Publications

Numerical Analysis

Towards a new PGD strategy for the simulation of slender structures

Effective models for slender structures derived from well-known plate (or shell) theories are justified within the limit of a small thickness, and may therefore prove limited for intermediate slenderness. On the other hand, direct 3D simulation of…

Jean Ruel, Frédéric Legoll, Arthur Lebée, Ludovic Chamoin

Engineering Sciences

TRansformer pour Adapter l'existant : une approche multisCalairE et Systémique

Face à l’intensification des changements globaux liés aux processus d’urbanisation à l’échelle planétaire, la transformation de l’existant représente un défi crucial pour répondre aux enjeux contemporains et repenser les modes de conception,…

Manuel Appert, Roberta Morelli, Michela Barbot, Cédric Giry, Hervé Lequay, Catherine Gauthier

Géotechnique

Performance of chitosan and alginate for soil stabilization under saturated conditions

Min Yao, Benhui Fan, Fernando Lopez‐caballero, Thomas Reiss, Jean-Marie Fleureau

European Journal of Environmental and Civil Engineering - 2026

Mechanics of materials

Multiscale modeling of twinning mechanism in polycrystalline 26at%Nb-Ti shape memory alloy

This article investigates the twinning mechanism in a polycrystalline 26at%Nb-Ti shape memory alloy, developed as a biocompatible alternative to NiTi. After metallurgical and mechanical characterization, tensile tests reveal that only the {332} $…

Marie Caruel, Karine Lavernhe, Carlos Angelo Nuñes, Olivier Hubert

Mechanics of Materials - 2026

Infrastructures de transport

Graph Transformer Transferability for Flood Scusceptibility mapping in contrasting regions

Graph Transformers have demonstrated considerable promise for spatial prediction tasks, yet their capacity to generalize across contrasting flood regimes remains poorly understood. This study examined whether a GT model trained on the French Riviera…

Sreenath Vemula, Filippo Gatti, Pierre Jehel

International Structural Engineering and Construction Society (ISEC) - 2026

Machine Learning

Correction: Pawelkiewicz et al. Introducing Machine Learning in Teaching Quantum Mechanics. Atoms 2025, 13, 66

Missing Supplementary Materials In the original publication [1], the Supplementary Materials was not included. The supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/atoms13070066/s1. Supplementary Materials citation…

M. Pawelkiewicz, Filippo Gatti, Didier Clouteau, Viatcheslav Kokoouline, Mehdi Adrien Ayouz

Atoms - 2026

Modeling and Simulation

AI surrogate models for lifetime prediction in power electronic modules

Reliability assessment of power electronic modules (PEMs) traditionally relies on counting methods to decompose complex mission profiles (MPs) into equivalent loading cycles, followed by a cumulative damage rule to estimate fatigue life. While…

M. Ghrabli, Emanuel Aldea, Mounira Bouarroudj, Ludovic Chamoin

Microelectronics Reliability - 2026

Distributed, Parallel, and Cluster Computing

High-performance machine learning and data analysis for next-generation railway design

The MINERVE project aims to create a digital twin of the French railway infrastructure,which will then be used to assess the state of the railway and predict its evolution. To achieve such goal, the project requires a robust architecture capable of…

Hugo Gabrielidis

Health

Impact of artifact reduction using generative adversarial networks on diagnostic accuracy in cone-beam computed tomography

Objective To evaluate the impact of artifact reduction using a generative adversarial network (GAN) on the diagnostic performance for vertical root fracture (VRF) detection in cone-beam computed tomography (CBCT) images. Methods A human mandible…

Amanda Candemil Kanashiro, Hugo Gabrielidis, Filippo Gatti, Manoel Damião Sousa-Neto

Journal of Dentistry - 2026

Engineering Sciences

From data to reality: Criteria for the validation of data-driven models for history-dependent materials

This paper addresses the issue of validating identified data-driven material models for history-dependent materials, which are nowadays typically represented using neural networks. For this purpose, we introduce an a posteriori general acceptability…

Pierre Ladevèze, Ludovic Chamoin

European Journal of Mechanics - A/Solids - 2026