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Enhancing metal-forming predictions with VR-infused digital twin models
No full textInternational audienceThis article presents a two-step method to enhance metal-forming predictions by integrating Virtual Reality (VR) into Digital Twin models, focusing on single-blow cold copper upsetting operations. The process begins with developing a real-time predictive surrogate model that considers actual process parameters, acting as a crucial link between conventional numerical simulations and immediate decision-making. Subsequently, the surrogate model is integrated into a realistic VR environment, aligned with the experimental forging setup. The study underscores the need and potential advantages of real-time digital twins in the forging field, emphasizing the bridging capability between numerical simulations and instant decision-making through predictive modeling and immersive virtual environments
Predicting the post-bifurcated patterns of architectured materials using group-theoretic tools
No full textInternational audienceExtensive studies on hexagonal honeycombs under in-plane compression have demonstrated that the structure’s symmetry plays a decisive part in the emergence of deformation patterns in post-bifurcated configurations. In this work, the aim is to take advantage of this property by presenting a new group-theoretic approach to list the various attainable post-bifurcated patterns of periodic architectured materials.As of today, some group-theoretic approaches have been elaborated for determining the post-bifurcated paths and thus patterns of a symmetric system submitted to specific loading conditions. However, the application of these approaches requires knowledge of the system’s governing equations. By making use of another group-theoretic tool, this work predicts the various possible post-bifurcated configurations of a periodic architectured material a priori of any non-linear computation by simply assessing the symmetry group of its undeformed configuration.This approach is applied, as an example, to the buckling of regular hexagonal honeycombs but can be easily transferred to any periodic architectured material. This work is a first step towards the elaboration of a more general process for the design of architectured materials when harnessing post-bifurcated behaviour is essential
Fusion laser sur lit de poudre de petites pièces en Inconel 625. Effets de taille et de stratégie de fabrication.
No full textStudy of SLM induced microstructures on designed materials and influence of parameters on the structures size. The main objectives are (1) the implementation of an instrumented additive manufacturing process in order to develop architectural materials, of the truss type, and the determination in real-time information (temperature, hydrodynamics) on the materials being developed, (2) the study of the microstructural and mechanical properties of the materials and the elaboration of structures (simple complexes or more), in relation to their development conditions and their unit dimensions.Etude des microstructures induites par SLM sur matériau architecturé et Influence des paramètres du procédé et de la taille des structures. Il s'agit de : (1) mettre en œuvre un procédé de fabrication additive instrumenté pour élaborer des matériaux architecturés, de type treillis, et disposer d'informations temps réel (température, hydrodynamique) sur les matériaux en cours d'élaboration, (2) étudier les propriétés microstructurales et mécaniques des matériaux et structures élaborés (simples ou plus complexes), en relation avec leurs conditions d'élaboration et leurs dimensions unitaires
Challenges of Holistic Approach for Energy Management Strategies of Hybrid Dual-mode Trains
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Quantum Annealing Solutions for Drone Route Planning Problems
No full textInternational audienceWe present annealing solutions for route optimisation problems for unmanned aerial vehicles (UAVs). The route planning problem is a generalised version of the Travelling Salesman Problem which has many applications in logistics planning. Our annealing solutions combine classical algorithms withquantum/digital annealers specifically designed for quadratic optimisation problems and shows improvements over generic traditional solvers such as Gurobi. We empirically test the solvability of our annealing solutions on both hand-crafted hard test cases as well as simulated ‘real-world’ examples of urban environments where the operations of the UAVs can be affected by the direction and intensity of wind, which is conditioned by the presence of buildings
Multi-part kinematic constraint prediction for automatic generation of CAD model assemblies using graph convolutional networks
No full textInternational audienceThis paper presents a machine learning-based approach to predict kinematic constraints between CAD models that have potentially never been assembled together before. During the learning phase, the algorithm is trained to predict the next-possible-constraints between a set of parts candidate to the assembly. Assemblies are represented in a new graph-based formalism that is capable of capturing features associated with parts, interfaces between parts and constraints between them. Using such a multi-level feature extraction strategy coupled to a state-by-state graph decomposition, the approach does not need to be trained on a large database. This formalism is used to model both the network input and output where the next-possibleconstraints appear after evaluation. The core of the approach relies on a series of networks based on a link-prediction encoder-decoder architecture, integrating the capabilities of several convolutional networks trained in an end-to-end manner. A decision-making algorithm is added to post-process the output and drive the prediction process in finding one among the set of next-possible-constraints. This process is repeated until no more constraints can be added. The experimental results show that the proposed approach outperforms state-of-the-art methods on such assembly tasks. Although the state-by-state assembly algorithm is iterative, it still takes into account the whole set of parts as well as the whole set of constraints already predicted, and this makes it possible to handle constraint cycles, which is generally not possible when not considering multiple parts as input
Forecasting Empty Container availability for Vehicle Booking System Application
No full textInternational audienceContainer terminals, pivotal nodes in the network of empty container movement, hold significant potential for enhancing operational efficiency within terminal depots through effective collaboration between transporters and terminal operators. This collaboration is crucial for achieving optimization, leading to streamlined operations and reduced congestion, thereby benefiting both parties. Consequently, there is a pressing need to develop the most suitable forecasting approaches to address this challenge. This study focuses on developing and evaluating a data-driven approach for forecasting empty container availability at container terminal depots within a Vehicle Booking System (VBS) framework. It addresses the gap in research concerning optimizing empty container dwell time and aims to enhance operational efficiencies in container terminal operations. Four forecasting models-Naive, ARIMA, Prophet, and LSTM-are comprehensively analyzed for their predictive capabilities, with LSTM emerging as the top performer due to its ability to capture complex time series patterns. The research underscores the significance of selecting appropriate forecasting techniques tailored to the specific requirements of container terminal operations, contributing to improved operational planning and management in maritime logistics.</div
Tone Noise Characterization of an Open-Fan Engine Using Source-Mode Integral Formulations
No full textInternational audienceThis study discusses the development of a tone noise model dedicated to an open fan engine, also called Unducted Single Fan. This model intents to be soon implemented into microphone array techniques to better characterize the dominant sources in future wind-tunnel experiments and segregate rotor and stator contributions. It is based on FW-H analogy relying on the thickness and loading noise terms of Goldstein’s formulation, written in the frequency domain. A decomposition into angular modes through equivalent fixed phase-shifted sources is proposed. The predicted sound field takes in account different contributions, which are investigated here: the thickness noise, the steady and unsteady loading noise (from rotor and stator) in advancing flight configurations, and include near-field effects. The unsteady loading harmonics are obtained from URANS calculations with elsA ONERA code. First predictions are compared to reference solutions provided by a time-domain FW-H solver, with fully non-compact sources involving a complete surface integration, at multiple operating points. A more practical compact-source approach is proposed, reducing drastically the number of unknowns involved in the microphones array processing. The preliminary results of this compact modeling are compared with the non-compact solutions at two operating points. Finally, the coupling of this propagation model with array processing is introduced, with a mathematical rewriting in matrix form suitable for implementing in current deconvolution approach, which is first validated for a simplified case with single source-mode
Elastoviscoplastic effects on liquid plug propagation and rupture in an airway model
No full textInternational audienc
Are the ground reaction forces altered by the curve and with the increasing sprinting velocity?
No full textInternational audienceAbstract In 200‐ and 400‐m races, 58% of the total distance to cover is in the curve. In the curve, the sprinting performance is decreased in comparison to the straight. However, the reasons for this decreased performance is not well understood. Thus, the aim of this study was to identify the kinetic parameters underpinning the sprinting performance in the curve in comparison to the straight. Nineteen experienced‐to‐elite curve specialists performed five sprints in the straight and in the curve (radius 41.58 m): 10, 15, 20, 30, and 40 m. The left and the right vertical, anterior–posterior, medial‐lateral, and resultant ground reaction forces (respectively , , , and ), the associated impulses (respectively , , , and ) and the stance times of each side were averaged over each distance. In the curve, the time to cover the 40‐m sprint was longer than in the straight (5.52 ± 0.25 vs. 5.47 ± 0.23 s, respectively). Additionally, the left and the right and were lower than in the straight while the left and the right increased, meaning that the was more medial. The left was also lower than in the straight while the left stance times increased to keep the left similar to the straight to maintain the subsequent swing time. Overall, the sprinting performance was reduced in the curve due to a reduction in the left and the right and , that were likely attributed to the concomitant increased to adopt a curvilinear motion