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Estimation of stresses in 1D structures via high resolution inverse wavenumber analysis
No full textEvaluation et contrôle non destructif; GAPSUS - Acoustique Physique, Sous-Marine et Ultra-SonoreNational audienceDe nombreuses applications industrielles, comme les procédés de fabrication additive, nécessitent le développement de méthodes d’évaluation des contraintes résiduelles. Dans ce cadre, l’utilisation des mesures de champ dynamique sur les structures contraintes permet la formulation de méthodes qui, par rapport aux méthodes actuelles (diffraction des rayons X, trou incrémental, ...) pourraient permettre une estimation in-situ et non-destructive du champ de contraintes. En particulier, la théorie de l’acousto-élasticité décrit la propagation d’une onde dans un milieu précontraint. Les équations de dispersion correspondantes peuvent être associées à une analyse en nombres d’onde appliquée à une mesure de champ pour remonter à la précontrainte via un problème inverse. Une preuve de concept de la mesure obtenue sur des fils polymères et métalliques tendus est présentée. Le dispositif expérimental se compose d’une lentille cylindrique permettant d’amplifier optiquement le déplacement transverse du fil résultant d’une sollicitation transitoire par un impacteur électro-magnétique. La réponse dynamique de la structure est obtenue par corrélation d’images numériques mesurées avec une caméra rapide (51200FPS). Après extraction du spectre de nombres d’ondes associé au signal spatio-temporel obtenu sur une large gamme de fréquences (10Hz à 10kHz), on montre qu’il est possible d’estimer, sans connaissance a priori des lois de comportement du matériau, à la fois la contrainte dans le fil et le module de Young du matériau constituant, avec des erreurs respectives de l’ordre de 2% et 3%
Effect of different cryogenic lubrication methods on machinability of Ti6Al4V
No full textInternational audienc
A high-order, fully well-balanced, unconditionally positivity-preserving finite volume framework for flood simulations
No full textInternational audienceIn this work, we present a high-order finite volume framework for the numerical simulation of shallow water flows. The method is designed to accurately capture complex dynamics inherent in shallow water systems, and it is particularly suited for real applications such as tsunami simulations. The arbitrarily high-order framework ensures accurate representation of flow behavior, crucial for simulating phenomena characterized by rapid changes and fine-scale features. Thanks to an ad-hoc reformulation in terms of production-destruction terms, the time integration ensures positivity preservation without any time-step restrictions, a vital attribute for physical consistency, especially in scenarios where negative water depth reconstructions could lead to unrealistic results. In order to introduce the preservation of general steady equilibria dictated by the underlying balance law, the high-order reconstruction and numerical flux are blended in a convex fashion with a well-balanced approximation, which is able to provide exact preservation of both static and moving equilibria for pseudo-monodimensional states as well as for general 2D water at rest solutions. Through numerical experiments, we demonstrate the effectiveness and robustness of the proposed approach in capturing the intricate dynamics of shallow water flows, while preserving key physical properties essential for flood simulations
Enhancing Digital Continuity and Interoperability in Building Energy Management: A Digital Twin Approach with Large Language Models
No full textInternational audienceIn the field of building energy management, the heterogeneity of data arising from the coexistence of multiple standards and ontologies, such as Building Energy Management (BEM) and Building Management Systems (BMS), presents a critical obstacle to achieving efficient, interoperable, and continuous digital twins (DTs). These systems produce disparate and often semantically incompatible data, impeding seamless integration and hindering the realization of holistic energy management strategies. To overcome these challenges, advanced data structuring and AI-based strategies are imperative to ensure semantic interoperability and uninterrupted data continuity across heterogeneous systems. This paper introduces a novel approach for constructing a unified ontology that harmonizes BEM and BMS standards, enabling the seamless fusion of their datasets within a digital twin architecture. By leveraging the capabilities of Large Language Models (LLMs), we enrich the semantic structuring process, facilitating automated and precise reconciliation of heterogeneous data sources. Experimental results underscore the viability and efficacy of the proposed methodology in maintaining robust interoperability and ensuring digital continuity, thereby enhancing the operational efficiency of digital twins for smart building energy management
Impact des mécanismes d’usure des forets sur l’endommagement thermomécanique des empilages Ti6Al4V/CFRP
No full textThis thesis aims to improve the understanding of tool wear during the drilling of Ti6Al4V/CFRP stacks by analyzing its impact on thermomechanical loads and the defects generated in the machined assembly. The study highlights the effect of abrasive wear, caused by CFRP, on the tool’s micro-geometry, while considering operating parameters and cutting angles. It also examines how mechanical forces and additional heat fluxes evolve as wear progresses. Furthermore, it explores the formation of defects, such as burrs in Ti6Al4V and delamination in CFRP, by linking them to the thermomechanical forces measured at the drill exit. Finally, supercritical CO2 (scCO2) assistance is investigated as a promising solution to better control the thermal conditions during drilling and reduce these defects. These findings contribute to optimizing the drilling process and improving the quality of the stacks, with potential applications in aerospace.Cette thèse permet d’approfondir la compréhension des mécanismes d’usure des forets lors du perçage des empilages Ti6Al4V/CFRP, en analysant leur impact sur les chargements thermomécaniques et, par conséquent, sur les défauts générés dans l’assemblage usiné. L’étude met en évidence l’effet de l’usure abrasive, causée par le CFRP, sur la micro-géométrie de l’outil, tout en prenant en compte les paramètres opératoires et les angles de coupe. Elle s’intéresse ensuite à l’évolution des efforts mécaniques et des flux thermiques additionnels dues à l’usure. Ces travaux explorent également la formation de défauts, tels que la bavure dans le Ti6Al4V et le délaminage dans le CFRP, en les reliant aux efforts thermomécaniques mesurés en sortie de perçage. Enfin, l’assistance par CO2 supercritique (scCO2) est étudiée comme une solution prometteuse pour améliorer le régime thermique lors du perçage, afin de réduire ces défauts. Ces avancées ouvrent la voie à l’optimisation de l’opération de perçage et à l’amélioration de la qualité des empilages, avec des applications potentielles dans des secteurs tels que l’aéronautique
Machine learning-boosted nonlinear homogenization
No full textInternational audiencePrevious research has established nonlinear homogenization as an efficient technique for deriving macroscopic constitutive relations and field statistics in heterogeneous (i.e. composite) materials. This method involves optimal linearization of the nonlinear composite, resulting in a best linear comparison composite that shares identical microstructure and field statistics with the nonlinear material. However, the computational time associated with this method increases as the fidelity of the material representation improves, limiting its practical implementation in commercial finite element software for large-scale structural calculations in which a Representative Volume Element must be considered at each integration point. To overcome this limitation without sacrificing precision or efficiency, machine learning can be employed to develop a digital twin of the homogenization-based constitutive law. This approach enables real-time prediction of macroscopic material behavior while maintaining accuracy. The effectiveness of this approach has been demonstrated for two-phase composites with nonlinear power-law constitutive relations, and it has been successfully extended to model the complex three-dimensional behavior of viscoplastic polycrystals. In the latter case, a significant reduction in computational time has been achieved without compromising the precision of nonlinear homogenization method outputs
Comprehensive Review of Hybrid Energy Systems: Challenges, Applications, and Optimization Strategies
No full textInternational audienceThis paper provides a comprehensive review of hybrid energy systems (HESs), focusing on their challenges, optimization techniques, and control strategies to enhance performance, reliability, and sustainability across various applications, such as microgrids (MGs), commercial buildings, healthcare facilities, and cruise ships. The integration of renewable energy sources (RESs), including solar photovoltaics (PVs), with enabling technologies such as fuel cells (FCs), batteries (BTs), and energy storage systems (ESSs) plays a critical role in improving energy management, reducing emissions, and increasing economic viability. This review highlights advancements in multi-objective optimization techniques, real-time energy management, and sophisticated control strategies that have significantly contributed to reducing fuel consumption, operational costs, and environmental impact. However, key challenges remain, including the scalability of optimization techniques, sensitivity to system parameter variations, and limited incorporation of user behavior, grid dynamics, and life cycle carbon emissions. The review underlines the need for robust, adaptable control strategies capable of accommodating rapidly changing energy environments, as well as the importance of life cycle assessments to ensure the long-term sustainability of RES technologies. Future research directions emphasize the integration of variable RESs, advanced scheduling, and the application of emerging technologies such as artificial intelligence and blockchain to improve system resilience and efficiency. This paper introduces a novel classification framework, distinct from existing taxonomies, addressing gaps in prior reviews by incorporating emerging technologies and focusing on the dynamic nature of energy management in hybrid systems. It also advocates for bridging the gap between theoretical advancements and real-world implementation to promote the development of more sustainable and reliable HESs
Evaluating Robustness of Deep Reinforcement Learning for Autonomous Surface Vehicle Control in Field Tests
No full textInternational audienceDespite significant advancements in Deep Reinforcement Learning (DRL) for Autonomous Surface Vehicles (ASVs), their robustness in real-world conditions, particularly under external disturbances, remains insufficiently explored. In this paper, we evaluate the resilience of a DRL-based agent designed to capture floating waste under various perturbations. We train the agent using domain randomization and evaluate its performance in real-world field tests, assessing its ability to handle unexpected disturbances such as asymmetric drag and an off-center payload. We assess the agent's performance under these perturbations in both simulation and real-world experiments, quantifying performance degradation and benchmarking it against an MPC baseline. Results indicate that the DRL agent performs reliably despite significant disturbances. Along with the open-source release of our implementation, we provide insights into effective training strategies, real-world challenges, and practical considerations for deploying DRLbased ASV controllers
Propagation of laser weak shock waves in a three-dimensional woven composite composite
No full textInternational audienceThe propagation of a laser-driven shock wave in an aeronautic composite material is investigated. The material, made of three-dimensional carbon fiber lattices embedded in an epoxy matrix, is heterogeneous and anisotropic, due to the intrinsic anisotropy of the carbon fibers and to the weaving process. The shock is generated by a 10 ns laser pulse, focused on the material surface. Its ablation results in an expanding plasma, which induces a shock wave in the material with a peak compression stress of a few GPa. Starting from an optical microscopy visualization of the weaving, a differentiation between resin and fibers and a segmentation of the fibers lead to an evaluation of the material's local elastic properties below the laser spot position. The shock propagation is simulated using a nonlinear source model, combined with a time domain finite difference discretization of the equations of linear elastodynamics with Lebedev's scheme adapted to the material anisotropy. The high frequency content of the signal, the material heterogeneity and anisotropy induce a complex propagation. A measurement campaign has been performed for several samples and repeated laser illuminations. Experimental data are statistically compared to the model outputs and discussed
Ex vivo mechanical properties of human thoracolumbar fascia and erector spinae aponeurosis under traction loading and shear wave elastography
No full textInternational audienceThe thoracolumbar fascia (TLF) and the erector spinae aponeurosis (ESA) play an important role in the biomechanics of the spine and could be a source of low back pain. Although the TLF and ESA are key structures in several musculoskeletal dysfunctions and in tissue engineering, there is still a lack of evidence in the literature to prove that they have different mechanical properties and roles when considered as a single tissue. Furthermore, no methods are currently available to study these structures in vivo. The objective of this study was to analyze the ex-vivo tensile properties TLF and ESA, and to test the potential of ultrasound shearwave elastography (SWE) to characterize these tissues. Hundred samples from N = 10 fresh-frozen human donors were studied. Shear wave speed (SWS) was measured in all samples with SWE, and their tensile properties were measured with mechanical testing. Results show that TLF is anisotropic, and more compliant than ESA. SWS was not significantly correlated to tensile moduli.These findings could potentially aid surgeons in their daily practices, assist engineers with in silico simulations, and support physiotherapists in musculoskeletal rehabilitation by enabling them to customize medical interventions for each specific patient and clinical condition. However, further research is necessary to further investigate the behavior in terms of time-dependent response and link between the tissue anisotropy and microstructural organization