Physics informed self-supervised segmentation of elastic composite materials
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Publication:6641894
DOI10.1016/j.cma.2024.117355MaRDI QIDQ6641894
Petr Dokládal, Cristian Ovalle, Etienne Decenciere, Lucien Laiarinandrasana, Guilherme Basso Della Mea
Publication date: 21 November 2024
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Random materials and composite materials (74A40) Numerical and other methods in solid mechanics (74S99) Elastic materials (74Bxx)
Cites Work
- A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics
- Recurrent neural networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step
- Transfer learning based multi-fidelity physics informed deep neural network
- A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions
- Physics informed neural networks for continuum micromechanics
- Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
- Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- Object-Oriented Programming Applied to the Finite Element Method Part II. Application to Material Behaviors
- Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks
- Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities
- On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs
- Enhanced physics‐informed neural networks for hyperelasticity
- Data-driven nonparametric identification of material behavior based on physics-informed neural network with full-field data
- Meshless physics-informed deep learning method for three-dimensional solid mechanics
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