A framework for self-evolving computational material models inspired by deep learning
From MaRDI portal
Publication:6495609
DOI10.1002/NME.6177MaRDI QIDQ6495609
Publication date: 30 April 2024
Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)
nonlinear finite element analysismultiscale analysismachine learningdeep learningdata-driven simulation
Numerical and other methods in solid mechanics (74Sxx) Artificial intelligence (68Txx) Material properties given special treatment (74Exx)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Eigendeformation-based reduced order homogenization for failure analysis of heterogeneous materials
- A multilevel finite element method (FE\(^{2}\)) to describe the response of highly nonlinear structures using generalized continua.
- Nonuniform transformation field analysis
- Three-dimensional bridging scale analysis of dynamic fracture
- Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials
- Data-driven computational mechanics
- Reduced basis hybrid computational homogenization based on a mixed incremental formulation
- Diffusion maps, spectral clustering and reaction coordinates of dynamical systems
- Multilayered grouping parallel algorithm for multiple-level multiscale analyses
- Human-level concept learning through probabilistic program induction
- Continuum Thermodynamics
- Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables
- An enhanced genetic algorithm for structural topology optimization
- The dynamics of a changing range genetic algorithm
- Detection and quantification of flaws in structures by the extended finite element method and genetic algorithms
- An efficient coarse-grained parallel algorithm for global-local multiscale computations on massively parallel systems
- A neural algorithm for a fundamental computing problem
- Superhuman AI for heads-up no-limit poker: Libratus beats top professionals
- Prior Probabilities
- Smoothing spline ANOVA models
This page was built for publication: A framework for self-evolving computational material models inspired by deep learning