Impact of cognitive Effort, Social Interaction, Enjoyment of Learning, and Immersive Presence on Academic Achievement with Virtual Reality

Immersive technologies represent significant advancements that allow users to engage in interactive and captivating environments, both perceptually and sensorily. This study aims to enrich the understanding of the relationship between several key variables and the achievement of academic objectives when using VR. An experiment was conducted with first-year university institute of technology students who participated in a virtual visit to a biology laboratory. The primary objective is to evaluate how each of the studied variables influences academic goals. By providing insights into the key factors that determine academic success in immersive environments, this research aims to optimize the use of these technologies in educational contexts, thereby enhancing students' learning outcomes

Recent advances in the remelting process for recycling aluminium alloy chips: a critical review

This critical review examines advances in preprocessing and remelting processes for aluminium alloy chip recycling, emphasizing pre-treatment and remelting techniques that improve both resource recovery and material quality. Pre-treatment strategies, particularly cleaning methods and compaction are critically evaluated. Various cleaning methods, including centrifugation, ultrasonic solvent washing, extraction, and distillation are compared based on their ability to remove residual cutting fluids. Cold compaction, which augments chip density to approximately 2.5 g/cm³, significantly curtails oxidation losses and enhances metal recovery. During remelting, NaCl-KCl-based fluxes with limited fluoride additions (e.g., 3–7 wt% Na₃AlF₆) disrupt oxide networks but require careful dosage control to minimize furnace corrosion and environmental hazards. Moreover, mechanical stirring combined with suitable melting temperatures reduces porosity while enhancing melt purity. Future research should prioritize the development of low-energy cleaning methods, flux composition optimization, and scalable production techniques to further advance sustainable aluminium recycling

On the strain energy decomposition in phase field brittle fracture: established models and novel cleavage plane-based techniques

Thèse 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

Experimental and modeling approach for estimating the psychological adaptation and perceived thermal comfort of occupants in indoor spaces

This study proposes a methodology for examining the relationship between environmental thermal conditions and occupant's perceived thermal comfort evaluation. Therefore, their psychological adaptation was examined to quantify and incorporate it in thermal comfort evaluations. To achieve the closure of the model's system of equations, experiments are carried out in which subjects are exposed to various thermal conditions in an enclosed space that simulates an office indoor environment; thermal measurements and perceived data are collected. Thus, the study aims to evaluate the adaptive factor that causes the difference between the physiological evaluation and the subjects’ actual thermal perception. This adaptive factor is linked to the physical stimuli experienced owing to the thermal environment and the cognitive information within the occupant's memory systems; thus, the closure equation is derived from the outdoor air temperature and indoor operative temperature

Contribution à la mise en œuvre de l’économie circulaire pour les Matières Plastiques (MP) pour la REP ASL

La Responsabilité Elargie des Producteurs (REP) pour les Articles de Sport et de Loisirs (ASL) a été instaurée en France depuis le 1er janvier 2022. ..

Investigation of a constitutive law for the prediction of the mechanical behavior of WEEE recycled polymer blends

This research focuses on a mechanical study of an acrylonitrile–butadiene–styrene (ABS)/ polycarbonate (PC) blend totally derived from Waste Electrical and Electronic Equipment (WEEE) recycling. First, an experimental work was developed in laboratory for the preparation of different mixtures of ABS/PC blend. Then, mechanical tensile tests were performed on the injected specimens and the stress/strain experimental data were gathered to be used in the modelling part. In order to enable the prediction of the mechanical response of the blend, G’Sell and Jonas constitutive law was considered for this purpose. An optimization method based on the Generalized Reduced Gradient (GRG) nonlinear algorithm was developed to identify the input parameters governing the mechanical model. In addition, an uncertainty parametric study was assessed to qualitatively and quantitatively evaluate the constitutive law sensitivity versus the parameter uncertainty. Monte Carlo simulations were performed and the convergence of the numerical model was proved in terms of means and standard deviation statistical data. The results showed an excellent agreement between the numerical approach and the experiments. Besides, it was highlighted the crucial role of coupling uncertainty parametric study with modelling for accurately describing the mechanical behavior of the blend

Investigation of non-Schmid effects in dual-phase steels using a dislocation density-based crystal plasticity model

Non-Schmid (NS) effects in body-centered cubic (BCC) single-phase metals have received special attention in recent years. However, a deep understanding of these effects in the BCC phase of dual-phase (DP) steels has not yet been reached. This study explores the NS effects in ferrite-martensite DP steels, where the ferrite phase has a BCC crystallographic structure and exhibits NS effects. The influences of NS stress components on the mechanical response of DP steels are studied, including stress/strain partitioning, plastic flow, and yield surface. To this end, the mechanical behavior of the two phases is described by dislocation density-based crystal plasticity constitutive models, with the NS effect only incorporated into the ferrite phase modeling. The NS stress contribution is revealed for two types of microstructures commonly observed in DP steels: equiaxed phases with random grain orientations, and elongated phases with preferred grain orientations. Our results show that, in the case of a microstructure with equiaxed phases, the normal NS stress components play significant roles in tension-compression asymmetry. By contrast, in microstructures with elongated phases, a combined influence of crystallographic texture and NS effect is evident. These findings advance our knowledge of the intricate interplay between microstructural features and NS effects and help to elucidate the mechanisms underlying anisotropic-asymmetric plastic behavior of DP steels

A probabilistic model to consider scale and gradient effects in the prediction of the fatigue life of Inconel 718 for turbine disk application

The aim of this paper is to implement and compare different fatigue post-processing approaches for fatigue life assessment of complex parts. Inconel 718 is taken as an example, as it can exhibit several factors influencing fatigue life, such as mean stress, stress gradient and scale effects. Tests on different specimen geometries to exacerbate these effects were carried out at 550°C. The range of service operating life is between 103 and 106 cycles. A modelling chain was then set up. A structural calculation was performed using an elasto-visco-plastic behavior law to obtain the mechanical fields at cycle stabilize. These values were finally exploited by applying a post-processing treatment approach to predict the fatigue life of the structure. Two main types of post-processing approach were investigated: standard and probabilistic. The way in which the different factors influencing fatigue life are considered, depending on the approach used, was discussed. Finally, the probabilistic volume approach yields better results, thanks to its ability to consider mean stress, stress gradient and scale effects in the proposed formulation

Assessing VOIP intelligibility in a low-connectivity environment

Previous work has shown that telecollaboration is a suitable solution for remote assistance of industrial maintenance operations, provided that an audio chat solution is available. There are several reasons why audio chat may not be available: the quality of the available Internet network, both in terms of bandwidth and stability (jittering), but also the presence of too much noise at the site of the operation, which interferes with voice capture. This paper presents a methodology to evaluate the quality provided by an audio chat solution. This methodology is then tested on a specific audio chat solution built on a lossy compression algorithm based on the grouping of successive similar values to overcome the jittering problem and significantly reduce bandwidth requirements. We suggest evaluating the audio quality by assessing the intelligibility of different audio recordings using standard speech therapy methods. Our results suggest that an audio chat can be provided even in a low bandwidth scenario and in a noisy environment, which provides promising insights for the further development of telecollaboration. Moreover, the assessment of audio quality using restitution exercices to evaluate intelligibility, tested on a real use case gives interesting results on the usability of an audio chat solution as well as detailed feedbacks on which part of the altered signal is to be improved

U-NET-based deep learning for automated detection of lathe checks in homogeneous wood veneers

Automated detection of lathe checks in wood veneers presents significant challenges due to their variability and the natural properties of wood. This study explores the use of two convolutional neural networks (U-Net architecture) to enhance the precision and efficiency of lathe checks detection in poplar veneers. The approach involves sequential application of two U-Nets: the first for detecting lathe checks through semantic segmentation, and the second for refining these predictions by connecting fragmented lathe checks. Post-processing techniques are applied to denoise the mappings and extract precise lathe check characteristics. The first U-Net demonstrated strong performance in predicting lathe check presence, with precision and recall scores of 0.822 and 0.835, respectively. The second U-Net refined predictions by linking disjointed segments, improving the overall lathe checks mapping process. Comparative analysis with manual methods revealed comparable or superior performance of the automated approach, especially for shallow lathe checks. The results highlight the potential of the proposed method for efficient and reliable lathe check detection in wood veneers