accurate estimation of its profile is important. This research focuses on an electrical resistivity technique, which is highly sensitive to the water content in concrete. Our work aims to design a prototype of embedded sensors in concrete structures to measure the resistivity profile with depth and the water content profile after calibration. The study highlights the capability of different types of sensors to measure the resistivity profile of a 30cm-thick concrete section. Several numerical studies are conducted to design different possible configurations of the embedded sensors and to optimize the sensors geometry in order to obtain the most relevant configuration. Several types of sensors are tested on small specimens; for instance Wenner type (aligned and equidistant four-pin probe resistivity method), proved capable of identifying the resistivity profile. The methodology for observing, measuring and monitoring the resistivity profile over time is studied.

Résumé : Abstract : Resumen : In this study, square pulse thermography is used to detect and characterize defects in carbon/epoxy composite plates. Defects are polymeric disks inserted between plies at different depths in the samples. A practical experimental set-up is developed: temperature measurements are only required on the front face of the samples and the heating source consists in using standard halogen lamps. A transient thermal modeling based on thermal quadrupoles and several adimensional parameters provides a one- dimensional analytical solution. Singular value decomposition analysis is used to differentiate sound and defect areas. An inversion procedure is carried out to estimate unknown parameters without any prior knowledge on sample properties or defect locations. Especially it is possible to estimate both depth and thermal resistance of the defect with reduced uncertainties. Results on the influence of the analysis and heating durations are presented. A comparison of the thermal contact quality relative to the different defects is finally performed.

Résumé : Abstract : Resumen : Ground Penetrating Radar (GPR) is a Non-destructive Testing (NDT) method used to investigate subsurface conditions of civil engineering structures and locate buried objects using wideband electromagnetic (EM) pulse. The adoption of GPR to locate utilities has increased due to its ability to detect both metallic and non-metallic pipes. Further, the technology facilitates localization of the buried pipes with the support of signal processing steps and GPS coordinates. In this process, the presence of a pipe yields hyperbolae signatures on the B-scan. Thus, identification and localization of such hyperbolae is a vital step in the GPR signal processing towards 3D localization. For smaller GPR data sets, the human interpretation is sufficient to identify hyperbolae. However, in large-scale utility survey, precise and fast hyperbolae detection is required to accelerate the processing time and minimize human resource and costs. From the literature, several studies have been conducted previously to develop automatic hyperbola detection models based on physical methods and machine learning techniques. The performance of the models varied depending on the signal preprocessing, annotation strategy and machine learning algorithms. The common drawback of these existing models were higher false positives as any hyperbola formed by multiple reflection or other effects were also detected as true positives. Therefore, considering all pending challenges and advancement of deep learning techniques, we have proposed Faster Region-based Convolutional Neural Network (Faster R-CNN) automatic hyperbola detection models using two annotation strategies. The model has been numerically validated using 2D gprMax based on FDTD model, followed by validation on field data.

Résumé : Abstract : Resumen : In civil engineering, ground penetrating radar (GPR) is used to survey pavement thickness at traffic speed, detect and localize buried objects (pipes, cables, voids, cavities), zones of cracks and discontinuities in concrete or soils. In this work, a ground-coupled radar made of a pair of transmitting and receiving bowtie-slot antennas is moved linearly on the soil surface to detect the reflected waves induced by discontinuities in the subsurface. The GPR system operates in the frequency domain using a step-frequency continuous wave (SFCW) using a Vector Network Analyzer (VNA) in an ultra-wide band [0.3 ; 4] GHz. The detection of targets is usually focused on time imaging. Thus, the targets (limited in size) are usually shown by diffraction hyperbolas on a Bscan image that is an unfocused depiction of the scatterers. The contrast in permittivity and the ratio between the size of the object and the wavelength are important parameters in the detection process. Thus, we have made a first study on the use of polarization diversity to obtain additional information relative to the contrast between the soil and the target and the dielectric characteristics of a target. The two main polarizations configurations of the radar have been considered in the presence of objects having a pipe geometry: the TM (Transverse Magnetic) and TE (Transverse Electric. To interpret the diffraction hyperbolas on a Bscan image, we have used pre-processing techniques are necessary to reduce the clutter signal which can overlap and obscure the target responses, particularly shallow objects. The clutter, which can be composed of the direct coupling between the antennas and the reflected wave from the soil surface, the scattering on the heterogeneities due to the granular nature of the subsurface material, and some additive noise, varies with soil dielectric characteristics and/or surface roughness and leads to uncertainty in the measurements (additive noise). Because of the statistical nature of the clutter, we have considered and quantified the performance of the Principal Component Analysis (PCA) and the Independent Component Analysis (ICA) in remove or minimizing the clutter using the receiver operating characteristics (ROC) graph. The study has been focused in the preferred polarization on simulated and experimental scenarios of soil structures with a few parameters such as the presence of a different target depths which are capable to perturb the first arrival times made of clutter components, and different dielectric characteristics (conductive or dielectric) of a given target (pipe).

Résumé : Abstract : Resumen : In this paper the statistical subspace damage localization (SSDL) method is employed in localizing the damage in a real structure, namely the Yellow frame. The SSDL method is developed for real testing conditions and tested in two damage configurations. It was demonstrated that the SSDL method can localize the damage robustly in the Yellow frame for simple and multiple distinct damage scenarios using the analytical modal parameters. The method is described and its effectiveness is demonstrated.

Résumé : Abstract : Resumen : Tensegrities are structural mechanisms, with dedicated compression (struts/bars) and tension members (cables). The compression members float inside the network of tension members. Tensegrities are characterized by the presence of at least one infinitesimal mechanism, which is stabilized by the pre-stress present in the members, to ensure the equilibrium of the structure. Under external load, tensegrity may change its form by altering its member pre-stress, thereby affecting its global stiffness even in the absence of damage. Moreover, tensegrities can have different stiffness properties under the same structural configuration in the absence of any damage or external load, if the pre-stress levels of the members are different. However, the changes in dynamic characteristics of tensegrities are not limited to the aforementioned causes only and is also affected by ambient uncertainties. A variation in temperature may alter the dynamic characteristics of a tensegrity by influencing its material (Young's modulus, etc.) and structural (boundary conditions, structural dimensions, etc.) properties. This can potentially lead to a false impression of tensegrity damage/health. Meanwhile, the prolonged usage of tensegrity may lead to loss of pre-stress in the cables, buckling of the bars, corrosion, and damage of the members, etc. Thus affecting the structural stiffness which leads to change in the measured dynamic properties of the tensegrity. To account for this actual damage in the tensegrity, all the mentioned major challenges that could lead to a false alarm need to be dealt with. The present study develops a vibration-based time-domain approach for tensegrity health monitoring in the presence of uncertainties due to ambient force, measurement noise, and varying temperature. An interacting filtering technique has been used, where the state variables are estimated by the Ensemble Kalman filter that resides inside the Particle filter which computes the health parameters.

Résumé : Abstract : Resumen : Damage detection and localization based on ultrasonic guided waves revealed to be promising for structural health monitoring and nondestructive testing. However, the use of a piezoelectric sensor’s network to locate and image damaged areas in composite structures requires a number of precautions including the consideration of anisotropy and baseline signals. The lack of information related to these two parameters drastically deteriorates the imaging performance of numerous signal processing methods. To avoid such deterioration, the present contribution proposes different methods to build baseline signals in different types of composites. Baseline signals are first constructed from a numerical simulation model using the previously determined elasticity tensor of the structure. Since the latter tensor is not always easy to obtain especially in the case of anisotropic materials, a second PZT network is used in order to obtain signals related to Lamb waves propagating in different directions. Waveforms are then translated according to a simplified theoretical propagation model of Lamb waves in homogeneous structures. The application of the different methods on transversely isotropic, unidirectional and quasi-transversely isotropic composites allows to have satisfactory images that well represent the damaged areas with the help of the delay-and-sum algorithm.

Résumé : Abstract : Resumen : Early signs of mechanical characteristic changes are essential for structural health monitoring (SHM). Due to the complexity of civil, mechanical or aeronautical structures, SHM is often faced with high dimensional mechanical characteristics together with limited sensor instrumentation. In this paper, Lasso regression is applied to address this complexity issue, based on its ability for solving large regression problems. The mechanical vibration model is first appropriately transformed into a linear regression model, with its parameters corresponding to small changes in the monitored mechanical characteristics, then these parameters are estimated from mechanical sensor signals under the assumption that most of the parameters are zeros. The performance of the proposed method is illustrated with a simulated truss structure.

Résumé : Abstract : Resumen : Tensegrity structures form a special class of truss with dedicated cables and bars, that take tension and compression, respectively. To ensure equilibrium, the tensegrity members are required to be prestressed. Over prolonged usage, the cables may lose their prestress while bars may buckle, affecting the structural stiffness as well as its dynamic properties. The stiffness of tensegrities also vary with the load even in the absence of damage. This can potentially mask the effect of damage leading to a false impression of tensegrity health. This poses a major challenge in tensegrity health monitoring especially when the load is stochastic and unknown. Present study develops a vibration based output-only time-domain approach for monitoring the health of any tensegrity in the presence of uncertainties due to ambient force and measurement noise. An Interacting Particle Ensemble Kalman Filter (IPEnKF) has been used that can efficiently monitor tensegrity health from contaminated response data. IPEnKF combines a bank of Ensemble Kalman Filters to estimate response states while running within a Particle Filter envelop that estimates a set of location based health parameters. Further to make damage detection cheaper, strain responses are used as measurements. The efficiency of the proposed methodology has been demonstrated using numerical experiments performed on a simplex tensegrity.

Résumé : Abstract : Resumen : This paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its function-ality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt truss system, the value of damage detection information is determined , demonstrating the potential of risk reduction and expected cost reduction.

Résumé : Abstract : Resumen : DIARITsup is a chain of various softwares following the concept of "system of systems". It interconnects hardware and software layers dedicated to in-situ monitoring of structures or critical components. It embeds data assimilation capabilities combined with specific Physical or Statistical models like inverse thermal and/or mechanical ones up to the predictive ones. It aims at extracting and providing key parameters of interest for decision making tools. Its framework natively integrates data collection from local sources but also from external systems. DIARITsup is a milestone in our roadmap for SHM Digital Twins research framework. Furthermore, it intends providing some useful information for maintenance operations not only for surveyed targets but also for deployed sensors. Thanks to its Model-view-controller (MVC) design pattern, DIARITsup can be extended, customized and connected to existing applications. Its core component is made of a supervisor task that handles the gathering of data from local sensors and external sources like the open source meteorological data (observations and forecasts) from Météo-France Geoservice for instance. Meanwhile, a recorder manage the recording of all data and metadata in the Hierarchical Data Format (HDF5). HDF5 is used to its full potential with its Single-Writer-Multiple-Readers feature that enables a graphical user interface to represent the saved data in real-time, or the live computation of SHM Digital Twins models [3] for example. Furthermore, the flexibility of HDF5 data storage allows the recording of various type of sensors such as punctual sensors or full field ones. Finally, DIARITsup is able to handle massive deployment thanks to Ansible automation tool and a Gitlab synchronization for automatic updates. An overview of the developed software with a real application case will be presented. Perspectives towards improvements on the software with more component integrations (Copernicus Climate Data Store, etc.) and a more generic way to configure the acquisition and model configuration will be finally discussed.

Résumé : Abstract : Resumen : The vibration-based Structural Health Monitoring plays a central role in ensuring the safe operation of infrastructures by monitoring their structural integrity based on data collected by sensors. While damage detection has reached maturity, the localization and the quantification of small-scale damage remain an open challenge. To address it, both the localization and the quantification of damage are often posed as an updating problem of a Finite Element Model (FEM) of the operating structure, minimizing the misfit between some features computed from response measurements of a faulty structure and its FEM in a reference, healthy condition. This paper investigates the choice of the features for the design of the objective function to quantify structural cracks. For this purpose, a FEM of a beam with a transverse crack is developed and parametrized by the second moment of area of the elements to locate and quantify the crack-related damage. Subsequently, the impact on the choice of the objective function is discussed based on a small-samples Monte Carlo study.

Résumé : Abstract : Resumen : Heat transport characterisation inside rotary drum dryer has a considerable importance linked to the many industrial applications. The present paper deals with the heat transfer analysis from experimental apparatus installed in a large-scale rotary drum reactor applied to the asphalt materials production. The equipment including in-situ thermal probes and external visualization by mean infrared thermography gives rise to the longitudinal evaluation of inner and external temperatures. The assessment of the heat transfer coefficients by an inverse methodology is resolved in order to accomplish a fin analysis of the convective mechanism inside baffled (or flights) rotary drum. The results are discussed and compared with major results of the literature.

Résumé : Abstract : Resumen : We introduce a computational framework for controlling the location of isolated response curves, i.e. responses that are not connected to the main solution branch and form a closed curve in parameter space. The methodology relies on bifurcation tracking to follow the evolution of fold bifurcations in a codimension-2 parameter space. Singularity theory is used to distinguish points of isola formation and merger from codimension-2 bifurcations and an optimization problem is formulated to delay or advance the onset or merger of isolated response curves or control their position in the state/parameter space. We illustrate the methodology on three examples: a finite element model of a cantilever beam with cubic nonlinearity at its tip, a two-degree-of-freedom oscillator with asymmetry and a two-degree-of-freedom base-excited oscillator exhibiting multiple isolas. Our results show that the location of points of isola formation and mergers can effectively be controlled through structural optimization.

Résumé : Abstract : Resumen : In this paper, we study the strain transfer mechanism between a host material and an optical fiber. A new analytical model handling imperfect bonding between layers is proposed. A general expression of the crack-induced strain transfer from fractured concrete material to optical fiber is established in the case of a multilayer system. This new strain transfer model is examined through performing wedge splitting tests on concrete specimens instrumented with embedded and surface-mounted fiber optic cables. The experimental results showed the validity of the crack-induced strain expression fitted to the distributed strains measured using an Optical Backscattering Reflectometry (OBR) system. As a result, precise estimations of the crack openings next to the optical cable location were achieved, as well as the monitoring of the optical cable response through following the strain lag parameter.

Résumé : Abstract : Resumen : In the era of the information society, the impact of the information systems on the economy of material and immaterial is certainly perceptible. With regards to the information resources of an organization, the annotation involved to enrich informational content, to track the intellectual activities on a document and to set the added value on information for the benefit of solving a decision-making problem in the context of economic intelligence. Our contribution is distinguished by the representation of an annotation process and its inherent concepts to lead the decisionmaker to an anticipated decision: the provision of relevant and annotated information. Such information in the system is made easy by taking into account the diversity of resources and those that are well annotated so formally and informally by the EI actors. A capital research framework consist of integrating in the decision-making process the annotator activity, the software agent (or the reasoning mechanisms) and the information resources enhancement.

Résumé : Abstract : Resumen : The latest improvements in infrared detectors enable the use of infrared thermography in many applications for outdoor temperature measurements through a low cost and easy to maintain solution. However, converting the radiative fluxes received by the infrared camera to the object of interests' apparent surface temperature is a challenging task. It requires us to consider the global radiative heat balance at the sensor level. Such a correction implies taking into account the background contributions (sky, sun, other elements on the scene), the involved transmissions (camera optics, atmosphere, participating media of the scene), etc. As a consequence, supplementary data are needed to achieve quantitative outdoor thermal monitoring. In this study, we propose a comparison of gathering those data from different observation scales: a local weather station, existing sensor networks such as Meteorological Aerodrome Report (METAR) and open source online satellite data from the European Copernicus program. Finally, the feasibility, advantages and limitations of the proposed methods are discussed.

Résumé : Abstract : Resumen : The objectives of the study summarized hereafter are to compare square pulse and pulsed thermography for defect detection and characterization of CFRP plates used as structural reinforcement in Civil Engineering applications. Image processing and an inverse method coupled with thermal quadrupoles model are also studied.

Résumé : Abstract : Resumen : Transport infrastructures play a significant role in the economy of countries. However, in European countries, transport infrastructures aging (>40 years) and traffic increase require to develop in-situ efficient inspection and maintenance solutions. Monitoring of steel and composite structures are important issues for sustainability of existing and new infrastructure. Classical approach relies on large human activities eventually performed in unsafe conditions. To overcome the problem on site contactless global automated measurement methods are to be favoured. For apparent corrosion, visible imaging coupled with image processing allows to detect and characterize the extension of the defective area. Anyway, characterization of corrosion thickness and nature require complementary measurements. Among imaging techniques, knowing that corrosion acts as a insulating layer, active infrared thermography is a possible approach [1-2]. But here we will focus on the complementary approach based on THz-TDS imaging as investigated and tested for corrosion detection under painting with preliminary corrosion type classification [2]. In the present study, we first performed a measurement campaign on several steel samples at different corrosion stages. Typically, three stages were investigated: from non-corroded with paint coating, to pitting corrosion up to fully corroded sample surface. Data were gathered by means of the Z-Omega Fiber-Coupled Terahertz Time Domain (FICO) system working in a high-speed reflection mode and were processed by using a properly designed data processing chain recently proposed in [3] and involving a noise filtering procedure based on the Singular Value Decomposition (SVD) of the data matrix. Complementary post-processing approach for quick detection and characterization were added to these filtered data. The obtained results, which will be presented in detail at the conference, allowed us to state the imaging capabilities offered by the adopted instrumentation and obtain valuable information on the surveyed specimens, such as the corrosion thickness connection with apparent pseudo-intensity images. Finally, perspectives on coupling techniques will be introduced.

Résumé : Abstract : Resumen : In this paper, two Non Destructive Testing approaches by active infrared thermography mounted on a 6-axis robot are presented and studied. Data acquisition and thermal excitation is carried out dynamically over various CFRP specimens with increasing geometry complexity, from planar, to convex and concave shapes. An automated procedure is proposed to reconstruct thermal image sequences issued from the two scanning procedure studied: Line Scan and Flying Line procedures. Defective area detection is performed by image processing and an inverse technique based on thermal quadrupole method is used to map the depth of flaws. Results obtained are discussed and perspectives are addressed.

Résumé : Abstract : Resumen : In a costs reduction and comfort requirements context, the use of phase change materials (PCM) is a sustainable and economical answer. For transportation infrastructures and winter maintenance, they avoid ice occurrence or snow accumulation. Their characteristics, and more specifically, the solid to liquid phase transition temperature and enthalpy, are usually obtained through DSC. Raman spectroscopy can bring answers and information on their microstructures. The liquid to solid phase change was investigated on three PCM, a paraffin, formic acid and diluted formic acid. A comparison made on freezing temperature obtained through DSC, Raman spectroscopy associated with chemiometrics indicated a consistency between the methods. Raman spectroscopy coupled with multivariate data analysis allowed the identification of an additional specificity in the freezing process of the paraffin. All methods provided results consistent between each other, although some differences between literature and experimental freezing temperatures of the considered PCM were observed in all cases.

Résumé : Abstract : Resumen : In the field of civil engineering, Ground Penetrating Radar (GPR) is widely used to monitor structural integrity. With the help of Step-frequency Radar (SFR) for data acquisition and proper data processing algorithms, it is possible to detect small sub-surface defects within the pavement. In this paper, we discuss a conventional method based on the signal's amplitude, a supervised machine learning method (namely SVM) and a semi-supervised clustering based algorithm to detect said defects. The data are collected using an SFR at IFSTTAR's fatigue carousel where debondings are artificially introduced.

Résumé : Abstract : Resumen : Les techniques de contrôle optimal prédictif sont, de par leur formulation, les plus adaptées à une gestion intelligente et efficace des systèmes climatiques de l'habitat. Elles reposent sur l'utilisation d'un modèle numérique du système que l'on cherche à contrôler au travers d'une fonction de coût à minimiser. Leur principale diffculté de mise en oeuvre réside dans la nécessité de disposer d'un modèle suffisamment proche de la réalité, et d'avoir des méthodes de calcul e caces pour une implémentation temps-réel. Nos travaux présentent l'utilisation d'une méthode e cace de calcul de commande optimale basée sur l'utilisation d'un modèle thermique dynamique d'un cas test de deux pièces et d'un modèle adjoint associé. Nous montrons également comment cette approche permet de mener à des études de sensibilité, particulièrement utiles pour spécifier les problèmes d'identi cation paramétrique et d'instrumentation

Résumé : Abstract : Resumen : Fault detection and isolation in stochastic systems is typically model-based, meaning fault-indicating residuals are generated based on measurements and compared to equivalent mathematical system models. The residuals often exhibit Gaussian properties or can be transformed into a standard Gaussian framework by means of the asymptotic local approach. The e_ectiveness of the fault diagnosis depends on the model quality, but an increasing number of model parameters also leads to redundancies which, in turn, can distort the fault isolation. This occurs, for example, in structural engineering, where residuals are generated by comparing structural vibrations to the output of digital twins. This article proposes a framework to _nd the optimal parameter clusters for such problems. It explains how the optimal solution is a compromise, because with an increasing number of clusters, the fault isolation resolution increases, but the detectability in each cluster decreases, and the number of false alarms changes. To assess these factors during the clustering process, criteria for the minimum detectable change and the false-alarm susceptibility are introduced and evaluated in an optimization scheme.

Résumé : Abstract : Resumen : The bending behavior of foam core sandwich composites has increasingly attracted attention and application in industries such as shipbuilding, aircraft and wind turbine industries. The main objective of this research work is the assessment of shear strain in a foam core beam by means of optical fiber sensors during bending test. Experimental studies were conducted on a PVC foam beam in which three optical fibers were embedded in a longitudinal plane across the thickness of the foam core; straight optical fibers measure strains due to the tension/compression load, whereas the sinusoidal fibers catch strains due to the shear load. Finite element model (FEM) was used to predict strain levels in order to validate and explain optical fiber sensor measurements from 3-and 4-point bending tests. The concordance of the shear properties identified by optical-fiber sensor results and obtained by finite element simulation was evaluated to validate the new developed technique of characterization. Results shows good agreement between the experimental and numerical responses.

Résumé : Abstract : Resumen : The monitoring of mechanical systems aims at detecting damages at an early stage, in general by using output-only vibration measurements under ambient excitation. In this paper, a method is proposed for the detection and isolation of small changes in the physical parameters of a linear mechanical system. Based on a recent work where the multiplicative change detection problem is transformed to an additive one by means of perturbation analysis, changes in the eigenvalues and eigenvectors of the mechanical system are considered in the first step. In a second step, these changes are related to physical parameters of the mechanical system. Finally, another transformation further simplifies the detection and isolation problem into the framework of a linear regression subject to additive white Gaussian noises, leading to a numerically efficient solution of the considered problems. A numerical example of a simulated mechanical structure is reported for damage detection and localization.

Résumé : Abstract : Resumen : The prediction of a building's thermal behaviour within a short time horizon is necessary in many energy management applications. A numerical model can serve this purpose provided a good accuracy is obtained through a suitable calibration procedure. The paper deals with a model calibration procedure based on short-time on-site and weather measurements. It builds upon optimal control theory: an adjoint model is introduced to derive the gradient of a least squares cost function at a low computational cost. Two problems are solved. The first one is a non-linear model training problem. It consists in identifying the main influencing parameters of the system of partial differential equations that form the tendency model. The second problem is a linear identification problem that consists in identifying the unknown internal gains. This second problem can be solved in real-time in a continuous monitoring process. Both problems are solved within the same framework and same tools, illustrating the efficiency of the optimal control tools in this context. We give simulation results that show the performance of the calibration procedure under uncertainties on input parameters.

Résumé : Abstract : Resumen : For several years, Model Predictive Control (MPC) is depicted in the literature as a promising way to increase buildings' energy efficiency during operation. This model-based control technique uses the optimal control theory to provide a constraint compliant, anticipative control, maximizing performance criteria. However, building and calibrating a reliable model for a real application is difficult, costly and time-consuming. Indeed, it requires hard expert work to retrieve all the building's data and tune the corresponding model. This prevents MPC to be widespread in Building Management Systems. In this paper, we propose a MPC formulation where all the optimization problems included in a MPC strategy (calibration, estimation, optimal control) are performed efficiently using gradient-based techniques and adjoint-based gradient computations. This formulation relies on an automated "white-box" modeling technique (with partial-differential equations) using Building Information Model (BIM - using gbXML standard here) files parsing. We also show that making extensive use of adjoint models in MPC opens opportunities for fast sensitivity analysis, which can, for instance, help to choose which parameters to calibrate.

Résumé : Abstract : Resumen : The Kitanidis filter is a natural extension of the Kalman filter to systems subject to arbitrary unknown inputs or disturbances. Though the optimality of the Kitanidis filter was founded for general time varying systems more than 30 years ago, its boundedness and stability analysis is still limited to time invariant systems, up to the authors' knowledge. In the framework of general time varying systems, this paper establishes upper and lower bounds of the error covariance of the Kitanidis filter, as well as upper bounds of all the auxiliary variables involved in the filter. By preventing data overflow, upper bounds are crucial for all recursive algorithms in real time applications. The upper and lower bounds of the error covariance will also serve as the basis of the Kitanidis filter stability analysis, like in the case of time varying system Kalman filter.

Résumé : Abstract : Resumen : The boundedness of the Kalman filter, as the first cornerstone of its stability analysis, has been proved in the classical literature through upper bounds of non-recursive filters in the sense of the trace of the state estimation error covariance. In this paper, an upper bound of the Kalman filter prediction error covariance is established in the sense of matrix positive definiteness, based on a bounded recursive non-optimal filter. The boundedness of the error covariance is a prerequisite for the definition of a Lyapunov function involved in the state estimation error dynamics stability analysis.

Résumé : Abstract : Resumen : Structural Health Monitoring (SHM) enables assessing in-service structures' performance by localizing structural anomaly instances immediately after their occurrence. Typical SHM approaches monitor the entire structural spatial domain aggravating the required density and cost of instrumentation. Further, with modelbased approaches, the entire structural domain is needed to be defined with high dimensional, computeintensive models rendering the SHM approaches ill-posed and slow especially when the instrumentation is limited and system observability is compromised. Moreover, in absence of high-fidelity models, oversimplification and subsequent model inaccuracies may lead to inaccurate estimation and possibly false alarms even if a subdomain is modeled inaccurately, e.g. support boundaries. To mitigate such issues, stand-alone monitoring focusing only on a subdomain of interest may be a computationally cheaper and prompt approach while being substantially robust to false alarms. Typically, such stand-alone substructure monitoring approaches demand extensive measurement of the interface, which can be a challenge in real-life applications. This paper presents a novel filtering-based online time domain approach for estimating substructure parameters without the need to measure or estimate the substructure interfaces. The proposed component-wise estimation is stand-alone so that the health estimation of the complete structural domain can be undertaken in parallel and later coupled through post-processing. The requirement of the interface measurement has been alleviated by employing an output injection approach. The proposal has been validated on a numerical beam structure subjected to arbitrary forces and subsequently, the sensitivity against noise and damage severity of the proposal has been investigated. Finally, the proposal is validated on a real beam to illustrate its real-life applicability and significance.

Résumé : Abstract : Resumen : The interpretation of stabilization diagrams is a classical task in operational modal analysis, and has the goal to obtain the set of physical modal parameters from estimates at the different model orders of the diagram. The diagrams are contaminated by spurious modes that appear due to the unknown (non-white) ambient excitation and sensor noise, as well as possible over-modelling. Under the premise that spurious modes will vary and physical modes will remain quite constant at different model orders, the focus is to retrieve the physical modes that constitute the identified model, while rejecting the non-physical, spurious modes. Over the last decade, extensive research has been devoted for developing automated strategies facilitating their interpretation. To this end, the interpretation is in principle disconnected from the identification method and boils down to three stages i.e., clearing the diagram from the spurious mode estimates, aggregating the modal parameter estimates in modal alignments and the final parameter choice. Besides the point estimates of the modal parameters, also their confidence bounds are available with some identification methods, such as subspace identification. These uncertainties provide useful information for an automated interpretation of the stabilization diagrams. First, modes with high uncertainty are most likely non-physical modes. Second, the confidence bounds provide a natural threshold for the automated extraction of modal alignments, avoiding the requirement of a deterministic threshold regarding the allowable variation within an alignment. In this paper, a strategy is presented for the automated mode extraction considering their uncertainties, based on clustering a statistical distance measures between the modes. The relevance of the uncertainty consideration in the automated extraction will be demonstrated on vibration data from two bridges.

Résumé : Abstract : Resumen : A bi-static Ground Penetrating Radar (GPR) has been developed for the detection of cracks and buried pipes in urban grounds. It is made of two shielded Ultra Wide Band (UWB) bowtie-slot antennas operating in the frequency band [0.3;4] GHz. GPR signals contain not only responses of targets, but also unwanted effects from antenna coupling in air and in the soil, system ringing, and soil reflections that can mask the proper detection of useful information. Thus, it appears necessary to propose and assess several clutter reduction techniques as pre-processing techniques to improve the signal-to-noise ratio, discriminate overlapping responses issued from the targets and the clutter, and ease the use of data processing algorithms for target detection, identification or reconstruction. In this work, we have evaluated on Bscan profiles three different statistical data analysis such as mean subtraction, Principal Component Analysis (PCA), and Independent Component Analysis (ICA) considering a shallow and a medium depth target. The receiver operating characteristics (ROC) graph has allowed to evaluate the performance of each data processing in simulations and measurements to further draw a comparison in order to select the technique most adapted to a given soil structure with its radar probing system.

Résumé : Abstract : Resumen : Global Navigation Satellite Systems (GNSS) provide accurate and reliable positioning solutions in open field environments. However, the positioning performance is not the same in dense urban areas, where satellite signals are blocked or reflected by tall buildings. A 3D city model, "Urban Trench", is introduced to simulate blockage and reflection of GNSS signals. The "Urban Trench" model assesses the reflection environment of the city and the non-light-of-sight (NLOS) ranging errors are corrected, based on satellite elevation and a 3D surface model. Subsequently, the metric of NLOS signal exclusion using an elevation-enhanced map is developed and tested using real vehicular data in the test urban network of Nantes. A GPS&GLONASS-constellation single-frequency receiver is used during the experiment. The performance of both systems, stand alone and in combination as dual-constellation, are presented, compared and evaluated, with and without "Urban Trench" model implementation. Additionally, a fault detection and exclusion test is applied, to check and enhance the integrity of the output.

Résumé : Abstract : Resumen : This paper presents the feasibility of damage detection in asphalt pavements by embedded fiber optics as a new non-destructive inspection technique. The distributed fiber optic sensing technology based on the Rayleigh scattering was used in this study. The main advantage of this technique is that it allows to measure strains over a long length of fiber optic with a high spatial resolution, less than 1 cm. By comparing strain profiles measured at different times, an attempt was made to link strain changes with the appearance of damage (cracking) in the pavement. This non-destructive method was evaluated on accelerated pavement testing facility, in a bituminous pavement. In our experimentation, the optical fibers were placed near the bottom of the asphalt layer. The application of 728 000 heavy vehicle loads (65 kN dual wheel loads) was simulated in the experiment. Optical fiber measurements were made at regular intervals and surface cracking of the pavement was surveyed. After some traffic, a significant increase of strains was detected by the optical fibers at different points in the pavement structure, before any damage was visible. Later, cracking developed in the zones where the strain profiles were modified, X. Chapeleau et al. thus indicating a clear relationship between the increased strains and crack initiation. These first tests demonstrate that distributed fiber optic sensors based on Rayleigh scattering can be used to detect crack initiation and propagation in pavements, by monitoring strain profiles in the bituminous layers.

Résumé : Abstract : Resumen : To optimize de-icers use in winter on roads and airports, some sustainable solutions were promoted in a global project entitled "Roads of the Future". PCM into pavements were then considered to rely on the released enthalpy to delay the occurrence of black ice or snow accumulation. Coupling a spectroscopic monitoring of the PCM behavior and thermography on pavement surface indicated a significant delay between the phase change and the thermal manifestation of the released energy. Considering an accurate description of PCM according to cooling weather phenomena, these elements might provide valuable information for numerical models.

Résumé : Abstract : Resumen : Ground penetrating radar (GPR) is a well-known non-destructive technique based on electromagnetic wave propagation that is able to detect by reflection or scattering of waves dielectric discontinuities in the underground. Our application is mainly concerned with civil engineering to perform supervision, inventory, and soil characterization. Because the air-coupled radar suffers from a significant reflection at the ground interface that reduces energy transfer of electromagnetic radiation in the sub-surface and penetration depth, we have developed an ultra-wide band (UWB) ground-coupled radar made of a pair of partially shielded compact planar bowtie slot antennas. As the antenna dimension (36*23 cm2) is close to the A4 sheet size, the maturity of the microstrip technology has allowed to design a particular geometry on the FR4 substrate (h=1.5 mm) which is able to operate at frequencies from 460 MHz to beyond 4 GHz in air. Contrary to a commercial GPR where details on antenna design are not available, it appears here possible to know and control the radiation characteristics and develop full-wave FDTD modeling that can represent field experiments for comparisons and analyses. The objective of this work is to improve, by means of a parametric study, the knowledge of physical phenomena involved in dielectric polarization when waves interact with buried discontinuities and particularly cracks, pipes, delaminations that can be distinguished by their shape, size, dielectric contrast with the surrounding medium, orientation relative to the electric field. . . Thus, we have first characterized by FDTD modeling and field measurements in a wet sand the radar link in two perpendicular polarizations (parallel and mirror) in the presence of a common soil (epsilon’=5.5, sigma=0.01 S/m) considering variable offsets. Afterwards, we have studied and analyzed the hyperbola signatures generated by the presence of buried canonical objects (pipes, strips) with several dielectric properties (dielectric and conductive) in a wet sand with a small lateral dimension (less than 20 mm) in both polarizations. Comparisons with FDTD simulations including the detailed structure of the antennas appear promising as they have allowed to interpret the measurements and take advantage of signal polarization to extract information associated with the discontinuities. After cluster removal using classical data processing (SVD, median value substraction. . . ), the analytical model based on the ray theory and including the antenna size has allowed to first analyze the hyperbola responses. This study is supposed to prepare the development of data processing associated with B-scans to extract quantitative information from the electromagnetic probing of the subsurface in a very large frequency band.

Résumé : Abstract : Resumen : La Métropole Rouen Normandie souhaitait concevoir une nouvelle passerelle nécessitant des appuis provisoires en Seine. Aussi a-t-elle sollicité l’Ifsttar pour conduire une étude statistique des données de trajectoires, afin de définir les fuseaux de mobilité des navires en fonction notamment de leur vitesse et de leur gabarit, deux facteurs susceptibles d’avoir un impact sur la manoeuvrabilité des navires. Le traitement des données au format SIA a nécessité de recourir à des outils dédiés aux gros fichiers de données. Puis un modèle de régression linéaire a été retenu pour l’analyse des trajectoires rectilignes hors manoeuvres d’accostage. La détermination d’intervalles de prédiction a permis de délimiter les zones de navigation, et donc de mettre en évidence les surfaces du fleuve aptes à accueillir les appuis provisoires.

Résumé : Abstract : Resumen : Digital image correlation is a popular method for estimating object displacement in successive images. At the pixel level, displacement is estimated by maximizing the crosscorrelation between two images. To achieve subpixel accuracy, displacement estimation can be refined in the vicinity of the crosscorrelation peak. Among existing refinement methods, quadratic surface fitting provides a good trade-off between accuracy and computational burden. The purpose of this paper is to analyze the quadratic surface fitting method. It is shown that the quadratic surface fitted to the cross-correlation values in the vicinity of the cross-correlation peak does not always have a maximum. Then the conditions ensuring the existence of a maximum are analyzed. The reported results consolidate the theoretic basis of the quadratic surface fitting method for subpixel motion extraction.

Résumé : Abstract : Resumen : Structural health monitoring (SHM) systems often ask for a robust, flexible and costeffective solution. In that domain, since years, the technological development of Wireless Sensor Network try to be an answer. Between many other questions, one of the keypoint in wireless sensing resides in the time synchronization (e.g. how to ensure the same time base between electronic systems that doesn't know each other?). At Gustave Eiffel University, robust and deterministic solutions based on GNSS modules have already been demonstrated [1], the goal of the work presented in this paper is to go deeper into turn-key solutions by implementing and coupling this GNSS-synchronization principle into a low-power FPGA to an Analog-To-Digital converter. This hardware and software association represents a generic solution for signal sampling in a wireless manner. This work is illustrated and demonstrated by an application on the acoustic monitoring of wire-breaks in bridges cables.

Résumé : Abstract : Resumen : This paper presents an inverse Algebraic Wavenumber Identification (AWI) technique for multi-modal 1D-periodic structures, which can extract complex wavenumbers from steady-state vibration measurements under stochastic conditions. These wave dispersion characteristics provide valuable vibroacoustic indicators for model updating, damage monitoring in operational conditions, or metamaterial design. Wavenumber extraction techniques are highly sensitive to noisy measurements, nonuniform sampling points, or geometrical uncertainties. The proposed formulation relies on algebraic parameters identification to enable the extraction of complex wavenumbers in four scenarios: (a) low Signal Noise Ratio; (b) small perturbation caused by uncertainties on sampling points' coordinates; (c) unknown structural periodicity; (d) nonuniform sampling. This AWI is compared with Inhomogeneous Wave Correlation (IWC) method and INverse COnvolution MEthod (INCOME) to assess the robustness and accuracy of the method.

Résumé : Abstract : Resumen : L'anticipation des phénomènes de crues soudaines est d'une importance cruciale pour limiter leurs effets dommageables. Pour mieux répondre à ce besoin, le projet de recherche ANR Prévision immédiate intégrée des impacts des crues soudaines (PICS, 2018-2021) vise à concevoir et évaluer des chaînes de prévision des crues soudaines et de leurs impacts offrant jusqu'à 6h d'anticipation. Le projet repose sur l'interaction entre des équipes scientifiques aux compétences variées (météorologues, hydrologues, hydrauliciens, économistes, sociologues), et des acteurs opérationnels (sécurité civile, autorités locales, compagnies d'assurance, gestionnaires d'ouvrages hydroélectriques et de réseaux de transport). Les chaînes de prévision testées intégreront : i) des estimations quantitatives de précipitations à haute résolution et des prévisions immédiates de pluie pour des horizons de 0 à 6h, ii) des modèles pluie-débit distribués adaptés aux petits cours d'eau non jaugés, iii) des modèles hydrauliques pour la délimitation des zones potentiellement inondées à partir de modèles numériques de terrain, et iv) plusieurs modèles d'impacts visant à représenter les effets socio-économiques des crues. Le projet visera à coupler ces différents modèles, à estimer leurs incertitudes et complémentarité, et à évaluer la capacité des chaînes de prévision proposées à répondre aux besoins des utilisateurs finaux à partir d'études de cas.

Résumé : Abstract : Resumen : Large-scale civil infrastructures play a vital role in society as they ensure smooth transportation and improve the quality of people's daily life. However, they are exposed to several and continuous external dynamic actions such as wind loads, vehicular loads, and environmental changes. Interaction assessment between external actions and civil structures is become more challenging due to the rapid development of transportation. Data-driven models have lately emerged as a viable alternative to traditional model-based techniques. They provide different advantages: timely damage detection, structural behaviors prediction and suggestions for optimal maintenance strategies. The chapter aims to describe the advantages and the characteristics of datadriven techniques to predict the dynamic behavior of civil structures through Artificial Neural Network (ANN). The applicability and effectiveness of the proposed approach are supported by the results achieved processing the measurements coming from a monitoring system installed on a cable-stayed bridge (Tabarly, Nantes). Accelerations recorded by a network of sixteen mono-axial accelerometers and Nantes Airport weather data acquired with the observation platform of the METAR (MEteorological Terminal Aviation Routine Weather Report) Station Network have been used as training to predict the structural response and to statistically characterize the behavior through a Nonlinear AutoRegressive (NAR) prediction network. The performance has been evaluated through statistical analysis of the error between the measured and predicted values also related to both environmental conditions and number of the signals. The results show that the forecast network could be useful to detect the trigger of anomalies, hidden in the dynamic response of the bridge, at a low computational cost.

Résumé : Abstract : Resumen : This paper presents an algebraic wavenumber identification method to identify wavenumbers under stochastic conditions. Stochastic condition results from the introduction of small perturbation which is referred to the uncertainty of measurements points’ coordinates caused by the operation faults or problems with experimental errors. The proposed method is compared with two popular alternatives, namely: inhomogeneous wave correlation method and inverse convolution method which are both capable of extracting the bending wavenumbers of a meta-structure. A good performance is observed for the identification of complex wavenumbers in presence of uncertainty. In addition, the proposed method needs to solve a linear problem, reducing the computational cost compared to the inhomogeneous wave correlation method.

Résumé : Abstract : Resumen : Rotating machinery are present in many engineering applications. Such rotor systems often subjected to high vibration loads that can be at the origin of noise or failure. For these reasons, it is of main importance to predict with accuracy the critical speeds and the dynamic response amplitude of such structures. However, they are often subjected to many potential uncertainties that may rise from environmental variations or manufacturing tolerances. These uncertain parameters, often described as random, are often numerous and must be taken into consideration during the design stage. For this, some design parameters are usually adjusted to propose a robust design of the rotor, considering the possible variation of the random parameters. Performing such studies require to be able to deal with a high number of uncertain parameters and with parameters of different nature, namely parametric and random. This work proposes to illustrate the efficiency of advanced kriging-based surrogate modelling in order to achieve such a goal. The proposed hybrid surrogate-model combines polynomial chaos expansion and kriging to deal with both parameter natures, to consider nine varying parameters of a full finite element model of the rotating system under study. For the first time, this hybrid surrogate model is applied to perform rotordynamics analysis and more specifically the prediction of critical speeds and the associated unbalance responses for a complex rotor system with uncertainties. Compared to previous works, the kriging performances are significantly increased by integrating some physical properties of the rotor directly in its construction. Finally, the hybrid surrogate model gives a direct access to the Sobol indices which makes it possible to carry out without additional computation costs an extensive sensitivity analysis.

Résumé : Abstract : Resumen : Abstract In this paper, a numerical strategy based on the combination of the kriging approach and the Polynomial Chaos Expansion (PCE) is proposed for the prediction of buckling loads due to random geometric imperfections and fluctuations in material properties of a mechanical system. The original computational approach is applied on a beam simply supported at both ends by rigid supports and by one punctual spring whose location and stiffness vary. The beam is subjected to a deterministic axial compression load. The PCE-kriging meta-modelling approach is employed to efficiently perform a parametric analysis with random geometrical and material properties. The approach proved to be computationally efficient in terms of number of model evaluations and in terms of computational time to predict accurately the buckling loads of a beam system. It is demonstrated that the buckling loads are substantially impacted not only by both the location and the stiffness of the spring, but also by the random parameters.

Résumé : Abstract : Resumen : It is essential to predict accurately the critical speeds and associated vibration amplitudes of rotating machineries to ensure a correct design to limit noise nuisance and fatigue failure. However, numerous uncertainties are present, due to environmental variations or manufacturing tolerances for e.g., and must be taken into consideration in the design stage to limit their impact on the system dynamics. These uncertainties are usually modelled with a probability law and the dynamic response becomes stochastic. On the other side, during the design stage, a few key parameters, often called design parameters, are identified and tuned to ensure a robust conception of the rotor w.r.t to the uncertain model parameters. In this context, one must tackle a high-dimension parametric problem but numerous parameters of different nature. The efficiency of an advanced meta-modelling technique that couple polynomial chaos expansion and kriging is demonstrated here. The kriging efficiency is improved by introducing physical properties of the rotor. A finite element model of a rotor subjected to nine uncertain parameters is studied. The hybrid surrogate model gives a direct access to the Sobol indices, exploited to conduct an extensive sensitivity analysis.

Résumé : Abstract : Resumen : In tropical areas, with marine environment, high temperature and humidity, corrosion is a constant threat. The maintenance of steel structures (like FPSO’s) is becoming a challenge. The current technique of “crop and renewing” repair involves a certain number of major issues for project owners such as: “hot work”, that is to say welding; temporary weakening of the structure; need to empty, clean and purging the oil tanks of the FPSO’s, resulting in long downtime and an expensive solution. “Cold repair”, such as composite repair, is a promising solution. However, surface preparation and the influence of the primer are crucial issues to be addressed to ensure the strength and reliability of this type solution based on bonded patch. The paper presents an experimental study of the influence of the surface preparation and the primer on the strength of small steel bonded specimens which have been deliberately degraded by corrosion and pollution. Several surface preparation methodologies were investigated and the quality of these preparations was assessed using methods that can be implemented on site. Two main aspects were investigated: the detection of the residual presence of pollutants through the use of a portable infrared spectrometer; and the determination of surface energy after preparation using contact angle and wettability measurement equipment. To study the impact of the primer on the adhesion capacity of the steel surface, critical toughnesses measurements was performed with End notch flexure tests. Three configurations have been tested: bonding with the epoxy resin without initial application of primer and bonding with the Epoxy resin with initial application of two Primer A and B. The results shown clearly that the type of primer and the quality of its application are paramount importance to ensure the strength of steel bonded patches.

Résumé : Abstract : Resumen : For joint estimation of state variables and unknown parameters, adaptive observers usually assume some persistent excitation (PE) condition. In practice, the PE condition may not be satised, because the underlying recursive estimation problem is ill-posed. To remedy the lack of PE condition, inspired by the ridge regression, this paper proposes a regularized adaptive observer with enhanced parameter adaptation gain. Like in typical ill-posed inverse problems, regularization implies an estimation bias, which can be reduced by using prior knowledge about the unknown parameters.

Résumé : Abstract : Resumen : We consider a simplied model of a coupled parabolic PDE-ODE describing heat transfer within buildings. We describe an identication procedure able to reconstruct the parameters of the model. The response of the model is nonlinear with respect to its parameters and the reconstruction of the parameters is achieved by the introduction of a new vectorial descent stepsize, which improves the convergence of the Levenberg-Marquardt minimization algorithm. The new vectorial descent stepsize can have negative and positive entries of different sizes, which fundamentally differs from standard scalar descent stepsize. The new algorithm is proved to converge and to outperform the standard scalar descent strategy. We also propose algorithms for the initialization of the parameters needed by the reconstruction procedure, when no a priori knowledge is available.

Résumé : Abstract : Resumen : In this paper, we propose to perform time-delay estimation (TDE) of coherent GPR signals by taking into account the radar pulse and noise pattern. The proposed method can process raw GPR data without whitening procedure and decorrelate coherent signals properly with a Hankel matrix which contains the signal eigenvector, the radar pulse and the noise characteristics. Simulations and a field experiment show the effectiveness of the proposed method.

Résumé : Abstract : Resumen : This paper derives a formula to determine the minimum detectable damage based on ambient vibration data. It is a key element to analyze which damage scenarios can be detected before a monitoring system is installed. For the analysis, vibration data from the reference structure as well as a finite element model are required. Minimum detectability is defined by adopting a code-based reliability concept that considers the probability of detection and the probability of false alarms. The results demonstrate that the minimum detectable damage depends on three elements: the uncertainty of the damage-sensitive feature (which decreases with increasing measurement duration), its sensitivity towards model-based design parameters, and the reliability requirements regarding the damage diagnosis results. The theory is developed for the stochastic subspace-based damage detection method but can be applied to any damage-sensitive feature provided its sensitivities and statistical properties can be characterized. For proof of concept, the minimum detectable change in stiffness and mass of a pin-supported beam are analyzed in a numerical and experimental study, respectively. The predictions with the developed approach appear to be accurate and robust to noise effects for both simulated and real data.

Résumé : Abstract : Resumen : Ground penetrating radar (GPR) and electric resistivity tomography (ERT) are well assessed and accurate geophysical methods for the investigation of subsurface geological sections. In this paper, we present the joint exploitation of these methods at the Montagnole (French Alps) experimental site with the final aim to study and monitor effects of possible catastrophic rockslides in transport infrastructures. The overall goal of the joint GPR–ERT deployment considered here is the careful monitoring of the subsurface structure before and after a series of high energetic mechanical impacts at ground level. It is known that factors such as the ambiguity of geophysical field examination, the complexity of geological scenarios and the low signal-to-noise ratio affect the possibility of building reliable physical–geological models of subsurface structure. Here, we applied to the GPR and ERT methods at the Montagnole site, recent advances in wavelet theory and data mining. The wavelet approach was specifically used to obtain enhanced images (e.g. coherence portraits) resulting from the integration of the different geophysical fields. This methodology, based on the matching pursuit combined with wavelet packet dictionaries, permitted us to extract desired signals under different physical–geological conditions, even in the presence of strongly noised data. Tools such as complex wavelets employed for the coherence portraits, and combined GPR–ERT coherency orientation angle, to name a few, enable non-conventional operations of integration and correlation in subsurface geophysics to be performed. The estimation of the above-mentioned parameters proved useful not only for location of buried inhomogeneities but also for a rough estimation of their electromagnetic and related properties. Therefore, the combination of the above approaches has allowed us to set up a novel methodology, which may enhance the reliability and confidence of each separate geophysical method and their integration.

Résumé : Abstract : Resumen : Floating productions, storage and offloading (FPSO) units are subject to corrosion problems. The use of adhesively bonded FRP patches as a repair appears to be a particularly interesting solution. However, design strategies still need to be improved and validated to insure the robustness and, ultimately, confidence in this solution. Since 2018, Bureau Veritas leads a joint industrial project called Strength Bond Offshore which aims at defining such a design strategy. First, the patch designed during this project will be presented. Then, the experimental test campaign is detailed: manufacturing, monotonic tests in traction and bending. Finally, the results of the fatigue tests campaign are developed. Ongoing additional developments are under progress to better assess equivalent interfacial behaviors for an overall design strategy.

Résumé : Abstract : Resumen : In this study, we present an inversion approach to detect and localize inclusions in thick walls under natural so-licitations. The approach is based on a preliminary analysis of surface temperature field evolution with time (for instance acquired by infrared thermography); subsequently, this analysis is improved by taking advantage of a priori information provided by ground-penetrating radar reconstruction of the structure under investigation. In this way, it is possible to improve the accuracy of the images achievable with the stand-alone thermal reconstruction method in the case of quasi-periodic natural excitation.

Résumé : Abstract : Resumen : The use of Machine Learning (ML) has rapidly spread across several fields of applied sciences, having encountered many applications in Structural Dynamics and Vibroacoustic (SD&V). An advantage of ML algorithms compared to traditional techniques is that physical phenomena can be modeled using only sampled data from either measurements or simulations. This is particularly important in SD&V when the model of the studied phenomenon is either unknown or computationally expensive to simulate. This paper presents a survey on the application of ML algorithms in three classical problems of SD&V: structural health monitoring, active control of noise and vibration, and vibroacoustic product design. In structural health monitoring, ML is employed to extract damage-sensitive features from sampled data and to detect, localize, assess, and forecast failures in the structure. In active control of noise and vibration, ML techniques are used in the identification of state-space models of the controlled system, dimensionality reduction of existing models, and design of controllers. In vibroacoustic product design, ML algorithms can create surrogates that are faster to evaluate than physics-based models. The methodologies considered in this work are analyzed in terms of their strength and limitations for each of the three considered SD&V problems. Moreover, the paper considers the role of digital twins and physics-guided ML to overcome current challenges and lay the foundations for future research in the field.

Résumé : Abstract : Resumen : In the field of geophysics and civil engineering applications, ground penetrating radar (GPR) technology has become one of the emerging non-destructive testing (NDT) methods thanks to its ability to perform tests without damaging structures. However, NDT applications, such as concrete rebar assessments, utility network surveys or the precise localization of embedded cylindrical pipes still remain challenging. The inversion of geometric parameters, such as depth and radius of embedded cylindrical pipes, as well as the dielectric parameters of its surrounding material, is of great importance for preventive measures and quality control. Furthermore, the precise localization is mandatory for critical underground utility networks, such as gas, power and water lines. In this context, innovative signal processing techniques associated with GPR are capable of performing physical and geometric characterization tasks. This paper evaluates the performance of a supervised machine learning and ray-based methods on GPR data. Support vector machines (SVM) classification, support vector machine regression (SVR) and ray-based methods are all used to correlate information about the radius and depth of embedded pipes with the velocity of stratified media in various numerical configurations. The approach is based on the hyperbola trace emerging in a set of B-scans, given that the shape of the hyperbola varies greatly with pipe depth and radius as well as with velocity of the medium. According to the ray-based method, an inversion of the wave velocity and pipe radius is performed by applying an appropriate nonlinear least mean squares inversion technique. Feature selection within machine learning models is also implemented on the information chosen from observed hyperbola travel times. Simulated data are obtained by means of the finite-difference time-domain (FDTD) method with the 2D numerical tool GprMax. The study is carried out on mono-static, ground-coupled GPR datasets. The preliminary study showed that the proposed machine learning methods outperforms the ray-based method for estimating radius, depth and velocity. SVR, for instance, calculates depth and radius values with mean absolute relative errors of 0.39% and 6.3%, respectively, with regard to the ground truth. A parametric comparison of the aforementioned methodologies is also included in the performance analysis in terms of relative error.

Résumé : Abstract : Resumen : In the field of civil engineering, ground penetrating radar (GPR) is a highly efficient nondestructive testing tool for sustainable management of pavement infrastructures. GPR allows to evaluate the structure of the roadway over large distances (with contactless configurations) and to detect significant subsurface defects. This letter presents a new method to detect thin debondings within pavement structures with the step-frequency GPR. The proposed method enables us to carry out the detection with only a small number of frequency samples and A-scans. It is based on the linear prediction and support vector regression theories. Two experimental results show its effectiveness.

Résumé : Abstract : Resumen : Temperature estimation through infrared thermography is facing the lack of knowledge of the observed material's emissivity. The derivation of the physical equations lead to an ill-posed problem. A new Kriged Interacting Particle Kalman Filter is proposed. A state space model relates the measurements to the temperature and the Kalman filter equations yield a filter tracking the temperature over time. Moreover, a particle filter associated to Kriging prediction is interacting with a bank of Kalman filters to estimate the time-varying parameters of the system. The efficiency of the algorithm is tested on a simulated sequence of infrared thermal images.

Résumé : Abstract : Resumen : Despite recent publications, the strain transfer in distributed optical fiber sensors is still often overlooked and poorly understood. In the first part of this paper, strain transfer is shown to be driven by a second-order differential equation, whether the optical fiber is embedded into the host material or surface-mounted. In this governing equation, only the value of a key parameter, called strain lag parameter, varies according to the attachment configuration and the type of optical fiber used as a sensor. Then, a general solution of the governing equation is proposed. It is an analytical expression established from new boundary conditions that are more adequate than those used previously in the literature and allows the determination of the strain profile in the core of a distributed optical fiber sensor under any arbitrary strain fields. This general solution has been validated by two experiments presented in the third part of the paper. A very good agreement between the analytical solutions and measured strain profiles using a high spatial resolution optical interrogator for both uniform and non-uniform strain fields has been obtained. These results highlight the importance of the strain lag parameter which must be taken into account for a correct interpretation of measurements, especially in the case of important strain gradients.

Résumé : Abstract : Resumen : Still very few publications relate test results of multiconstellation receivers since Galileo satellites massive launch by Ariane 5, leading to more than 20 operational space vehicles in orbit. One can refer to automotive receivers and smartphones test bench made during the European COST action SaPPART (Satellite Positioning Performance Assessment for Road Transport), but this was GPS only or GPS+Glonass. This article gives an overview of a test carried out in the city of Nantes, France, and its suburban area, with a brand new receiver, F9P, of the automotive range of Ublox. The dual constellation configuration GPS+Galileo is tested. This receiver is benchmarked with respect to the previous generation of Ublox LEA6T.

Résumé : Abstract : Resumen : The paper gives an overview of 3D GPR experiment to survey debonding areas within pavement structure during accelerated pavement testing on the IFSTTAR’s fatigue carrousel. Several artificial defects (tack-free, geotextile and sand-based) have been embedded during the construction phase between the top and the base layers. The data collection was organized in a two-stage experiments and covers the full life-cycle of the pavement structure. During the first stage that took place in 2012-13 leading to 300 kloading cycles, the structure revealed no clear degradation. Then, the second measurement campaign was performed in 2019 and lasted up to 720k loadings, until revealing a strongly degraded pavement surface. 3D GPR data were collected at 396, 500, 600 and 720 kloading cycles. They were completed by conventional 2D ground-coupled 1.5 and 2.6 GHz measurements in transverse and longitudinal directions. Radar data at 1.5 GHz are processed and compared on the three major defects.