A two-stage surrogate model for neo-Hookean problems based on adaptive proper orthogonal decomposition and hierarchical tensor approximation
type: Item
instance of: scholarly article
title: A two-stage surrogate model for neo-Hookean problems based on adaptive proper orthogonal decomposition and hierarchical tensor approximation
zbMATH Open document ID: 1506.65067
author: Steffen Kastian
author: Dieter Moser
author: Stefanie Reese
author: L. Grasedyck
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2021-04-26T00:00:00Z
Mathematics Subject Classification ID: 65F99
Mathematics Subject Classification ID: 74C05
zbMATH DE Number: 7337864
zbMATH Keywords: model order reduction
zbMATH Keywords: low rank approximation
zbMATH Keywords: surrogate modelling
zbMATH Keywords: response surface
describes a project that uses: PRMLT
describes a project that uses: Scikit
describes a project that uses: FEAP
MaRDI profile type: Publication
full work available at URL: j.cma.2020.113368
OpenAlex ID: W3091642552
cites work: POD-Galerkin approximations in PDE-constrained optimization
cites work: Proper orthogonal decomposition for optimality systems
cites work: An Adaptive Way of Choosing Significant Snapshots for Proper Orthogonal Decomposition
cites work: Anhpcertified reduced basis method for parametrized parabolic partial differential equations
cites work: An algorithmic comparison of the hyper-reduction and the discrete empirical interpolation method for a nonlinear thermal problem
cites work: POD-based model reduction with empirical interpolation applied to nonlinear elasticity
cites work: A Multilinear Singular Value Decomposition
cites work: Tensor-Train Decomposition
cites work: A new scheme for the tensor representation
cites work: An introduction to hierarchical (\(\mathcal H\)-) rank and TT-rank of tensors with examples
cites work: Hierarchical Singular Value Decomposition of Tensors
cites work: Tensor Decompositions and Applications
cites work: Tensor Spaces and Numerical Tensor Calculus
cites work: A literature survey of low-rank tensor approximation techniques
cites work: Black box approximation of tensors in hierarchical Tucker format
cites work: Multilevel Monte Carlo Methods
cites work: A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data
cites work: Historical Development of the Newton–Raphson Method
cites work: Dimensional model reduction in nonlinear finite element dynamics of solids and structures
cites work: A comparison of projection-based model reduction concepts in the context of nonlinear biomechanics
cites work: Turbulence, Coherent Structures, Dynamical Systems and Symmetry
cites work: The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview
cites work: A training set and multiple bases generation approach for parameterized model reduction based on adaptive grids in parameter space
cites work: Barycentric Lagrange Interpolation
cites work: The numerical stability of barycentric Lagrange interpolation
cites work: A theory of pseudoskeleton approximations
cites work: Fast monte-carlo algorithms for finding low-rank approximations
cites work: Efficient algorithms for CUR and interpolative matrix decompositions
cites work: The maximal-volume concept in approximation by low-rank matrices
cites work: Q3086656
cites work: Pseudo-skeleton approximations with better accuracy estimates
cites work: Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young'' decomposition
cites work: Parallel tensor sampling in the hierarchical Tucker format
cites work: Hierarchical Tensor Approximation of Output Quantities of Parameter-Dependent PDEs
cites work: Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs
cites work: A weighted POD method for elliptic PDEs with random inputs
cites work: Nonlinear dynamics by mode superposition
cites work: Nonlinear model order reduction based on local reduced-order bases
cites work: POD-DEIM model order reduction for strain-softening viscoplasticity
cites work: Evidence theory-based reliability optimization design using polynomial chaos expansion
cites work: On the convergence of generalized polynomial chaos expansions
cites work: The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
cites work: A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
cites work: Q5396710
cites work: Q5483032
cites work: Optimization on the hierarchical Tucker manifold - applications to tensor completion
cites work: Multilevel tensor approximation of PDEs with random data
cites work: Computation of the output of a function with fuzzy inputs based on a low-rank tensor approximation
DOI: 10.1016/J.CMA.2020.113368
description: scientific article; zbMATH DE number 7337864