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Introduction to Non-linear Mechanics: A Unified Energetical Approach
No full textInternational audienceThis book presents an introduction to the non-linear mechanics of materials, focusing on a unified energetical approach. It begins by summarizing the framework of a thermodynamic description of continua, including a description of the kinematics of deformation, and a summary of the equations of motion. After a short description of the motion of the system and the mechanical interaction, the book introduces the Lagrangean and Hamiltonian functionals of the system, transitioning to the quasistatic characterization with emphasis on the role of potential energy and pseudo-potential of dissipation. The framework is then extended to fracture and damage mechanics with a similar energetical approach proposed for material damage and wear. The book looks at homogenization in non-linear mechanics for locally plastic or damaged material with an analysis of stability and bifurcation of the equilibrium path. Lastly, inverse problems in non-linear mechanics are introduced using optimal control theory. All the concepts introduced in the book are illustrated using analytical solutions on beams, rods, plates, or using spherical and cylindrical symmetries. Graduate students and researchers working on continuum mechanics and interested in a deeper understanding of materials damage, wear, and fatigue will find this book instructive and informative
Measurement of three-dimensional volumetric displacement fields in structural porous adhesive joints, under tensile and tensile-shear load, by means of in-situ X-ray microtomography
No full textInternational audienceNowadays, structural bonding is increasingly used for its advantages over conventional joining methods such as riveting or welding. Bonding defects (incomplete polymerization, gradient of mechanical properties, and presence of pores, among others.) can significantly impact the mechanical behavior of these assemblies. Among these defects, the presence of pores, detectable by means of X-ray microtomography measurements, could have a significant influence on the mechanical strength of a bonded structure (reduction of the useful section, questioning of the continuity of the joint, and stress concentration, among others). The study of these pores populations by means of microtomographic measurements, as well as their evolution under mechanical stress, can therefore provide valuable information regarding the mechanical behavior. These data can provide information on (i) the mechanical behavior on a microscopic scale, (ii) the identification of mechanisms of damage and failure of the adhesive joint, or (iii) the measurement of volume displacement fields. In this work, a method for calculating volume displacement fields in an adhesive joint is presented, using the detected pores as markers. The robustness, limits, and effects of different parameters (noise, voxelization, among others.) on this algorithm are identified on synthetic data representative of an adhesive joint. Finally, the validation of the method is based on interrupted tests on relatively small bonded specimens (called mini-Scarf) under tensile and tensile-shear loads
Coexistence of five domains at single propagating interface in single-crystal Ni-Mn-Ga shape memory alloy
No full textInternational audienceCoexistence of both austenite and martensite during phase transformation is a common feature of all Shape Memory Alloys (SMAs). The martensite has different variants featuring characteristic deformations rotationally linked to each other due to the symmetries of the austenite parent phase, and can form twins by mixing pair of variants which lead to different mean characteristic deformations. Multiple-domain microstructures (consisting of austenite, martensite domain interface is not a perfectly compatible pattern like the basic habit plane (consisting of only one twin compatible with austenite). However, its level of non-compatibility is similar to that of the quite common X-interface (four-domain coexistence) which is observed in many SMAs. Further, the significant effects of the thermal loading path and the material initial state (the initial martensite variant) on the domain pattern formation are demonstrated and analyzed. The experimental observation and the theoretical analysis of the domain patterns can provide hints to better understand diffuse interface kinetics and phase transformation hysteresis
Investigation of 3D printed CF-PETG composites' tensile behaviors: Synergizing simulative and real-world explorations
No full textInternational audienceThis paper presents an experimental and numerical analysis of carbon fiber-reinforced thermoplastic polymer (CF-PETG) made using fused filament fabrication (FFF) technology on dumbbell-shaped specimens under static tensile tests for both honeycomb (NIDA) and rectilinear (RECT) fill patterns at different infill densities (20%, 50%, 75%, and 100%). The tensile test is meticulously executed using the state-of-the-art INSTRON 5969 testing apparatus, with a precise displacement speed set at 2 mm per minute, ensuring the utmost accuracy in our measurements. The experimental results show that the mechanical behavior of each specimen is elastoplastic. The honeycomb pattern showed better strength and stiffness when compared to the rectilinear pattern. The Digimat material model allows for the simulation of complex material behavior, including nonlinear and anisotropic behavior, considering microstructure effects. The numerical model developed using Abaqus/Digimat coupling with experimental results shows a good correlation between the obtained results
DRL-Based Thruster Fault Recovery for Unmanned Underwater Vehicles
No full textInternational audienceThruster faults are one of the most common malfunctions encountered during Unmanned Underwater Vehicle (UUV) missions. This type of fault can lead to unwanted behaviour and jeopardise the UUV mission. Successful thruster fault management depends on accurate diagnostics. However, some scenarios, particularly instances of thruster faults due to external factors, pose a hard diagnostic task. This is particularly challenging in the context of abnormal behaviours that are detected but no fault diagnosis can be provided by the onboard fault management system. This type of fault is called nondiagnosable and it is the main target of this work. The aim of this paper is to propose a solution for controlling UUVs subject to non-diagnosable thruster faults using a Deep Reinforcement Learning (DRL)-based approach. This paper provides a comparison between an end-to-end DRL-trained controller and a standard PID controller to overcome partial and total thruster faults of a UUV. The consistency and robustness of the proposed method is verified by simulations. The results demonstrate the DRL-based controller's effectiveness in addressing nondiagnosable thruster faults that would otherwise hinder the successful completion of the mission
The Beneficial Role of Curiosity on Route memory in Children
No full textWe assessed the influence of trait and state curiosity on route memory. Forty-two 10-year-old children with low and high-trait curiosity (20 Females; 22 Males) actively explored virtual environments that elicited varying levels of uncertainty (i.e., state-curiosity). As trait curiosity increased, so did memory performance in low and high uncertainty conditions, suggesting that high-curiosity children can better recruit cognitive resources within non-optimal environments. Children with high compared to low curiosity also reported greater feelings of presence during exploration. Importantly, in environments with medium uncertainty, children with low trait curiosity were able to perform as well as those with high curiosity. Results show that individual differences in trait curiosity influence route learning, and interact dynamically with state-curiosity invoked within different environments
Coherence and superradiance from a plasma-based quasiparticle accelerator
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Evolving Reservoirs for Meta Reinforcement Learning
No full textInternational audienceAnimals often demonstrate a remarkable ability to adapt to their environments during their lifetime. They do so partly due to the evolution of morphological and neural structures. These structures capture features of environments shared between generations to bias and speed up lifetime learning. In this work, we propose a computational model for studying a mechanism that can enable such a process. We adopt a computational framework based on meta reinforcement learning as a model of the interplay between evolution and development. At the evolutionary scale, we evolve reservoirs, a family of recurrent neural networks that differ from conventional networks in that one optimizes not the synaptic weights, but hyperparameters controlling macro-level properties of the resulting network architecture. At the developmental scale, we employ these evolved reservoirs to facilitate the learning of a behavioral policy through Reinforcement Learning (RL). Within an RL agent, a reservoir encodes the environment state before providing it to an action policy. We evaluate our approach on several 2D and 3D simulated environments. Our results show that the evolution of reservoirs can improve the learning of diverse challenging tasks. We study in particular three hypotheses: the use of an architecture combining reservoirs and reinforcement learning could enable (1) solving tasks with partial observability, (2) generating oscillatory dynamics that facilitate the learning of locomotion tasks, and (3) facilitating the generalization of learned behaviors to new tasks unknown during the evolution phase
Quasi 3D electronic structures of Dion-Jacobson layered perovskites with exceptional short interlayer distances.
No full textInternational audienceIn the field of perovskite solar cells (PSCs), 3D/2D heterostructures are a promising route to obtain highly efficient and stable devices. Herein, inspired by dications which have afforded rare layered perovskites called Dion-Jacobson (DJ), with short interlayer distances, we designed and synthesized the new 2-iodopropane-1,3-diamonium dication (DicI), and we successfully obtained multi-n 2D layered perovskites (DicI)(MA)n- 1PbnI3n+1 (n= 1-4, MA+= methylammonium). As a result of a suitable size of the dication which well fits, in projection to the layer planes, in the square defined by four adjacent apical iodides, as well as halogen bonding between organic iodine and apical iodides (I(ap)) of perovskite layers, a perfect eclipsed configuration between adjacent layers takes place, yielding unprecedented short I(ap)….I(ap) distances, as small as 3.882 Å in (DicI)(MA)2Pb3I10. Density Functional Theory (DFT) calculations highlight unusually strong valence band dispersion along the the →Z direction. Effective masses for out-of-plane motions of holes are estimated on par with values computed for 3D perovskites, and similar to in-plane effective masses in 2D multilayered perovskites. This indicates these layered compounds feature quasi 3D electronic structures, hence appearing as promising candidates for PSCs heterostructure