HAL Portal UTC Université de Technologie de Compiègne
Not a member yet
11652 research outputs found
Sort by
Analysis of grain structure, precipitation and hardness heterogeneities, supported by a thermal model, for an aluminium alloy 7075 deposited by solid-state multi-layer friction surfacing
No full textInternational audienceThermomechanical cycles during multi-layer friction surfacing (MLFS) cause microstructural and mechanical heterogeneities in the deposited high-strength Al alloy, 7075. The thermal profile and heat accumulation were investigated in this study using a multilayer numerical thermal model of the MLFS process; additionally, these variables were linked to experimentally observed microstructural heterogeneities. Compared with the feedstock, grain sizes decreased by 55–80 %. The mean grain size at the bottom and top areas of a given layer was finer than that in the middle of the layer because of the enhanced recrystallisation, which resulted from the friction and shear deformation experienced by the deposited material. The differences in the thermal cycle and plastic strain rate of the bottom and top areas along the layers resulted in a gradual increase in the grain size at the bottom of each layer and a reduction in the grain size at the top of each layer. The grain growth and continuous dynamic recrystallisation mechanisms are governed by the temperature and strain rate, those mechanisms determine the intra- and inter- layer grain sizes. The accumulated heat, owing to subsequent experimental deposition, resulted in excessive growth of the precipitates in the bottom layers. The strengthening of the solid-solution and Guinier-Preston zones significantly increased the microhardness of the top layer. Post-deposition T6 heat treatments confirmed the restoration of a uniform distribution of microhardness
Practical Method for Estimating Energy Consumption Model of Electric Vehicles Using Real-World Driving Data
No full textInternational audienceTo enhance the environment-friendly performance of electric vehicles (EVs), maximizing energy efficiency remains a critical challenge. Achieving this objective requires highly accurate vehicle dynamics and energy models tailored to the target EV. This study proposes a cost-effective parameter estimation method based on real driving data, eliminating the need for conventional motor bench testing. By collecting motion and energy-related measurements directly from the vehicle during actual driving, the method formulates an optimization problem that minimizes the discrepancy between measured and calculated values to identify model parameters. The proposed approach enables parameter estimation on each driving occasion, allowing it to adapt dynamically to variations in vehicle characteristics and road conditions. As a result, the obtained model closely reflects the actual energy consumption, leading to a reduction in the root mean square error
Energy-Efficient Cooperative Decision-Making for CAVs: A Traffic Flow Optimization Approach
No full textInternational audienc
Context-Aware Hybrid Recommender System for Teachers within MEMORAe SoIS
No full textInternational audienceIn the contemporary educational context, teachers are confronted with the challenge of efficiently managing and utilizing a plethora of heterogeneous pedagogical resources across multiple digital platforms and sources, while simultaneously fostering collaboration in a dynamic educational collaborative environment. This challenge is further amplified by the increasing reliance on digital tools, which often operate in isolation, thereby limiting effective resource sharing and retrieval. To address these challenges, this paper explores the integration of a context-aware pedagogical resources recommender system for teachers within an educational collaborative environment. The paper begins with an identification of the necessity for an integrated approach that connects multiple information systems in order to support resource management and enhance collaborative practices. These are established as a foundation for integration within MEMORAe, a collaborative system of information systems, which employs ontologies for the organisation of heterogeneous resources from different systems and leverages collaborative knowledge sharing. Our integration approach employs the use of MEMORAe to address three pivotal challenges: the structuring of resources, the utilization of context information and the facilitation of collaboration.</div
In Situ Synthesis Of Iron Oxide Nanoparticles Within Polyisobutylene: Toward Multifunctional And Sustainable Nanocomposites
No full textInternational audienc
Assessing physical ergonomics in Industry 5.0: a preliminary deep learning-based approach
No full textInternational audienceMusculoskeletal disorders are frequent workplace injuries, especially during manual lifting activities. They are influenced by posture, lifting technique, and repetitive movements. Various ergonomic assessment methods exist, but each has limitations: observational methods can be slow and prone to error, while contact sensor-based methods, although more accurate, tend to be invasive and expensive. Recent developments have focused on non-contact sensors, such as RGB and RGB-D cameras, combined with Deep Learning algorithms and observational methods, to improve efficiency and reliability. This study proposes a solution combining a skeleton-based Deep Learning algorithm for Human Pose Estimation with an observational method for postural assessment. Using an RGB camera, four lifting techniques (stoop, squat, semi-squat, and weightlifter) were analyzed, evaluating their impact on worker posture through the REBA score. Among handle-assisted lifts, the stoop and weightlifter techniques showed the lowest average maximum REBA scores (5.375 and 6.125), while the squat and semi-squat techniques scored highest at 7. The semi-squat without handles showed the greatest postural risk (7.875). Future work will integrate 3D data and validate the approach with a larger, more diverse population.</div
Safe Cooperative Decision-Making in Uncertain Unsignalized Intersection based on Probabilistic and Predictive Risk Assessment Strategy
No full textInternational audienc
Représentations du son et de la musique au Moyen Âge : analyse et visualisation de la base de données Musiconis (enregistrements et interprétations)
No full textInternational audienceThis dataset is part of the study “Representations of Sound and Music in the Middle Ages: Analysis and Visualization of the Musiconis Database”, authored by Edmundo Camacho, Xavier Fresquet, and Frédéric Billiet. It contains structured descriptions of musical performances, performers, and instruments extracted from the Musiconis database (December 2024 version). This dataset does not include organological descriptions, which are available in a separate dataset. The Musiconis database provides a structured and interoperable framework for studying medieval music iconography. It enables investigations into: • The evolution and spread of musical instruments across Europe and the Mediterranean. • Performer typologies and their representation in medieval art. • The relationships between musical practices and social or religious contexts. Contents: • Musiconis Dataset (JSON format, December 2024 version): • Musical scenes and their descriptions • Performer metadata (roles, social status, gender, interactions) • Instrument classifications (without detailed organological descriptions) • Colab Notebook (Python): • Data processing and structuring • Visualization of performer distributions and instrument usage • Exploratory statistics and mapping Tools Used: • Python (Pandas, Seaborn, Matplotlib, Plotly) • Statistical and exploratory data analysis • Visualization of instrument distributions, performer interactions, and musical contextCe jeu de données fait partie de l’étude « Représentations du son et de la musique au Moyen Âge : analyse et visualisation de la base de données Musiconis », réalisée par Edmundo Camacho, Xavier Fresquet et Frédéric Billiet. Il contient des descriptions structurées d’interprétations musicales, d’interprètes et d’instruments extraites de la base de données Musiconis (version de décembre 2024). Ce jeu de données ne comprend pas de descriptions organologiques, disponibles dans un jeu de données distinct. La base de données Musiconis offre un cadre structuré et interopérable pour l’étude de l’iconographie musicale médiévale. Elle permet d’étudier : • L’évolution et la diffusion des instruments de musique en Europe et dans le bassin méditerranéen. • Les typologies d’interprètes et leur représentation dans l’art médiéval. • Les relations entre les pratiques musicales et les contextes sociaux ou religieux. Contenu : • Jeu de données Musiconis (format JSON, version décembre 2024) : • Scènes musicales et leurs descriptions • Métadonnées des interprètes (rôles, statut social, genre, interactions) • Classification des instruments (sans descriptions organologiques détaillées) • Notebook Colab (Python) : • Traitement et structuration des données • Visualisation de la répartition des interprètes et de l’utilisation des instruments • Statistiques exploratoires et cartographie Outils utilisés : • Python (Pandas, Seaborn, Matplotlib, Plotly) • Analyse statistique et exploratoire des données • Visualisation de la répartition des instruments, des interactions entre interprètes et du contexte musica
Fabrication Additive d'Alliages Ferromagnétiques Doux Fe-3.5Si-4.5Cr par L-PBF: Analyse de la Microstructure et des Propriétés Magnétiques
No full textLe travail final sera présenté en anglais.International audienceCette étude examine la fabrication additive d’unalliage ferromagnétique doux Fe-3,5 Si-4,5 Cr par fusion lasersur lit de poudre (FLLP). L’objectif est d’analyser l’influencedes paramètres de procédé, et notamment de la densité d’énergienormalisée, sur la densité, la microstructure, la texture cristallographique, la résistivité électrique et les propriétés magnétiquesdu matériau produit. Pour cela, des échantillons cubiques ettoroïdaux ont été réalisés sur machine Trumpf 1000 en faisantvarier la puissance laser, la vitesse de balayage, la distance de hachure et l’épaisseur de couche. La densité relative et la formationd’une texture colonnaire sont systématiquement corréléesà la valeur de la densité d’énergie normalisée. L’évolution de larésistivité électrique, mesurée selon la méthode de Van der Pauw,est reliée au raffinement de la microstructure et à la distributiondes grains, mettant en évidence l’impact du contrôle de la taillede grain sur la diffusion électronique. Enfin, l’induction à saturation et le champ coercitif des échantillons toroïdaux révèlentune fenêtre opérationnelle optimale de densité d’énergie pourminimiser les pertes par hystérésis et par courants de Foucault.La technique FLLP se révèle ainsi adaptée à la production decomposants Fe-Si-Cr aux performances magnétiques et électriquescontrôlables
