Recherche

Consulter le flux RSS

Publications

Liste des publications du LMPS

Affichage des publications 211 à 220 sur 1266 au total

Methods and statistics

Active learning reliability analysis for the design of reinforced concrete rail bridges

The design and analysis of reinforced concrete rail bridges is a challenging process in the context of uncertainty propagation. Active learning reliability analysis is an efficient way to design such complex structures and select the most performant…

Mouhammed Achhab, Pierre Jehel, Fabrice Gatuingt

LMP(hD)'S Day (LMPS) -

Differential Geometry

Objective rates as covariant derivatives on the manifold of Riemannian metrics

The re-foundation and geometrization of Continuum Mechanics was initiated by C. Truesdell and W. Noll at the beginning of the second half of the 20th century. The starting point of this formulation is an abstract manifold of dimension 3 (with…

Boris Kolev, Rodrigue Desmorat

3rd International Conference on Nonlinear Solid Mechanics -

Engineering Sciences

Modélisation objective de structures en maçonnerie

Cet article propose un modèle de comportement permettant de décrire la réponse de la maçonnerie sous chargement cyclique. Le modèle intègre les mécanismes d’élasticité orthotrope, d’endommagement orthotrope, de frottement en cisaillement, d’effet…

Héloïse Rostagni, Cédric Giry, Frédéric Ragueneau

16ème Colloque National en Calcul de Structures (CSMA 2024) -

Engineering Sciences

Eikonal gradient-enhanced regularization of anisotropic second-order tensorial continuum damage models for quasi-brittle materials

Continuum damage models are often employed to represent cracking in quasi-brittle materials (e.g., concrete, masonry and some rocks). From a numerical perspective, these models yield mesh-dependent results at the structural scale without…

Breno Ribeiro Nogueira, Giuseppe Rastiello, Cédric Giry, Fabrice Gatuingt, Carlo Callari

Computer Methods in Applied Mechanics and Engineering -

Engineering Sciences

Pré-dimensionnement de structures aéronautiques : une nouvelle perspective grâce à la combinaison de la réduction de modèles et de l'apprentissage profond sur graphes

Ce travail présente une preuve de concept combinant la réduction de modèles et l’apprentissage profond basé sur les graphes (Graph Neural Networks) pour le pré-dimensionnement des structures aéronautiques. Notre approche utilise des données…

Victor Matray, Faisal Amlani, Frédéric Feyel, David Néron

16ème Colloque National en Calcul de Structures (CSMA 2024) -