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Investigation of transonic flows through an idealized ORC turbine vane using Delayed Detached Eddy simulations
No full textInternational audienc
Enhancing Asynchronous Learning in immersive Environments: Exploring Baseline Modalities for Avatar-Based AR Guidance
No full textInternational audienceThis study investigates baseline modalities for evaluating Augmented Reality (AR) avatar guidance in asynchronous collaboration on spatially complex tasks. A formative study with three participants compared smartphone video, HoloLens video, and AR avatars across usability, collaboration, learning, and spatial awareness. Results suggest smartphone video as a reliable baseline due to usability and familiarity. Avatars showed potential for enhancing spatial awareness, task engagement, and learning outcomes but require interface improvements. Despite the small sample size, this study offers insights into immersive technologies for industrial training and collaboration
A methodology to bridge urban shade guidelines with climate metrics
No full textInternational audienceUrban overheating poses significant challenges to public comfort and health, particularly in pedestrian areas. While urban climate studies offer detailed maps of thermal discomfort and heat stress, urban planning often relies on simplified guidelines, creating a gap between research and practice. This study introduces a methodology to bridge this gap by developing a spatially aggregated dissatisfaction indicator, PPD*^, based on the Universal Thermal Climate Index (UTCI) and incorporating a minimum spatial requirement for shade derived from existing cities' shading policies. The novel indicator separately accounts for thermal discomfort in both shaded and sunlit pedestrian areas. A simulated case study in a neighborhood in La Rochelle, France, evaluates six tree planting scenarios, with canopy cover ranging from 0% to 80%. Results indicate that a 20% canopy cover is a practical threshold for mitigating discomfort in moderate and warm climates. This methodology can also be extended to assess additional cooling strategies, such as evaporative systems, and provides valuable insights for optimizing cost-effective and sustainable urban adaptation measures
Management and valorization of storage in electrical networks
No full textInternational audienceThis presentation addresses the management and valorization of energy storage in electrical grids, highlighting its key role in integrating renewable energy sources. In the face of intermittency in solar and wind power, storage smooths production fluctuations, ensures network stability, and enhances electric system flexibility. Case studies are presented before concluding with environmental issues, particularly the impact of material extraction and carbon footprint, while offering perspectives on sustainable solutions to support the energy transition
Multiscale modeling of mechanically recycled glass fiber reinforced polyamide 6 composites accounting for viscoelasticity, viscoplasticity, and anisotropic damage
No full textInternational audienceFiber-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 composites and improving the understanding of the relationship between microstructure and mechanical properties, with a focus on inelastic nonlinear behavior
Exploring the adoption of pay-per-month business models: A theoretical framework and behavioral analysis in the context of white goods in Guayas province, Ecuador
No full textInternational audienceIn response to increasing environmental concerns, this study explores the adoption of a pay-per-month (PPM) model in the white goods sector in Guayas province, Ecuador, within the framework of the circular economy (CE). The research integrates the Theory of Planned Behavior (TPB) and Norm Activation Model (NAM) to assess consumer behavior and preferences. Using a Discrete Choice Experiment (DCE), data were collected from 3267 respondents, evaluating the impact of psychographic factors on PPM model acceptance for products like refrigerators, stoves, and washing machines. Results show that ecological intentions, personal norms, and attitudes significantly influence acceptance. The study reveals that greater consumer education and policy incentives on the environmental benefits of PPM models can drive higher adoption rates. This research contributes to the existing literature by providing a comprehensive framework that merges TPB and NAM methodologies, addressing gaps in understanding consumer motivations in circular business models such as PPM. Additionally, while the focus is on Guayas, the insights gained may have broader applicability in similar developing regions. However, the study also acknowledges limitations related to geographic and socio-economic differences, suggesting avenues for future research to explore the PPM model's viability across diverse contexts. This article is part of a special issue entitled: CLET SDEWES 2023 published in Cleaner Engineering and Technology.</div
Turbulent shear flow without vortex shedding, Reynolds shear stress and small-scale intermittency
No full textInternational audienceThis work presents an experimental investigation of the effects of vortex shedding suppression on the properties and recovery of turbulent wakes. Four plates, properly modified so that they produce different vortex shedding strengths, are tested using high speed particle image velocimetry and hot-wire anemometry, and analysed using spectral proper orthogonal decomposition, mean-flow linear stability analysis and various turbulence statistics. When present, vortex shedding is found to exhibit a characteristic frequency that scales with the mean shear, providing a link between the mean flow and the main turbulent motion. To achieve full suppression of shedding, we combine the effects of porosity and fractal perimeter. The mean shear is then decreased to the point where the flow becomes convectively unstable and shedding vanishes. In that case, the onset of self-similarity is delayed, compared with the case with vortex shedding, and appears after another large-scale structure, the secondary vortex street, emerges. It is also found that both large- and small-scale intermittency are starkly reduced when shedding is absent. A simple theoretical representation of the wake dynamics explains the evolution of the wake properties and its connection to the coherent structures in the flow
U-NET-based deep learning for automated detection of lathe checks in homogeneous wood veneers
No full textInternational audienceAutomated 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
X-ray tomo-ptychography of single micrometric carbon and basalt fibres
No full textInternational audienceCarbon fibre-based composite materials are essential for emissions reduction in transportation. However, the physical properties of their main component, i.e. the micro-size carbon fibres, are still poorly documented because of experimental difficulties. Such material is however known for presenting high anisotropy between offand on-axis properties. Here we have used Ptychography X-ray Computed Tomography to probe quantitatively the bulk electronic density and the morphology of micrometric carbon and basalt fibres. The carbon fibre exhibits a density variation as function of its radius, with a maximum at its center and a minimum around half of the radius, while the basalt fibre is homogeneous. Morphology is investigated at the fibre scale to quantify its deviations from a perfect cylinder and at the nanoscale to evaluate the texture of the surface. Resolutions are around 200 nm. This pioneering work should open new understandings and bulk or surface experimentations on single micron-size fibres at the nanoscale
