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Numerical study of a novel jet-grid approach for Li-ion batteries cooling
No full textClimate change is driving new and more efficient ways of producing and storing energy. In particular, Lithium-ion batteries demonstrate to be a worthwhile storage system for their high specific power and energy density. Due to electrochemical processes inside batteries, high temperatures are achieved during fast charge and discharge. Herein, a novel jet-grid cooling technique, named ImpFilm, featuring fluid impingement and fluid film is proposed. The idea is to introduce an innovative system able to guarantee stable and uniform temperature for Lithium-ion batteries with the purpose to reduce weight and costs. Firstly, the system has been designed by means of a preliminary 0D thermodynamic analysis. Then, 3D CFD simulations have been run on a single module to test its feasibility and effectiveness by the standpoint of fluid and thermodynamics. Mass flow rate, velocity field, volume fraction and temperature distribution are analyzed in the module by focusing on the impact of the geometry grid on both flow dynamics and cell temperature evolution. Results show that a parametric study on the grid design is necessary to balance the flow rate subdivision and to uniform the temperature of all the batteries. Eventually, new grid features prove to be effective in keeping battery temperature uniform and below hazardous thresholds
Physico-Chemical and Mechanical Properties of DC-Sputtered ZrO2 Coatings Prepared by Oblique Angle Deposition
No full textIn 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
Environment Spatial Restitution for Remote Physical AR Collaboration
Get PDFThe emergence of spatial immersive technologies allows new ways to collaborate remotely. However, they still need to be studied and enhanced in order to improve their effectiveness and usability for collaborators. Remote Physical Collaborative Extended Reality (RPC-XR) consists in solving augmented physical tasks with the help of remote collaborators. This paper presents our RPC-AR system and a user study evaluating this system during a network hardware assembly task. Our system offers verbal and non-verbal interpersonal communication functionalities. Users embody avatars and interact with their remote collaborators thanks to hand, head and eye tracking, and voice. Our system also captures an environment spatially, in real-time and renders it in a shared virtual space. We designed it to be lightweight and to avoid instrumenting collaborative environments and preliminary steps. It performs capture, transmission and remote rendering of real environments in less than 250ms. We ran a cascading user study to compare our system with a commercial 2D video collaborative application. We measured mutual awareness, task load, usability and task performance. We present an adapted Uncanny Valley questionnaire to compare the perception of remote environments between systems. We found that our application resulted in better empathy between collaborators, a higher cognitive load and a lower level of usability, remaining acceptable, to the remote user. We did not observe any significant difference in performance. These results are encouraging, as participants' observations provide insights to further improve the performance and usability of RPC-AR
A comparison of process damping modelling as local flank face interaction and as macroscopic modal feature in a time domain machining simulation
Get PDFDissipative components of tool-workpiece interaction are of major importance in cutting-related vibrations. At the macroscopic vibration scale, such dissipation is usually accounted for by additional generalized damping forces in the equation of motion of the system’s elastodynamics. A finer consideration at cutting edge scale would bring up a line-distributed force mostly of ploughing nature. These two scales are usually linked by analytical integration, involving simplifying kinematical assumptions. In the present work a comparative investigation is proposed, for a machining operation, considering both representations in a detailed time domain modeling framework. Tool’s cutting edges are represented in a discretized manner, i.e. split into numerous elementary cutters allowing for detailed tool-workpiece interaction force distribution. The matter removal process is modeled via dexel-based surface discretization coupled with finite element-based modal shapes, enabling a consistent machined surface generation representation. Finally, the equations of motion are formulated for modal degrees of freedom and solved by a time marching algorithm. Based on these analyses, the limitations of resulting process damping force terms representations are considered regarding vibrations and interaction force magnitudes
On the strain energy decomposition in phase field brittle fracture: established models and novel cleavage plane-based techniques
Get PDFThèse financée par ALM (Angers Loire Métropole) et ANR RockStorHy.This work offers a detailed examination of the phase field approach for modeling brittle fracture, emphasizing its theoretical foundations, mathematical descriptions, and computational strategies. Central to our discussion is an in-depth analysis of strain energy decomposition methods integral to phase field models. We introduce an innovative technique using a cleavage plane based degradation that has shown promising results under various loading scenarios. We meticulously evaluate each method’s inherent limitations and challenges to highlight their respective advantages and drawbacks across different loading scenarios. This review aims not only to catalog existing knowledge but also to pave the way for future research directions in the application of phase field approach to fracture analysis
Topology Optimization of Chip Inductor Using Density Method
No full textThis paper proposes a novel methodology of the topology optimization method considering eddy current effects. The method is applied on chip inductors modelled by the Finite Element Method (FEM). Aiming to meet a specified inductance value while minimizing eddy current losses, we employ a density-based approach to construct a continuous material distribution. The derivative of the objective function with respect to the material distribution is obtained using the adjoint variable method, then the material layout is iteratively updated via the L-BFGS-B algorithm. The proposed framework is validated on both single-turn and multi-turn inductor structures, achieving designs that satisfy the target performance within a limited number of iterations. A key innovation of this work lies in the integration of field-circuit coupling into the topology optimization framework, enabling the analysis of inductors under complex coil configurations involving both series and parallel connections. Additionally, we present an original derivation of the sensitivity formulation associated with the inductance value ensuring that the optimized inductance meets the design specification
Screen Printed Piezoelectric Transducers for Structural Health Monitoring of Curved Thick Composite Panels
Get PDFThis research focuses on the development and experimental validation of a novel printed
piezoelectric transducers network employed on a foreign object damage panel substructure
of an aircraft engine fan blade. The main goal of the work is to leverage the screen printing
technology to fabricate arrays of piezoelectric transducers and ultimately employ these trans-
ducers for operations, enabling the development of structural health monitoring methods for
the panel. The printed transducer is made up of a piezoelectric layer sandwiched between
two silver electrodes, each printed in a controlled manner. Upon printing and drying of the layers, the transducers undergo polarization. The electromechanical behaviour of the printed transducers, characterized using impedance measurements, exhibits high repeatability, thus indicating its potential for large scale industrial deployment. Following this, it is demon-strated that the transducers are capable of accurately sensing impact, which is one the mostcommon yet critical sources of damage to an engine fan blade. It is also shown that the printed transducers are able to detect acoustic emission events. The ability of the printed transducers to actuate and sense guided wave signals over a range of ultrasonic frequencies is also demonstrated. Furthermore, apart from the noticeable advantages of the non-intrusive nature, and negligible weight as compared to their traditional ceramic counterparts, the printed piezoelectric transducers can potentially be integrated into the manufacturing process in the future, and the presence of transducer arrays ensures the availability of other transducers in case of an individual failure during service. This innovative printing technol-ogy for PZT transducer networks thus holds significant promise in bridging the gap between research advancements and the industrial implementation of SHM technology
Multiscale modeling of mechanically recycled glass fiber reinforced polyamide 6 composites accounting for viscoelasticity, viscoplasticity, and anisotropic damage
Get PDFFiber-reinforced thermoplastic composites are valued for their strength-to-weight ratio, cost-effectiveness, and recyclability, highlighting the need for efficient recycling technologies amid environmental concerns. This study addresses these challenges
by examining the mechanical response of recycled glass fiber reinforced polyamide 6 composites and modeling their nonlinear, time-dependent behavior under complex loading conditions. Advanced nonlinear constitutive and multiscale models, initially
developed for conventional fiber composites, are adapted to capture the stochastic response of recycled materials. These models integrate viscoelasticity, viscoplasticity and damage in the polymer matrix and account for anisotropic damage in the strands,
addressing the heterogeneity introduced by the recycling process. A modified random sequential adsorption technique replicates the microstructures for nonlinear response modeling. Hypotheses based on microstructural investigations consider processing
effects that disrupt the initial chip woven structure and create matrix-rich areas. The model captures anisotropy and variability observed in experimental data, providing a reliable framework for predicting the performance of recycled thermoplastic com-
posites and improving the understanding of the relationship between microstructure and mechanical properties, with a focus on inelastic nonlinear behavior
Coupled crystal plasticity-cohesive zone modeling of rock salt viscoplasticity
Get PDFRock salt, owing to its viscoplastic behavior and structural integrity under high pressure, is a promising candidate for safe and large-scale underground energy storage. This study presents a comprehensive numerical framework for modeling the viscoplastic deformation of rock salt, accounting for both intragranular and grain boundary (GB) deformation mechanisms. Intragranular deformation is modeled using a crystal plasticity approach governed by a power-law relation, capturing the activity of crystallographic slip systems. Concurrently, a cohesive zone model (CZM) is introduced to simulate grain boundary sliding (GBS) and opening via a rate-dependent traction–separation law. This modeling strategy enables a detailed analysis of the coupled interplay between crystal plasticity and intergranular decohesion phenomena
AI-driven advances in composite materials for hydrogen storage vessels: A review
No full textThis review provides a comprehensive examination of artificial intelligence methods applied to the design, optimization, and performance prediction of composite-based hydrogen storage vessels, with a focus on composite overwrapped pressure vessels. Targeted at researchers, engineers, and industrial stakeholders in materials science, mechanical engineering, and renewable energy sectors, the paper aims to bridge traditional mechanical modeling with evolving AI tools, while emphasizing alignment with standardization and certification requirements to enhance safety, efficiency, and lifecycle integration in hydrogen infrastructure. The review begins by introducing HSV types, their material compositions, and key design challenges, including high-pressure
durability, weight reduction, hydrogen embrittlement, leakage prevention, and environmental sustainability. It then analyzes conventional approaches, such as finite element analysis, multiscale modeling, and experimental testing, which effectively address aspects like failure modes, fracture strength, liner damage, dome thickness, winding angle effects, crash behavior, crack propagation, charging/discharging dynamics, burst pressure, durability, reliability, and fatigue life. On the other hand, it has been shown that to optimize and predict the characteristics of hydrogen storage vessels, it is necessary to combine the conventional methods with artificial intelligence methods, as conventional methods often fall short in multi-objective optimization and rapid predictive analytics due to computational intensity and limitations in handling uncertainty or complex datasets. To overcome these gaps, the paper evaluates hybrid frameworks that integrate traditional techniques with AI, including machine learning, deep learning, artificial neural networks, evolutionary algorithms, and fuzzy logic. Recent studies demonstrate AI’s efficacy in failure prediction, design optimization to mitigate structural risks, structural health monitoring, material property evaluation, burst pressure forecasting, crack detection, composite lay-up arrangement, weight minimization, material distribution enhancement, metal foam ratio optimization, and optimal material selection. By synthesizing these advancements, this work underscores AI’s potential to accelerate development, reduce costs, and improve HSV performance, while advocating for physics-informed models, robust datasets, and regulatory alignment to facilitate industrial adoption