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Etude du vieillissement hygrothermique des matériaux composites thermoplastiques utilisés pour la fabrication des réservoirs d’hydrogène de type V
No full textIn the context of the development of Type V hydrogen storage tanks, the durability of thermoplastic composites constitutes a major safety concern. This thesis focuses on the hygrothermal aging of a composite comprising a semi-aromatic polyamide (PPA) matrix reinforced with carbon fibers (CF), whose sensitivity to moisture may compromise long-term performance. The primary objective is to develop a fundamental, multi-scale understanding of the degradation mechanisms, adopting a twofold approach: first, the pure PPA matrix is characterized to establish a reference behavior; second, the composite is analyzed to isolate and quantify the roles of reinforcement and the fiber/matrix interface. To this end, the materials were subjected to accelerated aging by immersion in water at various temperatures (25–90 °C). A multi-scale characterization campaign was carried out, combining water absorption analyses (gravimetry and dynamic vapor sorption), physico-chemical techniques (differential scanning calorimetry, dynamic mechanical analysis, gel permeation chromatography), and mechanical testing (monotonic and cyclic tensile tests) coupled with microstructural observations via scanning electron microscopy. A primary result is the excellent chemical stability of the PPA matrix, whose aging was found to be purely physical, governed by a competition between water-induced plasticization and high-temperature recrystallization. Within the composite, a second key finding demonstrates that carbon fibers inhibit recrystallization, thereby preventing matrix embrittlement. Consequently, the dominant degradation mechanism shifts to the weakening of the fiber/matrix interface, which also acts as a preferential diffusion pathway for water. The principal contribution of this thesis lies in deconvolving these aging mechanisms and identifying the pivotal role of reinforcement-induced recrystallization inhibition—a phenomenon that preserves the composite’s ductility. Despite the earlier onset of interfacial damage, the composite maintains good damage tolerance. These findings provide an essential knowledge base for the qualification of these materials and the development of predictive lifetime models for hydrogen storage tanks.Dans le contexte du développement des réservoirs à hydrogène de type V, la durabilité des composites thermoplastiques est un enjeu de sécurité majeur. Cette thèse se concentre sur le vieillissement hygrothermique d'un composite à matrice polyamide semi-aromatique (PPA) et fibres de carbone (FC), dont la sensibilité à l'humidité peut altérer les performances à long terme. L'objectif principal est de développer une compréhension fondamentale et multi-échelle des mécanismes de dégradation. L'approche adoptée est double : étudier d'abord la matrice PPA pure afin d'établir un comportement de référence, puis analyser le composite pour isoler et quantifier le rôle du renfort et de l'interface fibre/matrice. Pour ce faire, les matériaux ont été soumis à un vieillissement accéléré par immersion en eau à différentes températures (25-90°C). Une caractérisation multi-échelle a été menée, combinant des analyses d'absorption d'eau (gravimétrie, DVS), physico-chimiques (DSC, DMA, GPC) et des essais mécaniques (traction monotone et cyclique) couplés à des observations microstructurales (MEB). Un résultat majeur est l'excellente stabilité chimique de la matrice PPA, dont le vieillissement s'est avéré être purement physique. Ce dernier est gouverné par une compétition entre la plastification par l'eau et une recristallisation à haute température. Au sein du composite, un second résultat clé montre que les fibres de carbone inhibent cette recristallisation, empêchant ainsi la fragilisation de la matrice. Le mécanisme de dégradation prépondérant devient alors l'affaiblissement de l'interface fibre/matrice, qui agit également comme un chemin de diffusion préférentiel pour l'eau. L'apport principal de cette thèse est d'avoir déconvolué ces mécanismes de vieillissement et identifié le rôle pivot de l'inhibition de la recristallisation par le renfort, un phénomène qui préserve la ductilité du composite. Malgré une initiation plus précoce de l'endommagement interfacial, le composite conserve une bonne tolérance aux dommages. Ces résultats constituent une base de connaissances essentielle pour la qualification de ces matériaux et le développement de modèles prédictifs de durée de vie pour les réservoirs à hydrogène
Different kinematic strategies are adopted by AIS patients during walking depending on Lenke type
No full textInternational audienceIntroductionAdolescent Idiopathic Scoliosis (AIS) is classically evaluated through static X-rays and health-related quality of life questionnaires that do not reflect the functional limitations of patients during daily life activities, such as walking. The aim was to investigate kinematic strategies in non-operated AIS with different types of curvature during walking using 3D gait analysis.Methods13 AIS with Lenke 5 (major Cobb: 23 ± 8°), 30 AIS with Lenke 1 (major Cobb: 40 ± 14°) in addition to 24 controls underwent biplanar X-rays followed by 3D gait analysis. The kinematic parameters of the head, trunk, spinal segments, pelvis and lower limbs were compared between groups.ResultsAIS Lenke 5 had a lumbar segment bending while walking (T12L3-L3L5: 5 ± 7° vs. -3 ± 7° in controls) to the concave side of the scoliosis. They walked with an increased pelvic frontal mobility (12 ± 3° vs. 9 ± 3°) and internal rotation of the right foot (-2 ± 6° vs. -11 ± 8°; all p < 0.05). AIS Lenke 1 increased their thoracic & lumbar segment bending to the concave and to the opposite side respectively (T6T9-T9T12: -4 ± 9° vs. 1 ± 4°; T12L3-L3L5: 8 ± 12° vs. -2 ± 7°). However, they tended to reduce their lumbo-pelvic mobility (7 ± 5° vs. 12 ± 5°; all p < 0.05).ConclusionIn response to their inherent lumbar stiffness and bending, AIS Lenke 5 patients tended to increase their pelvic frontal mobility and to develop a homolateral internal foot rotation, ensuring a dynamic alignment during gait. AIS Lenke 1, by producing opposite bending movement at the thoracic and lumbar segments, tended to reduce their lumbo-pelvic mobility and ensure coronal dynamic alignment
Interpolations spatio-temporelles (4D) basées sur des Graph Neural Network Dynamiques (GNN-D) et applications au stockage géologique de déchets radioactifs
No full textA deep disposal center for radioactive waste, such as Andra's Cigéo project requires continuous, long-term monitoring. This is made possible by a multitude of sensors. However, due to the environmental constraints associated with storage (i.e. radioactivity, the mechanical convergence of galleries, etc.), this network of sensors is prone to degradation over time. Therefore, it is crucial to ensure the consistency of the data collected to guarantee effective monitoring of the center. This means not only identifying sensor failures but also replacing erroneous values with reliable predictions. Graph Neural Networks (GNNs) are suitable tools for these tasks, as they enable accurate representation of system physics and take into account the local topology of the sensor network. In our research, we use data from Andra's underground research laboratory. Specifically, we are using data from an experiment that involved heating a high-activity (HA) cell demonstrator using heating resistors. This setup simulated the heating of radioactive waste on an HA cell. By introducing synthetic errors into this dataset, we trained Graph Neural Networks (GNNs) that leverage both current and historical sensor responses to assess sensor integrity. Additionally, we trained GNNs to generate predictions that could replace the responses of failed sensors, starting from the moment of failure. These GNNs are based on a forward integration mechanism and have been assessed on fundamental thermal simulation problems to evaluate their efficiency and limitations. The architecture of each GNN has been optimized through hyperparameter analysis. Given the large number of variables involved, we proposed a novel method for optimizing GNN architecture based on rating systems. Finally, we compared the performance of the best GNNs with traditional machine learning methods to demonstrate their effectiveness.Un centre de stockage profond de déchêts radioactifs comme le projet Cigéo de l'Andra requiert une surveillance continue sur le long terme. Cette surveillance est possible grâce à une multitudes de capteurs. Cependant, en raison des contraintes environementales associées au stockage (radioactivité, convergence mécanique des galeries, etc.) ce réseau de capteurs est sujet à une dégradation au fil du temps. Il est alors crucial d'assurer la cohérence des données recueillies pour garantir la surveillance du centre. Pour ce faire, il faut non seulement identifier les défaillances de capteurs mais aussi remplacer les valeurs erronées par des prédictions cohérentes. Les Graph Neural Networks (GNN) sont des outils adaptés pour ces tâches car ils permettent de représenter précisément la physique du système et prennent en compte la topologie locale du réseau de capteurs. Dans nos travaux, nous utilisons des données issues du laboratoire de recherche souterrain de l'Andra. En particulier, celles d'une expérience de chauffe d'un démonstrateur de cellule haute-activité (HA) par des résistances chauffantes. Ce qui permet d'imiter la chauffe d'une alvéole HA par des déchêts radioactifs. En ajoutant des erreurs synthétiques à ces données, nous avons entrainé des GNN qui utilisent les réponses capteurs (présentes et passées) pour détecter les défaillances capteurs. A l'aide des mêmes données, nous avons entrainés des GNN effectuant une prédiction au niveau des capteurs défaillants, à partir de l'instant de la panne. Ces GNN se basent sur un mécanisme d'intégration temporelle et ont été étudiés sur des problèmes de simulation thermique élémentaires afin d'évaluer leur efficacité ainsi que leurs limites. L'architecture de chacun des GNN a été optimisée par le biais d'un analyse hyper-paramétrique. En raison du grand nombre de variables, nous avons proposé une nouvelle méthode d'optimisation de l'architecture des GNN basée sur les systèmes de classement. Enfin, nous avons comparé les meilleurs GNN à des méthodes d'apprentissage machine traditionnelles afin de prouver leur efficacité
Cost-effective multi-fidelity strategy for the optimization of high-Reynolds number turbine flows guided by LES
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Indicators Targeting the Retrieval of Polymers in EEE and Their Re-Integration into New Equipment
No full textInternational audienceThe definition of the recycling and recyclability rates used today relies too heavily on the mass of the recycled materials, to the disadvantage of less dense materials such as polymers. In order to help with this issue, two indices have been created to, respectively, evaluate the retrievability of materials in their end-of-life stage and their reintegrability in new equipment once they have been recycled. These two indices comprise four indicators each, which are themselves divided into 23 sub-indicators. The six formal mathematical principles of the construction of these entities are presented, along with the formulas used for their calculation. Then, a case study is presented: the data of an equipment from a French EEE and sports and leisure distributor have been collected, and all sub-indicators, indicators and indices have been calculated for this equipment, hence assessing the retrievability and reintegrability of its constitutive materials. In conclusion, the precise nature of the indicators and sub-indicators has allowed us to give eco-design recommendations on different aspects of the design process, such as the choice of materials, the mechanical connections and modularity of the product, and its insertion into the waste treatment chain
The Effect of Avatar Transparency on Collaboration in Shared Virtual Spaces
No full textInternational audienceIn shared virtual spaces, users tend to mimic real-world social behaviors, such as maintaining interpersonal distances and avoiding collisions. During remote collaboration, these behaviors can limit movement and positioning, despite users are not co-located. Prior work found that avatar transparency reduces users' positioning constraints induced by social behaviors, as long as social presence between collaborators. Our goal was to develop a system that enhances navigation freedom without significantly increasing social presence. We designed a transparency management system based on interpersonal distances and collision avoidance. A user study involving groups of three remote collaborators indicated that our system reduced the distances between users compared to fully opaque avatars without any significant difference in social presence
Physico-Chemical and Mechanical Properties of DC-Sputtered ZrO2 Coatings Prepared by Oblique Angle Deposition
No full textInternational audienceIn this study, a ZrO2 thin film was deposited onto a Ti6Al4V substrate using the Oblique Angle Deposition (OAD) technique. The influence of the substrate/Zr target an-gle (15°, 30°, 45°, and 60°) was investigated, with a fixed azimuthal orientation (Phi) of 180°. The primary objective of this work is to develop and characterize novel biocompatible coat-ings for hip prosthesis implants with a complex 3D spherical geometry. The OAD method enables thin film deposition on such geometries and enhances understanding of how the par-ticle incidence angle affects the surface morphology and microstructure of zirconium oxide (ZrO2) thin films. This study combines an experimental approach DC magnetron sputtering with a multi-scale numerical approach using Monte Carlo codes (SRIM, SIMTRA, and NASCAM). The structure, texture, and growth of the ZrO2 coatings were analyzed via X-ray diffraction (XRD), while microstructure and surface morphology were examined using scan-ning electron microscopy (SEM). Hardness and Young’s modulus were determined through nanoindentation testing. Results indicate that increasing the oblique angle leads to a decrease in hardness. Experimental and numerical findings complement each other, offering deeper insight into the deposition phenomena. SIMTRA simulations closely replicate experimental observations: a higher number of incident particles results in increased coating thickness. Additionally, the film thickness decreases with increasing substrate inclination angle. The microstructure of ZrO₂ thin films is strongly influenced by substrate orientation, and coated substrates demonstrate superior performance compared to their uncoated counterparts
Comparative analysis of dynamic balance descriptors in humanoids and humans during perturbed bipedal locomotion and fall
No full textInternational audienceThis study identifies a robust parameter for quantifying instability in general biped systems by comparing three mechanical stability descriptors: the distance between the center of mass to the minimal moment axis (d CoM-MMA ), the margin of stability (MoS), and whole-body angular momentum (WBAM) in both humans and humanoid biped robots. We analyzed these metrics during normal and perturbed walking, including robot falls, a dynamic whose observation is limited in human trials due to safety concerns. Our comparative analyses demonstrate that d CoM-MMA is more predictive of different levels of instability and shows a clearer distinction between fall and non-fall states, compared to MoS and WBAM. These findings were consistent for both humans and biped robots, regardless of gait variability or the type and intensity of the perturbation methods. These qualities highlight its potential use in unified stability analysis in both fields, offering insights that can inform the design of exoskeletons, fall monitoring systems, and other gait-assistive devices for aging populations
Experimental validation of electron correlation models in warm dense matter
No full textWe report X-ray Thomson scattering measurements of warm dense aluminium at densities 3.75-4.5 g/cm and a temperature of approximately 0.6 eV, performed at the HED-HiBEF instrument of the European XFEL using the DiPOLE-100X drive laser. By probing plasmon dispersion across momentum transfers = 0.99-2.57 Angstrom with high statistical fidelity, we directly test competing theories of electron dynamics under extreme conditions. Time-dependent density functional theory (TDDFT) reproduces both the observed plasmon energies and spectral shapes across the full range, whereas the random phase approximation (RPA) and static local-field-correction (LFC) models systematically overestimate the plasmon frequency, even for aluminium (a canonical uniform electron gas metal). Considering electron localisation around ions and the loss of crystalline symmetry due to liquid-state disorder, our measurements provide direct evidence that simple uniform electron gas models fail in warm dense matter and establish TDDFT as a reliable approach for electronic correlations in this regime
Isostructural Phase Transition of Fe<sub>2</sub>O<sub>3</sub> under Laser Shock Compression
No full textInternational audienceWe present in-situ x-ray diffraction and velocity measurements of FeO under laser shock compression at pressures between 38-116 GPa. None of the phases reported by static compression studies were observed. Instead, we observed an isostructural phase transition from -FeO to a new -FeO phase at a pressure of 50-62 GPa. The -FeO phase differs from -FeO by an 11% volume drop and a different unit cell compressibility. We further observed a two-wave structure in the velocity profile, which can be related to an intermediate regime where both and phases coexist. Density functional theory calculations with a Hubbard parameter indicate that the observed unit cell volume drop can be associated with a spin transition following a magnetic collapse