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Numerical simulation of the oblique water impact of double curvature bodies involving suction and cavitation phenomena
No full textInternational audienceThe present study aims to assess the capability of a numerical method to model hydrodynamicimpacts representative of an aircraft ditching. The considered numerical method is based onthe Finite Element explicit solver Radioss and a Coupled Eulerian–Lagrangian approach. Thefluid–structure interaction is dealt with using an immersed contact interface and a penaltycoupling method. The oblique water impacts of three different fuselage sections have beenstudied based on the experimental campaigns carried out during the European project SARAHat the High-Speed Ditching Facility of CNR-INM in Rome, Italy. The results are presented interms of force coefficient, local relative pressure, and free surface elevation. The effect of thecoupling stiffness and size of the fluid elements on the numerical results is analysed to assessthe robustness of the numerical method. The numerical method shows a satisfying capabilityto reproduce most of the experimental results. Particular attention is given to the capabilityof the numerical method to describe the suction and cavitation phenomena. The effect of thespecimens’ transversal cross-section, the specimens’ longitudinal curvature and the developmentof cavitation phenomenon on the hydrodynamic loads are also investigate
McKean-Vlasov equations with singular coefficients - a review of recent results
No full textThis paper focuses on recent works on McKean-Vlasov stochastic differential equations (SDEs) involving singular coefficients. After recalling the classical framework, we review existing recent literature depending on the type of singularities of the coefficients: on the one hand they satisfy some integrability and measurability conditions only, while on the other hand the drift is allowed to be a generalised function. Different types of dependencies on the law of the unknown and different noises will also be considered. McKean-Vlasov SDEs are closely related to non-linear Fokker-Planck equations that are satisfied by the law (or its density) of the unknown. These connections are often established also in this singular setting and will be reviewed here. Important tools for dealing with singular coefficients are also included in the paper, such as Figalli-Trevisan superposition principle, Zvonkin transformation, Markov marginal uniqueness, and stochastic sewing lemma
Extension de l'expérience de la Phase-Locked Loop pour l'application à l'essai de vibration au sol
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KernelSOS for Global Sampling-Based Optimal Control and Estimation via Semidefinite Programming
No full textGlobal optimization has gained attraction over the past decades, thanks to the development of both theoretical foundations and efficient numerical routines to cope with optimization problems of various complexities. Among recent methods, Kernel Sum of Squares (KernelSOS) appears as a powerful framework, leveraging the potential of sum of squares methods from the polynomial optimization community with the expressivity of kernel methods widely used in machine learning. This paper applies the kernel sum of squares framework for solving control and estimation problems, which exhibit poor local minima. We demonstrate that KernelSOS performs well on a selection of problems from both domains. In particular, we show that KernelSOS is competitive with other sum of squares approaches on estimation problems, while being applicable to non-polynomial and non-parametric formulations. The samplebased nature of KernelSOS allows us to apply it to trajectory optimization problems with an integrated simulator treated as a black box, both as a standalone method and as a powerful initialization method for local solvers, facilitating the discovery of better solutions
Etude expérimentale de la cristallisation sous tension dans un caoutchouc naturel chargé
No full textInternational audienceLa modélisation de la cristallisation induite mécaniquement (MIC) est essentielle pour la conception de pièces antivibratoires en caoutchouc, mais le comportement viscoélastique de ces matériaux complique la compréhension des cinétiques de cristallisation. Ces travaux étudient un caoutchouc naturel chargé à travers des essais de traction, à différentes vitesses, et un essai anhystérétique (ANH) combinant des paliers statiques et monotones. Une analyse systématique du triplet {déformation, contrainte, indice de cristallinité}, appuyée par des mesures synchrotron in-situ, met en lumière les cinétiques de cristallisation ainsi que l’influence de l’histoire du chargement sur celle-ci
Feature expansion and enhanced compression for class incremental learning
No full textInternational audienceClass incremental learning consists in training discriminative models to classify an increasing number of classes over time. However, doing so using only the newly added class data leads to the known problem of catastrophic forgetting of the previous classes. Recently, dynamic deep learning architectures have been shown to exhibit a better stability-plasticity trade-off by dynamically adding new feature extractors to the model in order to learn new classes followed by a compression step to scale the model back to its original size, thus avoiding a growing number of parameters. In this context, we propose a new algorithm that enhances the compression of previous class knowledge by cutting and mixing patches of previous class samples with the new images during compression using our Rehearsal-CutMix method. We show that this new data augmentation reduces catastrophic forgetting by specifically targeting past class information and improving its compression. Extensive experiments performed on the CIFAR and ImageNet datasets under diverse incremental learning evaluation protocols demonstrate that our approach consistently outperforms the state-of-the-art . The code will be made available upon publication of our work
From Movement to Learning: Leveraging VR Behavioral Metrics to Evaluate Cognitive Load and Curiosity
No full textVirtual Reality (VR) is increasingly used in education due to its immersive and interactive capabilities, but its impact on cognitive load and curiosity remains underexplored, particularly regarding real-time behavioral indicators of cognitive load and curiosity. This study investigates how VR behavioral metrics-specifically hand and head movement patterns-can serve as objective, synchronous indicators of cognitive engagement and intrinsic motivation. A controlled experiment was conducted with 125 medical students, who engaged in a neuroanatomy learning task within a VR environment featuring varying levels of interactivity. Behavioral data, including movement entropy, exploration patterns, and gesture dynamics, were analyzed in relation to self-reported measures of cognitive load, motivation, and engagement. Results indicate that while greater hand movement was associated with lower intrinsic motivation, higher head movement correlated positively with germane cognitive load and intrinsic motivation, implying deeper cognitive engagement. Additionally, movement entropy emerged as a predictor of curiosity-driven learning, suggesting its potential as an indicator of learning behaviors in VR environments. These findings contribute to a better understanding of how behavioral data can complement traditional assessments of learning experiences in VR. They also highlight the need for further research into integrating movement-based metrics with instructional design to support engagement and learning outcomes
On the behavior of a granular soil deposit subjected to horizontal vibration: A discrete element modeling
No full textInternational audienceThis paper presents an analysis of the behavior of a non-cohesive granular material deposit excited at its base by a horizontal harmonic vibration. The analysis is carried out numerically by means of a 2D discrete element model. The performed simulations highlighted some aspects of vibration behavior in non-cohesive deposits, such as the shape of the vertical profile of the displacement, notably in the case of large displacements. The analysis particularly focused on the amplification of the movement at the free surface of the deposit, as well as its dependence on some parameters such as the excitation frequency and the excitation amplitude of the deposit confinement. The obtained results showed that the behavior of the deposit following the change in the excitation frequency is similar to the case of an elastic deposit excited by a harmonic displacement at the base, i.e. the Dynamic Amplification Factor (DAF) initially increases with the frequency increase, it reaches a peak of resonance then it decreases. The resonance frequency estimated from this analysis is close to the fundamental frequency for low excitation amplitudes, but becomes smaller as the excitation amplitude increases. On the other hand, for a fixed frequency, increasing the amplitude of the excitation induces greater amplification. It has been shown that this increase results from the degradation of the shear modulus due to the increase in the level of involved shear strain. Therefore, unlike elastic deposits, for non-cohesive granular deposits, increasing strain leads to a degradation of the shear modulus, resulting in a downward shift of the resonance frequency and can induce a significant increase in amplification. The confinement of the deposit is achieved by increasing the gravitational acceleration; it has been shown that increased confinement makes the deposit stiffer, and therefore reduces the amplification of the introduced movement
A Two-Timescale Decision-Hazard-Decision Formulation for Storage Usage Values Calculation
No full textThe penetration of renewable energies requires additional storages to deal with intermittency. Accordingly, there is growing interest in evaluating the opportunity cost (usage value) associated with stored energy in large storages, a cost obtained by solving a multistage stochastic optimization problem. Today, to compute usage values under uncertainties, an adequacy resource problem is solved using stochastic dynamic programming assuming a hazard-decision information structure. This modelling assumes complete knowledge of the coming week uncertainties, which is not adapted to the system operation as the intermittency occurs at smaller timescale. We equip the twotimescale problem with a new information structure considering planning and recourse decisions: decision-hazard-decision. This structure is used to decompose the multistage decision-making process into a nonanticipative planning step in which the on/off decisions for the thermal units are made, and a recourse step in which the power modulation decisions are made once the uncertainties have been disclosed. In a numerical case, we illustrate how usage values are sensitive as how the disclosure of information is modelled
Time-harmonic wave propagation in junctions of two periodic half-spaces
No full textInternational audienceWe are interested in the Helmholtz equation in a junction of two periodic half-spaces. When the overall medium is periodic in the direction of the interface, Fliss and Joly (2019) proposed a method which consists in applying a partial Floquet-Bloch transform along the interface, to obtain a family of waveguide problems parameterized by the Floquet variable. In this paper, we consider two model configurations where the medium is no longer periodic in the direction of the interface. Inspired by the works of Gérard-Varet and Masmoudi (2011, 2012), and Blanc, Le Bris, and Lions (2015), we use the fact that the overall medium has a so-called quasiperiodic structure, in the sense that it is the restriction of a higher dimensional periodic medium. Accordingly, the Helmholtz equation is lifted onto a higher dimensional problem with coefficients that are periodic along the interface. This periodicity property allows us to adapt the tools previously developed for periodic media. However, the augmented PDE is elliptically degenerate (in the sense of the principal part of its differential operator) and thus more delicate to analyse