A neural network‐enhanced reproducing kernel particle method for modeling strain localization
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Publication:6070083
DOI10.1002/nme.7040arXiv2204.13821MaRDI QIDQ6070083
Jiun-Shyan Chen, Unnamed Author, Jonghyuk Baek
Publication date: 20 November 2023
Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2204.13821
Basic methods in fluid mechanics (76Mxx) Numerical and other methods in solid mechanics (74Sxx) Generalities, axiomatics, foundations of continuum mechanics of solids (74Axx)
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Cites Work
- Unnamed Item
- A phase field model for rate-independent crack propagation: robust algorithmic implementation based on operator splits
- A phase-field description of dynamic brittle fracture
- Isogeometric analysis: CAD, finite elements, NURBS, exact geometry and mesh refinement
- Modelling of cohesive crack growth in concrete structures with the extended finite element method
- An element-free Galerkin method for three-dimensional fracture mechanics
- Reproducing kernel particle methods for large deformation analysis of nonlinear structures
- Filters, reproducing kernel, and adaptive meshfree method
- Discontinuous enrichment in finite elements with a partition of unity method
- A phase-field formulation for dynamic cohesive fracture
- SciANN: a Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks
- Hierarchical deep-learning neural networks: finite elements and beyond
- Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
- Deep autoencoders for physics-constrained data-driven nonlinear materials modeling
- A physics-constrained data-driven approach based on locally convex reconstruction for noisy database
- An adaptive multiscale phase field method for brittle fracture
- An energy approach to the solution of partial differential equations in computational mechanics via machine learning: concepts, implementation and applications
- Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- Thermodynamically consistent phase-field models of fracture: Variational principles and multi-field FE implementations
- Gradient-dependent plasticity: Formulation and algorithmic aspects
- Elastic crack growth in finite elements with minimal remeshing
- Extended finite element method for three-dimensional crack modelling
- Arbitrary branched and intersecting cracks with the extended finite element method
- Reproducing kernel particle methods
- A generalized finite element method for the simulation of three-dimensional dynamic crack propagation.
- Continuous meshless approximations for nonconvex bodies by diffraction and transparency
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