JinshuaiBai / LSWR_loss_function_PINNView external linksLinks
A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics
☆59May 30, 2024Updated last year
Alternatives and similar repositories for LSWR_loss_function_PINN
Users that are interested in LSWR_loss_function_PINN are comparing it to the libraries listed below
Sorting:
- PINN program for computational mechanics☆131Apr 1, 2024Updated last year
- Physics-guided neural network framework for elastic plates☆50Mar 24, 2022Updated 3 years ago
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆73May 18, 2025Updated 8 months ago
- This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six a…☆13Nov 17, 2022Updated 3 years ago
- Physics-informed radial basis network☆36May 20, 2024Updated last year
- A Machine Learning approach to Finite Element Methods, using U-Net inspired architectures.☆30Jul 26, 2019Updated 6 years ago
- ☆46Nov 27, 2023Updated 2 years ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network☆19Nov 26, 2025Updated 2 months ago
- In this project I use the generated dataset of stress analysis results of FVM method to train a Convolutional Neural Netwrok (CNN) model …☆28Aug 2, 2018Updated 7 years ago
- A place to share problems solved with SciANN☆304Nov 6, 2023Updated 2 years ago
- physics-informed neural network for elastodynamics problem☆154Jan 20, 2022Updated 4 years ago
- Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural …☆12Sep 27, 2024Updated last year
- ☆18Dec 22, 2025Updated last month
- A program for solving nonlinear boundary value problems in solid mechanics with nonlinear material behaviour and large deformation.☆12Jun 19, 2023Updated 2 years ago
- ☆12Dec 13, 2024Updated last year
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆45Aug 17, 2024Updated last year
- MATLAB codes for the RPIM-NNS☆14Jun 26, 2024Updated last year
- Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms☆12Nov 4, 2024Updated last year
- This is the code of my master thesis.☆184Feb 7, 2026Updated last week
- Neural network hyperelastic constitutive modeling of anisotropic materials. Includes UMAT☆26Jul 7, 2021Updated 4 years ago
- ☆13Dec 5, 2022Updated 3 years ago
- Neural Network Approach for Elastoplastic Constitutive Modeling☆25May 17, 2023Updated 2 years ago
- Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…☆15Apr 12, 2024Updated last year
- Implementation of a ResUNet-based DeepONet for predicting stress distribution on variable input geometries subject to variable loads. A R…☆19Jul 20, 2023Updated 2 years ago
- Physics-informed deep learning for structural dynamics under moving load☆19Oct 4, 2024Updated last year
- 3D FEM code (matlab)☆34Mar 17, 2024Updated last year
- A deep energy method (DEM) to solve J2 elastoplasticity problems in 3D.☆27Jan 20, 2023Updated 3 years ago
- Meshless methods for Computational Mechanics☆18Apr 26, 2022Updated 3 years ago
- FEM enhanced neural network☆20Nov 27, 2022Updated 3 years ago
- A Jupyter Notebook implementation of Physics-informed neural network to solve solid mechanics problem.☆25May 11, 2023Updated 2 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆206Feb 21, 2023Updated 2 years ago
- Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆393Aug 12, 2024Updated last year
- Deep learning for Engineers - Physics Informed Deep Learning☆363Dec 20, 2023Updated 2 years ago
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆20Jan 15, 2022Updated 4 years ago
- Adaptive phase field modeling of fracture using deep energy minimization.☆39Mar 29, 2021Updated 4 years ago
- Constitutive modeling · Deep learning · History-dependent materials · Recurrent neural networks · Viscoelasticity☆19Mar 20, 2025Updated 10 months ago
- Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material proper…☆23Jul 3, 2023Updated 2 years ago
- Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks☆34Feb 29, 2020Updated 5 years ago