Concurrent multiscale simulations of nonlinear random materials using probabilistic learning

DOI10.1016/j.cma.2024.116837OpenAlexW4391908430MaRDI QIDQ6125499

Johann Guilleminot, Peiyi Chen, Christian Soize

Publication date: 11 April 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2024.116837

zbMATH Keywords

nonlinear elasticityrandom mediaprobabilistic learninguncertainty quantificationsurrogatesconcurrent methods

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Computer science (68-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• A Mathematical Theory of Communication
• On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties
• Uncertainty quantification. An accelerated course with advanced applications in computational engineering
• Numerically explicit potentials for the homogenization of nonlinear elastic heterogeneous materials
• Data-driven probability concentration and sampling on manifold
• The heterogeneous multiscale methods
• The reduced model multiscale method (R3M) for the nonlinear homogenization of hyperelastic media at finite strains
• A numerical method for homogenization in nonlinear elasticity
• An adaptive method for homogenization in orthotropic nonlinear elasticity
• Two scale analysis of heterogeneous elastic-plastic materials with asymptotic homogenization and Voronoi cell finite element model
• A multilevel finite element method (FE\(^{2}\)) to describe the response of highly nonlinear structures using generalized continua.
• \(FE^2\) multiscale approach for modelling the elastoviscoplastic behaviour of long fibre SiC/Ti composite materials
• Two-stage data-driven homogenization for nonlinear solids using a reduced order model
• Prediction of the mechanical behavior of nonlinear heterogeneous systems by multi-level finite element modeling
• Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites
• NH-PINN: neural homogenization-based physics-informed neural network for multiscale problems
• Spatially-dependent material uncertainties in anisotropic nonlinear elasticity: stochastic modeling, identification, and propagation
• Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints
• Stochastic elasticity. A nondeterministic approach to the nonlinear field theory
• Efficient multiscale modeling for woven composites based on self-consistent clustering analysis
• Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials
• A random field model for anisotropic strain energy functions and its application for uncertainty quantification in vascular mechanics
• A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites
• A nonlinear manifold-based reduced order model for multiscale analysis of heterogeneous hyperelastic materials
• Adaptive reduced basis finite element heterogeneous multiscale method
• Non-Gaussian positive-definite matrix-valued random fields for elliptic stochastic partial differential operators
• Multiscale finite element methods for nonlinear problems and their applications
• Computational homogenization of nonlinear elastic materials using neural networks
• The heterogeneous multiscale method
• Information Theory and Statistical Mechanics
• Multiscale Finite Element Methods
• Non-linear anisotropic elasticity for real-time surgery simulation
• Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
• Multi‐scale constitutive modelling of heterogeneous materials with a gradient‐enhanced computational homogenization scheme
• Computational Homogenization Using Convolutional Neural Networks
• COMPUTATION OF SOBOL INDICES IN GLOBAL SENSITIVITY ANALYSIS FROM SMALL DATA SETS BY PROBABILISTIC LEARNING ON MANIFOLDS
• Nonlinear Continuum Mechanics for Finite Element Analysis
• On constitutive macro-variables for heterogeneous solids at finite strain
• A class of general algorithms for multi-scale analyses of heterogeneous media
• Probabilistic learning on manifolds (PLoM) with partition
• Probabilistic learning and updating of a digital twin for composite material systems
• Updating an uncertain and expensive computational model in structural dynamics based on one single target FRF using a probabilistic learning tool
• A Neural Network Approach for Homogenization of Multiscale Problems

This page was built for publication: Concurrent multiscale simulations of nonlinear random materials using probabilistic learning