Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: extension to geometrical parameterizations
From MaRDI portal
Publication:2096859
DOI10.1016/j.cma.2022.115636OpenAlexW4283723537MaRDI QIDQ2096859
Karen Veroy, Francesco A. B. Silva, Theron Guo, Ondřej Rokoš
Publication date: 11 November 2022
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2206.13627
proper orthogonal decompositionshape optimizationreduced order modelingGaussian process regressioncomputational homogenizationgeometrical transformation
Micromechanics of solids (74M25) Effective constitutive equations in solid mechanics (74Q15) Mathematical modeling or simulation for problems pertaining to mechanics of deformable solids (74-10)
Related Items
Uses Software
Cites Work
- Unnamed Item
- A comparison of projection-based model reduction concepts in the context of nonlinear biomechanics
- On the computation of the macroscopic tangent for multiscale volumetric homogenization problems
- A comparative study on low-memory iterative solvers for FFT-based homogenization of periodic media
- Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations. Application to transport and continuum mechanics.
- Multi-scale computational homogenization: trends and challenges
- Nonuniform transformation field analysis
- Non-intrusive reduced order modeling of nonlinear problems using neural networks
- High-performance model reduction techniques in computational multiscale homogenization
- A numerical study of different projection-based model reduction techniques applied to computational homogenisation
- Projection-based model reduction: formulations for physics-based machine learning
- An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
- A numerical method for computing the overall response of nonlinear composites with complex microstructure
- Computational micro-to-macro transitions of discretized microstructures undergoing small strains
- Reduced order modeling for nonlinear structural analysis using Gaussian process regression
- Model-free data-driven inelasticity
- Anisotropic hyperelastic constitutive models for finite deformations combining material theory and data-driven approaches with application to cubic lattice metamaterials
- Constitutive artificial neural networks: a fast and general approach to predictive data-driven constitutive modeling by deep learning
- A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems
- A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths
- Unsupervised discovery of interpretable hyperelastic constitutive laws
- Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method
- Data-driven model order reduction for problems with parameter-dependent jump-discontinuities
- Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials
- Data driven computing with noisy material data sets
- A virtual element method for transversely isotropic elasticity
- Efficient model reduction of parametrized systems by matrix discrete empirical interpolation
- Data-driven computational mechanics
- Certified Reduced Basis Methods for Parametrized Partial Differential Equations
- Computational homogenization of nonlinear elastic materials using neural networks
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- Hyper-reduction of mechanical models involving internal variables
- 3‐D shape optimal design and automatic finite element regridding
- Transformation field analysis of inelastic composite materials
- Radial Basis Functions
- Advanced Lectures on Machine Learning
- Reduced Basis Methods for Partial Differential Equations
- On the distribution of points in a cube and the approximate evaluation of integrals
- An approach to micro-macro modeling of heterogeneous materials