Probabilistic learning and updating of a digital twin for composite material systems

DOI10.1002/nme.6430MaRDI QIDQ6090721

Christian Soize, Loujaine Mehrez, Roger G. Ghanem, Venkat Aitharaju

Publication date: 17 November 2023

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)

zbMATH Keywords

compositesprobabilistic updatingdigital twinprobabilistic machine learningprobabilistic learning on manifolds

Mathematics Subject Classification ID

Multivariate analysis (62Hxx) Stochastic processes (60Gxx) Distribution theory (60Exx)

Related Items (6)

Computational stochastic homogenization of heterogeneous media from an elasticity random field having an uncertain spectral measure ⋮ Probabilistic learning on manifolds (PLoM) with partition ⋮ Updating an uncertain and expensive computational model in structural dynamics based on one single target FRF using a probabilistic learning tool ⋮ Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems ⋮ Concurrent multiscale simulations of nonlinear random materials using probabilistic learning ⋮ Probabilistic learning constrained by realizations using a weak formulation of Fourier transform of probability measures

Cites Work

• Data-driven probability concentration and sampling on manifold
• A PCE-based multiscale framework for the characterization of uncertainties in complex systems
• Entropy-based closure for probabilistic learning on manifolds
• Polynomial Chaos Expansion of a Multimodal Random Vector
• Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
• Multivariate Density Estimation
• Numerical Methods for Second‐Order Stochastic Differential Equations

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