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Dimension reduction (DR) methods provide systematic approaches for analyzing high-dimensional data. A key requirement for DR is to incorporate global dependencies among original and embedded samples while preserving clusters in the embedding space. To achieve this, we combine the principles of optimal transport (OT) and principal component analysis (PCA). Our method seeks the best linear subspace that minimizes reconstruction error using entropic OT, which naturally encodes the neighborhood information of the samples. From an algorithmic standpoint, we propose an efficient block-majorization-minimization solver over the Stiefel manifold. Our experimental results demonstrate that our approach can effectively preserve high-dimensional clusters, leading to more interpretable and effective embeddings. Python code of the algorithms and experiments is available online.

National audience; -L'imagerie radar à travers murs (TWRI) est un domaine de recherche en cours qui vise à étudier l'intérieur d'un bâtiment depuis son extérieur. Dans le cadre le plus courant, il cherche à détecter ou à surveiller des cibles fixes. S'éloignant des techniques classiques de radar à synthèse d'ouverture (SAR), des problèmes de regression parcimonieuse ont été proposés pour résoudre ce problème. Ces méthodes reposent sur une étape de prétraitement où une séparation appropriée des sous-espaces mur et cibles est effectuée pour supprimer la réponse du mur obstruant la vue du radar sur la pièce. Dans ce travail, nous explorons des méthodes en une étape utilisant des méthodes de décomposition jointe en composantes de faible rang et parcimonieuse via Robust PCA (RPCA). La nouveauté est une reconstruction en une étape par un problème d'inversion structuré en produit de Kronecker pour lequel nous adaptons l'algorithme Alternating Direction Method of Multipliers (ADMM). Nous validons et comparons notre méthode sur des simulations.

International audience; Les radio-interféromètres sont des réseaux phasés produisant des images à haute résolution à partir de la matrice de covariance des mesures. L'étalonnage de tels instruments est nécessaire et constitue une tâche critique. Toutefois, les radio-interféromètres modernes représentent un nouveau défi pour la radioastronomie car ils sont plus sensibles aux interférences de radiofréquence (RFI). En effet, la présence de RFI dans le processus de calibration induit des biais dans l'estimation des erreurs instrumentales. L'objectif de cet article est de proposer une alternative pour atténuer les effets des RFI. Pour cela, nous proposons d'abord un modèle permettant de prendre en compte la présence de RFI dans les données sur plusieurs canaux de fréquences grâce à un modèle de rang faible. Nous réalisons ensuite une estimation par maximum de vraisemblance des paramètres de calibration avec un algorithme d'Espérance Maximisation Généralisée sur Espaces Alternés (SAGE). Pour cet algorithme, nous dérivons deux ensembles originaux de données complètes, pour lesquels nous obtenons des solutions explicites. Des simulations numériques montrent un gain en performance significatif sur des données corrompues par des RFI comparé aux méthodes de l'état de l'art.

This paper proposes new algorithms for the metric learning problem. We start by noticing that several classical metric learning formulations from the literature can be viewed as modified covariance matrix estimation problems. Leveraging this point of view, a general approach, called Robust Geometric Metric Learning (RGML), is then studied. This method aims at simultaneously estimating the covariance matrix of each class while shrinking them towards their (unknown) barycenter. We focus on two specific costs functions: one associated with the Gaussian likelihood (RGML Gaussian), and one with Tyler's M -estimator (RGML Tyler). In both, the barycenter is defined with the Riemannian distance, which enjoys nice properties of geodesic convexity and affine invariance. The optimization is performed using the Riemannian geometry of symmetric positive definite matrices and its submanifold of unit determinant. Finally, the performance of RGML is asserted on real datasets. Strong performance is exhibited while being robust to mislabeled data., Published in EUSIPCO 2022. Best student paper award

International audience; In this paper, we consider a domain decomposition algorithm associated to a finite element method to approximate a unilateral frictionless contact problem between two elastic bodies. We present a global error estimator that takes into account of the error introduced by finite element analysis as well as the error introduced by the iterative resolution of the domain decomposition algorithm. The control of these error sources is a key point in order to introduce adaptive techniques and we propose error indicators that estimate the contribution of each source of error.

International audience; This study presents a general simulation methodology to assess both full and partial composite action of steel-concrete-steel (SCS) structures. This refined methodology, using 3D finite elements, is applied to two three-point bending beams in which a different composite action is provided through variation of the number of studs. The comparison to experimental results validates the methodology and the global and local behavior can be reproduced. However, the important calculation cost reduces the use of this numerical strategy to more complex structures. A simplified methodology is proposed with 1D finite elements to represent the connectors. This modelling choice allows to greatly reduce the computational cost. It also imply a reduction of the reproduced phenomena. Particularly, local damage of the concrete core around the dowels is slightly different. Nevertheless, this strategy allows to accurately reproduce the global behavior as well as the failure modes of SCS beams with full and partial composite action.

International audience; In order to evaluate the cracking process in large reinforced and pre-stressed concrete structures, a predictive model of concrete damage with refined mesh and a nonlinear law can be required. Because of the computational load, such modelling is not applicable directly on large-scale structures whose characteristic dimensions are over several meters. To overcome this difficulty, a method based on the static condensation, called “ASC” has been proposed. It concentrates the computational effort on the damaged area, which can evolvedue to crack propagation or initiation. In order to reach a higher level of representativeness, mesh refinement is integrated into the ASC method in the proposed contribution. The method first uses a coarse initial mesh and refines it only in the domain of interest (DI) to reach a density of mesh adapted to a non-local model (order of the centimeter). This principle of refinement, integrated in the ASC method, is described. It is then applied to a notched bending beam. The use of mesh refinement combined to ASC method allow to keep results similar to a calculation with a fine meshon the entire structure. However, it also allows a saving in computational time and in memory occupation that increases with the increase in the mesh density of the refined zones.

International audience; In order to evaluate the cracking process in large reinforced and pre-stressed concrete structures, a predictive simulation of concrete damage with a refined mesh and a nonlinear law is required. Because of the computational load, such modelling is not applicable directly on large-scale structures whose characteristic dimensions are over several tens of meters. To deal with this type of structure, an adaptive static condensation method (ASC), which concentrates the computational effort on the damaged area (domain of interest) only, is proposed. The ASC method is first presented. A particular attention is paid to the needed developments to extend its domain of application up to prestressed concrete structures. The method is then applied to a three point bending prestressed beam and validated by comparison to a classical finite element damage computation. The numerical efficiency of the proposed approach is evaluated with, on this application, a time saving factor of about 15.An automatic mesh partitioning method is then implemented to make the method even more efficient. Based on physical considerations, it takes into account the expected shape and the evolution of the damaged regions during the loading. It is applied to three test cases with different geometries and loading to discuss the calibration process through a sensitivity analysis. A unique set of parameters is finally proposed and the efficiency of the method is demonstrated. As a conclusion; a complete automatic method is made available for the simulation of large scale reinforced and prestressed concrete structures

International audience; Radio interferometers are phased arrays producing high-resolution images from the covariance matrix of measurements. Calibration of such instruments is necessary and is a critical task. This is how the estimation of instrumental errors is usually done thanks to the knowledge of referenced celestial sources. However, the use of high sensitive antennas in modern radio interferometers (LOFAR, SKA) brings a new challenge in radio astronomy because they are more sensitive to Radio Frequency Interferences (RFI). The presence of RFI during the calibration process generally induces biases in state-of-the-art solutions. The purpose of this paper is to propose an alternative to alleviate the effects of RFI. For that, we first propose a model to take into account the presence of RFI in the data across multiple frequency channels thanks to a low-rank structured noise. We then achieve maximum likelihood estimation of the calibration parameters with a Space Alternating Generalized Expectation-Maximization (SAGE) algorithm for which we derive originally two sets of complete data allowing closed-form expressions for the updates. Numerical simulations show a significant gain in performance for RFI corrupted data in comparison with some more classical methods.

Angular and spectral separations of thermal radiation have become a key challenge in solar concentration or thermal management of sources radiating at extremely high or low temperatures. Reflections obtained from electromagnetic theory in an open cavity geometry increase the emission and absorption compared to a flat surface due to the cavity effect. In this paper, in order to obtain the directional emission of geometric surfaces (V-Grooves) using ray tracing and studying the propagation of light, a new algorithm is developed. The numerical simulations take into account the materials properties of both facets of the V-shape, thus simulating an original asymmetric and a multilayer V-shape and providing a very interesting directive thermal emission behavior. We evaluated the emission behavior from the reflection and emission coefficients of different rays at different angles for different parameters (materials properties, wavelength, and geometry). The simulations of a V-groove showed that due to the different reflections occurring inside an aluminum V-cavity with an aperture angle of 28°, the emissivity was well enhanced by 86% in the normal direction compared to a flat surface made of the same material. Moreover, using the original asymmetric opposite-sided materials (Al and Si) in a V- groove, it was possible to separate and control the emission by focusing the radiation or directing different spectral bands in different directions.

International audience; This paper presents a new algorithm for improving the estimation of interferometric SAR (InSAR) phases in the context of time series and phase linking approach. Based on maximum likelihood estimator of a multivariate Gaussian model, the estimation of the InSAR phases is solved using a Block Coordinate Descent algorithm. Compared to the state-of-the-art approaches, the main improvement lies on the joint estimation of the covariance matrix and the InSAR phases instead of using a plug-in coherence estimate obtained from the sample covariance of the data or the modeling of the temporal decorrelation of the target under observation. Results of synthetic simulations confirm the improvement brought by the proposed estimator.

International audience; The present work exploits a simulation-based design procedure to reduce the scattering of a metallic cylinder in desired directions using conformal sparse metasurfaces.

The aim of the present in vitro study was to evaluate specific mechanical and physicochemical properties of two calcium silicate based sealers, (AH Plus Bioceramic “AHPB”; Well-Root ST “WRST”), and a conventional resin sealer (AH Plus “AHP”). These aims were accomplished by assessing the porosity, pH, compression strength, roughness, wettability and cell attachment of the tested materials. The results were compared statistically using the one-way ANOVA test. Higher pH values were obtained in both AHPB and WRST compared to AHP at 3, 24 and 72 h (p < 0.05). A greater level of porosity and wettability was detected for both AHPB and WRST compared to the resin sealer AHP (p < 0.05). Evident cell growth characterized by elongated morphology was observed on the surface of AHPB and WRST, while only a thin layer of cells was seen on the surface of AHP. A significant lower compression strength and modulus were obtained in the specimens created using AHPB compared to those made with AHP and WRST (p < 0.05). The removal of calcium silicates may be quite tricky during endodontic retreatment. In conclusion, considering the limitations of the present in vitro study, both calcium silicate sealers demonstrated good physicochemical properties. However, the lower compression strength and modulus of AHPB may facilitate its removal and make the retreatment procedures considerably easier. Keywords: calcium silicate based sealer; resin sealer; mechanical properties; porosity

International audience; This paper studies a statistical model for heteroscedastic (i.e., power fluctuating) signals embedded in white Gaussian noise. Using the Riemannian geometry theory, we propose an unified approach to tackle several problems related to this model. The first axis of contribution concerns parameters (signal subspace and power factors) estimation, for which we derive intrinsic Cramér-Rao bounds and propose a flexible Riemannian optimization algorithmic framework in order to compute the maximum likelihood estimator (as well as other cost functions involving the parameters). Interestingly, the obtained bounds are in closed forms and interpretable in terms of problem's dimensions and SNR. The second axis of contribution concerns the problem of clustering data assuming a mixture of heteroscedastic signals model, for which we generalize the Euclidean K-means++ to the considered Riemannian parameter space. We propose an application of the resulting clustering algorithm on the Indian Pines segmentation problem benchmark.

International audience; In this paper, robust mean and covariance matrix estimation are considered in the context of mixed-effects models. Such models are widely used to analyze repeated measures data which arise in several signal processing applications that need to incorporate possible individual variations within a common behavior of individuals. In this context, most algorithms are based on the assumption that the observations follow a Gaussian distribution. Nevertheless, in certain situations in which the data set contains outliers, such assumption is not valid and leads to a dramatic performance loss. To overcome this drawback, we design an expectation-conditional maximization either algorithm in which the heterogeneous component is considered as a part of the complete data. Then, the proposed algorithm is cast into a parallel scheme w.r.t. the individuals in order to mitigate the computational cost and a possible central processor overload. Finally, the proposed algorithm is extended to deal with missing data which refers to the situation where part of the individual responses are unobserved. Numerical simulations are conducted to assess the performance of the proposed algorithm regarding robust regression estimators, probabilistic principal component analysis and its recent robust version.

The purpose of the present study was to evaluate the physicochemical properties and antibacterial activity of three calcium silicate cements. Mineral trioxide aggregate (MTA Biorep "BR"), Biodentine (BD) and Well-Root PT (WR) materials were investigated using scanning electron microscopy (SEM) at 24, 72 and 168 h of immersion in phosphate buffered saline (PBS). The antibacterial activity against Enterococcus faecalis (E. faecalis), the solubility, roughness, pH changes and water contact angle were also analyzed. All results were statistically analyzed using a one-way analysis of variance test. Statistically significant lower pH was detected for BD than WR and BR (p < 0.05). No statistical difference was found among the three materials for the efficacy of kill against E. faecalis (p > 0.05). Good antibacterial activity was observed (kill 50% of bacteria) after 24 h of contact. The wettability and the roughness of BR were higher than for the other cements (p < 0.05). BD was more soluble than WR and BR (p < 0.05). In conclusion, the use of bioceramic cements as retrograde materials may play an important role in controlling bacterial growth and in the development of calcium phosphate surface layer to support healing. Moreover, the premixed cement was easier to use than powder-liquid cement. Keywords: calcium silicate cement; powder–liquid cement; premixed cement; retrograde materials.

International audience; The information geometry of the zero-mean tdistribution with Kronecker-product structured covariance matrix is derived. In particular, we obtain the Fisher information metric which shows that this geometry is identifiable to a product manifold of S ++ p (positive definite symmetric matrices) and sS ++ p (positive definite symmetric matrices with unit determinant). From this result, we obtain the geodesics and the Riemannian gradient. Finally, this geometry makes it possible to propose an on-line covariance matrix estimation algorithm well adapted to large datasets. Numerical experiments show that optimal results are obtained for a reasonable number of data.

Sandwich structures are widely used in many industrial applications and especially in light aviation. The local buckling phenomenon named “wrinkling” is one of the primary causes of compressive failure of such structures. Its calculation is a difficult practical problem since this phenomenon cannot be captured by the GFEM (Global Finite Element Model) classically used for aircraft structure sizing. Therefore, pre-sizing involves the use of a wrinkling model, which can be found in the literature. In practice, such models are used with high safety factors by the industry. This paper proposes an evaluation of analytical wrinkling formulas in an industrial setting. Realistic applications involve a framework (3D stress state, orthotropy, skin asymmetry) far from the assumptions on which most of the analytical formulations are based. The case study is a sandwich composite beam subjected to uni-axial compressive load. Limitations and assumptions of the analytical wrinkling models studied are quantified and a discussion on the relevance of using simple formulas for the design of sandwich structured composites is developed.

We consider the problem of jointly estimating the location and scatter matrix of a Compound Gaussian distribution with unknown deterministic texture parameters. When the location is known, the Maximum Likelihood Estimator (MLE) of the scatter matrix corresponds to Tyler’s M-estimator, which can be computed using fixed point iterations. However, when the location is unknown, the joint estimation problem remains challenging since the associated standard fixed-point procedure to evaluate the solution may often diverge. In this paper, we propose a stable algorithm based on Riemannian optimization for this problem. Finally, numerical simulations show the good performance and usefulness of the proposed algorithm.

International audience; In this article, the active vibration control of a smart structure made out of a single functionally graded piezoelectric material layer, equipped with a network of discrete electrodes, is studied. The material properties vary continuously across the direction of thickness, so that top and bottom surfaces consist of pure PZT4 and the mid surface is composed of pure aluminium. The percolation phenomenon is taken into account. A functionally graded piezoelectric material plate finite element based on the first-order shear deformation theory hypothesis and layer-wise approximation for electric potential is implemented. An optimization procedure is considered to define the relevant electrodes for actuators and sensors, based on controllable and observable criteria. An adaptative fuzzy controller system is used, activating with relevance the actuators according to the most excited eigenmodes. Simulations show the effectiveness of this kind of concept.

Hypothesis: The setting time and mechanical properties of cements are a major technical concern for a long time in civil engineering. More recently those practical problems became a major concern for biomedical applications -in bone surgery and in dentistry- in particular concerning the setting time which should be minimized. The possibility to add organic additives to interact with the different constituting ions in cements constitutes a way to modify the setting kinetics. We made the assumption that a hydrolysable polyphenol like tannic acid could modify the setting time and the physical properties of Mineral Trioxide Aggregate (MTA). Experiments: Tannic acid is added in variable proportions to the water used to set MTA. The formation of the hybrid organic-mineral cements is investigated using a combination of structural, chemical and mechanical methods. X-ray tomography was also used to investigate the changes in porosity and pore size distribution upon incorporation of tannic acid in MTA based cements. The hydrophilicity of the cements was evaluated by measuring the permeation kinetics of small water droplets. Findings: We found that tannic acid allowed to reduce markedly the setting time of MTA based cements. The obtained cements have an increased hydrophilicity and display excellent resistance to compression. The number of pores but not the average pore size is also affected. The possible roles of tannic acid in modifying the cement properties are discussed. Keywords: Mechanical properties; Mineral trioxide aggregate; Natural additives; Setting time; Tannic acid; X-ray tomography.

International audience; Many anticounterfeiting tags rely on images intricate in different color and/or different polarization states to create optical effects invisible in conventional observation conditions. We build here an imaging micropolarimeter based on the dual rotating compensator system and using the color capabilities of cameras to yield the full polarimetric information for any color coordinates in one acquisition step. After correction for the camera response, the full color image reconstructed from the polarimetric response is validated by the comparison with images obtained in an optical microscope fitted with polarizers.

In this paper, robust mean and covariance matrix estimation are considered in the context of mixed-effects models. Such models are widely used to analyze repeated measures data which arise in several signal processing applications that need to incorporate a same global individuals behavior with a possible individual variations. In this context, most algorithms are based on Gaussian assumption of the observations. Nevertheless, in certain situations in which there exist outliers within the data set, such assumption is not valid and leads to a dramatic performance loss. To overcome this drawback, we design an expectation-conditional maximization either algorithm in which the heterogeneous component is considered as part of the complete data. Then, the proposed algorithm is cast into a parallel scheme, w.r.t. the individuals, in order to alleviate the computational cost and a possible central processor overload. Finally, the proposed algorithm is extended to deal with missing data which refers to the situation where part of the individual responses are unobserved. Numerical simulations are performed in order to assess the performance of the proposed algorithm in regard to robust regression estimators, probabilistic principal component analysis and its recent robust version.

In this paper, we propose a novel scheme for direction of arrival estimation in the presence of a noise which is a combination of white Gaussian distributed noise and spherically invariant random distributed noise. Such combination arises in practical scenario, in which, the Gaussian component represents the thermal noise (i.e., the internal noise), whereas, the spherically invariant random process represents the possible presence of outliers and/or non-homogeneities of the environment (i.e., interference, clutter, jammers). The classical direction of arrival estimation using the maximum likelihood is computationally intractable. In order to overcome this drawback while maintaining a fine accuracy and taking into account the presence of the two noise components, we design an expectation-maximization algorithm. Finally, numerical simulations show that the proposed algorithm outperforms the state-of-the-art.

This work focuses on the free and forced vibrations of sandwich beams and plates hosting an arbitrary number of damping cores. A fractional derivatives Zener-type model is adopted for representing the frequency-dependent viscoelastic behaviour, along with conventional series developments. The structural models are formulated within an established variable kinematics approach, which enables to investigate the role of specific assumptions and to identify the most accurate model at a least number of degrees of freedom. Approximate solutions are found by a computationally efficient Ritz method that allows to take into account any type of boundary conditions. Modal loss factors and damped eigenfrequencies are obtained from a complex eigenvalue problem, for which a modal strain energy approach or a complex eigensolution can be employed. Frequency responses can be computed by a direct approach or by elementary modal projection algorithms. Results are reported for conventional and innovative sandwich configurations. Different modelling and solution strategies are compared and the role of transverse normal deformation of the mechanically weak viscoelastic plies is particularly emphasised.

The delayed damage model has been introduced by Allix and Deu [1] as a way to overcome spuriousmesh dependency in failure analysis involving damage and dynamic loading. The damage rate is boundedthrough a time scale which, combined with the wave speed, introduces implicitly a length scale. In this paper,the delayed damage model is analyzed through numerical experiments on three different loading cases of abar: a slow loading leading to a dynamic failure, pulses and impact. We observe and discuss the load levelneeded for failure (and the dependence of this load level with respect to the loading rate), as well as thedissipation and extent of the fully damaged zone at failure. Observations lead to the following conclusions.First, the delayed damage model has no regularization effect for a dynamic failure initiating from rest. Second,for pulse loadings, the loading rate has no influence on the minimal load level needed for failure (even thoughthe delayed damage model is a time-dependent model), and beyond this minimal load level for failure, theextent of the fully damage zone rises, proportionally to the length scale. Third, regarding the impact, thevelocity needed to reach failure depends only the time-independent parameters of the models, and not theones linked to the delayed damage.

International audience; Le travail présenté exploite une procédure de conception basée sur de la simulation afin de créer une métasurface éparse conforme pour la réduction de la diffraction d’un cylindre métallique, lorsque celui-ci est illuminé par une onde plane.

Biodiversity is one of the global issues that explicitly responds to the notion of sustainable development. It is an explicit concern for human needs, for which it constitutes living natural resources found in nature. The fundamental concept of biodiversity is introduced by studying the spatial distribution of species and, more specifically, the well-known Species Area Relationship (SAR). Knowing the zone-species law that truly manages the phenomenon of spatial distribution of species enables us to predict the response of biodiversity to environmental changes at different scales and to assess policy options for global biodiversity conservation. Indeed, within the framework of this thesis, we propose a new approach to the phenomenon of spatial distribution of species and individuals by using the same tools and physical properties that the ones commonly used to treat statistical and geometrical dynamics of developed turbulence. For this purpose, we have adopted the dynamics of entropic skins E.S. describing the intermittence phenomenon in turbulence. The P.E. model was applied to experimental data on the spatial distribution of species through a geometry simulating the distribution of individuals in a form close to the two-dimensional Cantor geometry. We found that the distributions of species and individuals are well described by the E.S. model. Both spatial distributions show intermittent dynamics with a hierarchy of entropic skins extending between a parabolic fractal body (corresponding to the spatial extension of the less ordered plant population) and a pure fractal crest (corresponding to the metabolically active and ordered areas). Intermittence statistics can thus occur in phenomena other than turbulence., La biodiversité est un des enjeux internationaux qui répond explicitement à la notion du développement durable. C’est un intérêt explicite pour les besoins humains qui constitue des ressources naturelles vivantes se trouvant dans la nature. La biodiversité dans son concept fondamental est introduite par l’étude de la distribution spatiale des espèces et plus précisément la relation bien connue zone-espèces (Species Area Relationship ; SAR). La connaissance de la loi zones-espèces qui gère véritablement le phénomène de distribution spatiale des espèces nous permet de prédire la réponse de la biodiversité aux changements environnementaux à différentes échelles et d’évaluer les options politiques de conservation globale de la biodiversité. En effet, dans le cadre de cette thèse, nous proposons une nouvelle approche du phénomène de distribution spatiale des espèces et des individus en utilisant les mêmes outils et propriétés physiques que pour traiter la dynamique statistique et géométrique caractérisant le phénomène de turbulence développée. Dans ce sens, nous avons adopté la dynamique de peaux entropiques P.E décrivant le phénomène d’intermittence en turbulence. ce modèle a été appliqué sur des données expérimentales de distributions spatiales d’espèces en utilisant une géométrie simulant la distribution des individus sous une forme se rapprochant de la géométrie du Cantor à deux dimensions. Les résultats montrent que la répartition des espèces et des individus est bien décrite par le modèle des P.E. Ces deux distributions spatiales montrent une dynamique intermittente possédant une hiérarchie de peaux entropiques qui s’étend entre, un corps fractal parabolique et une crête fractale pure. On voit ainsi que les statistiques d'intermittence peuvent se produire dans des phénomènes autres que la turbulence.

International audience; This paper addresses structured scatter matrix estimation within the non convex set of Kronecker product structure. The latter model usually involves two matrices , which can be themselves linearly constrained, and arises in many applications, such as MIMO communication , MEG/EEG data analysis. Taking this prior knowledge into account generally improves estimation accuracy. In the framework of robust estimation, the t-distribution is particularly suited to model heavy-tailed data. In this context, we introduce an estimator of the scatter matrix, having a Kronecker product structure and potential linear structured factors. In addition, we show that the proposed method yields a consistent and efficient estimate.

In this work, a multi-resolution strategy is developed to solve unsteady diffusion problems with arbitrary heat source location. It is based on a variable separation approach which allows us to compute an explicit solution with respect to the heat source location and also to reuse an initial basis for new configurations. Thus, the change of sets of parameters (type of heat source, number of layers ...) does not imply the resolution of the complete thermal problem for each time step, but it is reduced to update 1D functions. For this purpose, the temperature is written as a sum of separated functions of the axial coordinate x , the transverse coordinate z , the time t and the volumetric heat source location x s . The derived non-linear problem implies an iterative process in which four 1D problems are solved successively at each iteration. In the thickness direction, a fourth-order expansion in each layer is considered. For the axial description, classical Finite Element method is used. The presented approach is assessed on various laminated beams under different loadings and comparisons with reference solutions with a fixed heat source location are proposed. These test cases show the possibilities and the accuracy of the method.

International audience; This paper proposes a new strategy based on the proper generalized decomposition method to solve the forced vibration problem for bi-dimensional piezoelectric composite beams. The approach considers a classical harmonic space-frequency description of the dynamic problem and redefines it by approximating the displacement and electric potential fields as a sum of separated functions of x (beam axis coordinate), z (thickness coordinate) and (load frequency). The methodology consists in an iterative algorithm that solves three one-dimensional linear problems at each iteration. The result is a 2D solution in frequency domain with 1D computational complexity. Several numerical tests with wide range of slenderness ratios are considered in order to assess the validity of the method. Moreover, a study of different combinations of boundary conditions is carried out. The results in terms of modal parameters and frequency response functions are analysed and compared with exact elasticity solution and finite element simulations.

The thermochemical models used today are capable of restituting experimental data of the states of stationary detonations and explosions in closed volume for CxHyOzNtAlu compositions, with a deviation from experiment of a few percent. The validation work has not yet been carried out on explosives containing aluminum particles, which oxidize in the detonation products. The thesis project is part of the development of the thermochemistry code SIAME (Aero-Thermochemical Simulation of Explosive Mechanics), for the benefit of the French General Directorate of Armaments. The objective is to study the thermochemical states of the alumina produced during the deflagration of gas-aluminium particles mixtures, in order to compare them with SIAME. It is then necessary to determine the temperature, pressure and volume fraction of alumina produced by combustion of aluminum particles for different mixtures. The different thermodynamic properties are determined by spectroscopy and by the measurements of a piezoelectric sensor. The work was focused on the improvement of an experimental setup developed at the Laboratory of Energetics, Mechanics and Electromagnetism (Paris Nanterre University), in order to conduct measurements during a deflagration. The analysis provided a better understanding of the physical phenomena involved during the deflagration and during the cooling phase, which is necessary to correctly evaluate the measured radiations for the study of alumina. After a study of the possible spectral zones to characterize alumina, an experimental campaign was conducted. The results are evaluated to determine the state of alumina from the measured radiation, by using an inversion model., Les modèles thermochimiques utilisés aujourd'hui permettent de restituer des données expérimentales des états de détonation stationnaire et d'explosion en volume clos d'explosifs de composition CxHyOzNt avec un écart à l'expérience de quelques pourcents. Le travail de validation n'a pas encore été mené sur des explosifs contenant des particules d'aluminium, qui s'oxydent dans la détente des produits de détonation. Le projet de thèse s'inscrit dans le cadre du développement du logiciel de thermochimie SIAME (Simulation Aéro-thermochimique de la Mécanique des Explosifs), au profit de la Direction Générale de l'Armement. L’objectif est d’étudier les états thermochimiques de l’alumine produit lors de la déflagration de compositions gazeuses contenant des particules d’aluminium, afin de les comparer avec SIAME. Il est alors nécessaire de déterminer la température, la pression et la fraction volumique de l'alumine produit par combustion des particules d'aluminium. Les propriétés thermodynamiques sont déterminées par spectroscopie et par les mesures d’un capteur piézoélectrique. Le travail a été orienté sur l’amélioration d’un banc expérimental au Laboratoire Energétique, Mécanique et Electromagnétisme (Université Paris Nanterre), pour effectuer des mesures lors d'une déflagration. Les analyses ont permis d’approfondir la compréhension des phénomènes physiques mis en jeu pendant la déflagration et au cours du refroidissement, ce qui est nécessaire pour exploiter correctement les rayonnements mesurés pour l’étude de l’alumine. Après une étude des zones spectrale possibles pour caractériser l’alumine, une campagne expérimentale a été menée. Les résultats sont évalués pour déterminer l’état de l’alumine à partir du rayonnement mesuré, par l’utilisation d’un modèle d’inversion.

International audience; To study detonation products of condensed matter in the post-combustion phase, a preliminary work is carried out on deflagrations. The study of the radiative properties of molecules during this fast phenomenon is not simple in the mid-infrared range. As the flame front of a H 2 /O 2 /N 2 /CO 2 gas mixtures spreads in a few tens of meters per second, a fast infrared detection system is required. Besides, there are no calibrating sources in that spectral range for the intensity and spectral position calibration. The important feature of the experimental setup presented is the record of high-resolution spectra at high frequency, up to 10 kHz. The setup is composed of a deflagration chamber with optical accesses. The pressure evolution is measured by a high speed piezoelectric sensor. The ignition is synchronized with the camera trigger. The radiation is focused into a monochromator and at its exit slit, a camera records the spectra in real time. The spectral intensity is calibrated using a blackbody. The correspondence between the spatial position of a pixel and the wavelength is fitted using an original method based on the application of a third degree polynomial, taking into account optical aberrations. The resulting spectra can be used to determine the temperature and the emissivity of gases.

International audience; Traditionally, equiaxed alpha grains rather than lamellar microstructure (LM) domains in titanium alloys are regarded as potential internal crack origins in high-cycle fatigue (HCF) and very-high-cycle fatigue (VHCF) re-gimes. Here, we found that the fatigue crack is prone to initiate from a large LM domain in a titanium alloy with the composition of LM and equiaxed microstructure (EM) of fine alpha grains. Then, the mechanisms of internal crack initiation and early growth for the cases of HCF and VHCF under stress ratio R =-1, 0.1 and 0.5 were addressed and a mechanism chart was constructed to illustrate the internal cracking behavior, especially showing that the numerous cyclic pressing process dominates the related microstructure evolution with grain size refinement and nanograin formation underneath the fracture surfaces in the region of crack initiation and early growth.

International audience

The common thread of this work has been the safety problems of energy installations, whether they are nuclear, such as the fast neutron channel that uses sodium as a heat transfer fluid, or for hydrogen as a storage medium for renewable energies. An experimental and modelling study undertaken with CEA Cadarache first focused on understanding the poorly understood mechanism of the sodium-water reaction based on the determination of temperature and concentration fields in the immersion of a sodium ball in a volume of water. We have shown that the reaction kinetics characterized by a fairly long latency time, which we have modeled, progresses like the vapour pressure of solid and then liquid sodium until it reaches 250°C, where disintegration occurs and then the explosion, which may be of the Coulomb type. The temperature of the effluent then peaks at 1400°C. In a second part we used the developments we had previously made in the remote sensing of hydrogen by the Raman effect. The remote detection of this odorless and colorless gas is one of the conditions for the development of hydrogen, the "fuel of the future". With the picosecond laser used, and although the Raman effect is particularly weak, we can determine the concentration of a leak and also what is original the temperature of a flame at distances up to a hundred meters., Le fil conducteur de ce travail a porté sur les problèmes de sécurité des installations énergétiques qu’elles soient nucléaires comme la filière neutrons rapides qui utilise le sodium comme fluide caloporteur ou pour l’hydrogène comme moyen de stockage des énergies renouvelables. On s’est d’abord intéressé dans le cadre d’une étude expérimentale et de modélisation entreprise avec le CEA Cadarache à comprendre le mécanisme mal connu de la réaction sodium-eau à partir de la détermination des champs de température et de concentration dans l’immersion dans un volume d’eau d’une boule de sodium. Les gaz dégagés sont la vapeur d’eau, la vapeur de sodium, l’hydrogène et le radical OH° .Nous avons montré que la cinétique de réaction caractérisée par un temps assez long de latence que nous avons modélisé, progresse comme la pression de vapeur du sodium solide puis liquide jusqu’à atteindre 250°C où se produit une désagrégation puis l’explosion qui est peut-être du type de Coulomb. La température des effluents plafonne alors à 1400°C. Dans une deuxième partie nous avons utilisé les développements que nous avions faits précédemment à la télédétection par effet Raman de l’hydrogène. La télédétection de ce gaz inodore et incolore est une des conditions au développement de l’hydrogène « combustible du futur ». Avec le laser picoseconde utilisé, et bien que l’effet Raman soit particulièrement faible, nous pouvons déterminer la concentration d’une fuite et aussi ce qui est original la température d’une flamme à des distances atteignant la centaine de mètres.

International audience; The last decade was marked by the advent of the concepts of phase gradient and Huygens' meta-surfaces which simple theoretical models have been leading the research on metasurfaces ever since. Meanwhile, theoretical modelling of non-planar metasurfaces have appeared to be exceptionally challenging where it demands accurate analysis of the metasurface geometry. The present work addresses this challenge with a radically different theoretical approach demonstrating how numerical calculation of Green's function can be employed to design conformal metasurfaces of arbitrary geometries within the same framework and without any accommodation. Against the classical concepts , the new approach permits building a metasurface of meta-atoms with electric-only response and significantly simplifying its design and fabrication. The theory is endorsed experimentally by testing several metasurface prototypes for different beam-forming functionalities: radiation with single or multiple beams in any desired directions.

The blind source separation problem is considered through the approach based on non-stationarity and coloration. In both cases, the sources are usually assumed to be Gaussian. In this paper, we extend previous works in order to handle sources drawn from the multivariate Student t-distribution. After studying the structure of the parameter manifold in this case, a new blind source separation criterion based on the log-likelihood of the considered distribution is proposed. To solve the resulting optimization problem, Riemannian optimization on the parameter manifold is leveraged. Practical expressions of the mathematical tools required by first order based Riemmanian optimization methods for this parameter manifold are derived to this end. The performance of the proposed method is illustrated on simulated data.

International audience; Metasurfaces present high capabilities for wavefront tailoring. Classical metasurfaces composed of densely packed meta-atoms with local electromagnetic response show limitations in terms of efficiency. Here, we present and discuss the design of sparse metasurfaces composed of only few elements with strong electromagnetic non-locality. Sparse metasurfaces of arbitrary geometry are designed and validated at microwave frequencies for antenna applications.

International audience; This paper derives a new change detector for multivariate Synthetic Aperture Radar image time series. Classical statistical change detection methodologies based on covariance matrix analysis are usually built upon the Gaussian assumption, as well as an unstructured signal model. Both of these hypotheses may be inaccurate for high-dimension/resolution images, where the noise can be heterogeneous (non-Gaussian) and where the relevant signals usually lie in a low dimensional subspace (low-rank structure). These two issues are tackled by proposing a new Generalized Likelihood Ratio Test based on a robust (compound Gaussian) low-rank (structured covariance matrix) model. The interest of the proposed detector is assessed on two Synthetic Aperture Radar Image Time Series data set from UAVSAR.

International audience; The estimation of covariance matrices is a core problem in many modern adaptive signal processing applications. For matrix-and array-valued data, e.g., MIMO communication, EEG/MEG (time versus channel), the covariance matrix of vectorized data may belong to the non-convex set of Kronecker product structure. In addition, the Kronecker factors can also exhibit an additional linear structure. Taking this prior knowledge into account during the estimation process drastically reduces the amount of unknown parameters, and then improves the estimation accuracy. On the other hand, the broad class of complex elliptically symmetric distributions, as well as the related complex angular elliptical distribution, are particularly suited to model heavy-tailed multivariate data. In this context, we first establish novel robust estimators of scatter and shape matrices (both related to a covariance matrix), having a Kronecker product structure with linearly structured Kronecker factors. Then, we conduct a theoretical analysis of their asymptotic performance (i.e., consistency, asymptotic distribution and efficiency), in matched and mismatched scenarios, i.e., when misspecifications between the true and assumed models occur. Finally, numerical results illustrate the theoretical analysis and assess the usefulness of the proposed estimators.

International audience; This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a low-rank plus identity structure. The considered geometry is the one induced by the product of the Stiefel manifold and the manifold of Hermitian positive definite matrices, quotiented by the unitary group. One of the main contribution is to consider an original Riemannian metric, leading to new representations of tangent spaces and geodesics. From this geometry, we derive a new Riemannian optimization framework for robust covariance estimation, which is leveraged to minimize the popular Tyler's cost function on the considered quotient manifold. We also obtain a new divergence function, which is exploited to define a geometrical error measure on the quotient, and the corresponding intrinsic Cramér-Rao lower bound is derived. Thanks to the structure of the chosen parametrization, we further consider the subspace estimation error on the Grassmann manifold and provide its intrinsic Cramér-Rao lower bound. Our theoretical results are illustrated on some numerical experiments, showing the interest of the proposed optimization framework and that performance bounds can be reached.

International audience; A numerical model to take into account the effect of the stress state on the bond behavior between steel and concrete in reinforced concrete structures is proposed. It is based on a zero thickness element, adapted to large-scale simulations and the use of 1D elements for steel bars. The proposed model also assumes the definition of a bond stress – slip law which includes the confining pressure around the steel bar as a parameter. The implementation of the model is presented and the calibration of the bond law is discussed. A general equation is especially proposed. This evolution law is validated through the comparison to 28 pullout tests. The model is able to reproduce the evolution of the bond stress (especially the bond strength) as a function of the confinement pressure, whatever the configuration (different concrete cover to steel diameter ratios). Finally, the effects at the structural level are investigated on a reinforced concrete tie. The response for different confining pressures is especially studied. It shows the capability of the model to reproduce the “expected” tendencies with an increase of the initial elastic stiffness with increasing pressures and consequently a higher number of cracks in the stabilized nonlinear regime. The “transfer length” is also shown to decrease with increasing confining pressures.

The aim of this study was to compare the physicochemical properties, filling ability, and antibacterial activity of a premixed calcium silicate-based sealer to those of a powder&ndash, liquid bioceramic sealer. Ceraseal (CS) and BioRoot (BR) materials were analyzed using scanning electron microscopy and energy-dispersive X-ray spectroscopy at 7 and 14 d of immersion in distilled water. The filling ability of the two sealers as well as the water contact angle, solubility, flow, roughness, crystalline microstructure, pH, and compressive strength were also evaluated. The antibacterial activity was assessed through an agar diffusion as well as through direct tests. All the results were statistically analyzed using one-way or two-way analysis of variance tests. Statistically significant lower void percentages were observed for CS at 2 and 8 mm from the working length (WL) compared to those for the BR group, whilst no significant difference was observed at 5 mm from the WL. BR sealer showed higher alkaline pH, rougher surface, lower water contact angle values, lower flowability, and higher solubility compared to CS. BR showed globular and needle-like crystalline microstructure, whilst CS had globular and flower-like crystalline microstructure up to 72 h. No statistical difference was found for the compressive strength between the two sealers. BR and CS showed no antibacterial effect against Enterococcus faecalis after 3 h, whilst both sealers showed antibacterial capacity after 24 and 72 h. BR demonstrated higher antibacterial activity after 24 h. In conclusion, the use of bioceramic sealers may play an important role in controlling bacterial growth. Moreover, CS may have superior filling ability and lower solubility than the BioRoot sealer due to its specific chemical composition and mixing method.

In this work, we investigate direction nding in the presence of sensor gain uncertainties and directional perturbations for sensor array processing in a multi-frequency scenario. Specically, we adopt a distributed optimization scheme in which coherence models are incorporated and local agents exchange information only between connected nodes in the network, i.e., without a fusion center. Numerical simulations highlight the advantages of the proposed parallel iterative technique in terms of statistical and computational eciency.

International audience; This paper provides an original asymptotic analysis of robust adaptive detectors performance in the context of non-Gaussian observations. We focus on a single-steering case in homogeneous environment and analyze the properties of different adaptive detectors such as Adaptive (Normalized) Matched Filter (AMF/ANMF), Kelly's GLRT, and Rao test when an estimator of the co-variance matrix is plugged in. When the noise distribution turns to be non-Gaussian, the detectors relying on the Sample Covariance Matrix (SCM) can perform poorly and an interesting alternative is the use of M-estimators. In this context, we show that, from Complex Elliptically Symmetric (CES) samples, the distribution of a detection statistic built with M-estimators can be accurately approximated by the one of the same statistic built from the SCM of an equivalent Gaussian setting. The loss due to this approximation is theoretically derived and shown to be negligible in most cases. This explicit equivalent statistic is especially interesting since it allows to tune robust plug-in detectors with well established results from the Gaussian detection framework. Furthermore, this approach provides new insights on the robust estimation tools behavior. Finally, some simulations illustrate the interest of the proposed results.

This brief introduces an innovative unidimensional thermal propagation modeling. It consists in thermal diffusion on conductor bulk structure based on the Kron–Branin (KB) formalism. The proposed KB model is inspired from the transmission line approach by considering the bulk material thermal resistance and capacitance. The KB-based equivalent graph topology of the heated structure is elaborated. The thermal transfer function (TTF) is established from the graph analytical abstraction. The TTF enables to determine the transient and frequency-dependent temperature diffusion along the structure. The KB model effectiveness is illustrated with both frequency and time-domain analyses. Proof-of-concept constituted by copper-based bulk material is considered. The TTF from KB, finite-element-method and Cauer models are compared. With computation from dc to 100 Hz, it was shown that the frequency domain magnitude and phase are in good correction. In addition, the calculated and simulated transient heat flows along the considered structure are in good agreement by considering 120-ms duration pulse width temperature source.

International audience; The reaction of sodium metal with liquid water is a heterogeneous, exothermic reaction known to be prone to runaway with explosive effects when uncontrolled. The occurrence of runaways requires the reactants to be effectively mixed which is not the case initially for sodium and water. The latter are put in contact in two distinct, condensed phases, that are moreover rapidly separated by a gaseous film generated by the reaction itself. The runaway is triggered by a reactant mixing process that is not elucidated. This mixing could occur either in liquid or gas-phase. In this paper, we investigate the mixing process of sodium-water reaction in the small scale configuration of 1–4 g sodium pellets with excess water in a closed vessel, using time-resolved video, optical, pressure and temperature acquisitions. The results show that sodium vaporization is implicated in the reaction and that it is generated in great quantity during runaway. However it appears from temperature measurements that boiling temperature is not reached in the sodium before runaway or only locally. It is therefore possible that reactant mixing occurs in the gas phase if an intensification of sodium vaporization takes place as a fast local transient. The possibility of reactant mixing in liquid phase is not contradicted by these results but was not identified from the available videos and data.

Este artículo se encuentra disponible en la siguiente URL: https://www.mdpi.com/2306-5354/9/3/85 Este artículo de investigación pertenece al número especial "Recent Advances in Biomaterials and Dental Disease". En este artículo de investigación también participan: Frédéric Addiego, Christine Affolter-Zbaraszczuk, Youri Arntz, Vincent Ball, Florent Meyer, Youssef Haikel y Davide Mancino. This study aimed at evaluating the physicochemical and biological properties of experimental epoxy-resin sealers containing polyphenols such as resveratrol and pyrogallol. A conventional epoxy resin (OB) was modified by adding different concentrations of resveratrol (RS) or pyrogallol (PY) to its composition. Antibacterial and antioxidant activities, mechanical properties, along with wettability and morphological changes were investigated. The results were statistically analyzed using ANOVA and multiple comparison tests ( = 0.05). The incorporation of the tested polyphenols into the epoxy resin enhanced its mechanical properties. PY demonstrated much better antioxidant and antibacterial activities than RS, which were associated with a higher release of PY. In contrast, PY showed a higher cytotoxicity than OB and OB doped with RS. OB containing PY presented a rougher surface and higher water absorption than OB doped with RS. Both tested polyphenols caused no notable changes to the overall porosity of OB. Resveratrol and pyrogallol may not only influence the morphology and mechanical properties of epoxy-resin sealers, but could also enhance antioxidant activity and antibacterial effects against Enterococcus faecalis. Most epoxy-resin sealers currently available in the market can be considered as “passive” materials. Thus, doping their composition with specific polyphenols may be a suitable strategy to confer some antibacterial properties, antioxidant potential, along with improvement of some mechanical properties.

International audience; Anticounterfeiting technologies rely on visual effects that are specific to particular structures and concealed to the unwary observer. Plasmonic nanostructures are one solution to these two requirements, and besides colored effects, the possibility to design covert images in a particular polarization state of light is particularly appealing. The generation of circular polarization provides a new degree of freedom, and the use of pseudochiral plasmonic resonators hosting magnetoelectric resonances allows tailoring opposite handedness of circular polarization within the same nanostructure. In this work, we have defined a palette of luminance observable only in circular dichroism by engineering the shapes and positions of the resonators. The spatial control of the polarization state of light is highlighted by realizing a micrometer-scale image revealed only in circular polarization with an additional contrast reversal associated with circular dichroism reversal.