stupid-cooh / Metal-Multiaxial-Fatigue-Life-Prediction-Using-Deep-Learning
This repository contains code for predicting multiaxial fatigue life of metals using deep learning models (CNN, LSTM, and GRU) combined with fully connected layers. It processes a dataset published on Materials Cloud, utilizing high-quality data to train and evaluate the models effectively.
☆14Updated 9 months ago
Alternatives and similar repositories for Metal-Multiaxial-Fatigue-Life-Prediction-Using-Deep-Learning
Users that are interested in Metal-Multiaxial-Fatigue-Life-Prediction-Using-Deep-Learning are comparing it to the libraries listed below
Sorting:
- ☆21Updated 6 months ago
- Scripts for the ANN publication submited to FEAD 2021☆13Updated 3 years ago
- ☆52Updated 2 years ago
- This repository contains the Python code for the paper "Transfer learning-based PINN model of 3D temperature field prediction for blue la…☆15Updated 9 months ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆30Updated 3 years ago
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆16Updated 3 years ago
- Adaptive phase field modeling of fracture using deep energy minimization.☆32Updated 4 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆71Updated last year
- Physics-Informed Neural Network (PINN) for Solving Direct and Inverse Heat Conduction Problems☆13Updated 2 years ago
- 复现CICP论文提出的几种改进PINN性能的方法☆19Updated last year
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- PINN program for computational mechanics☆110Updated last year
- Physics Informed Neural Networks: a starting step for CFD specialists☆31Updated 3 years ago
- Extraction of mechanical properties of materials through deep learning from instrumented indentation☆65Updated 3 years ago
- Predictive Modeling and Uncertainty Quantification of Fatigue Life in Metal Alloys using Machine Learning☆15Updated 2 months ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated 11 months ago
- Automated representative volume element simulator via abaqus for material constitutive law discovery☆20Updated 2 months ago
- CFD-DeepLearning-UNET☆14Updated 4 years ago
- Code for 'Unifying the design space of truss metamaterials by generative modeling'☆16Updated 10 months ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆32Updated 2 years ago
- Burgers equation solved by PINN in PyTorch☆21Updated 3 years ago
- The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks☆35Updated 2 years ago
- Phase-field code in MATLAB to solve the phase-field model of Fan & Chen for Grain Growth phenomena in 2D☆25Updated 4 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆15Updated 2 years ago
- ☆49Updated 5 months ago
- An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based …☆16Updated last year
- ☆38Updated 2 years ago
- A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations☆18Updated 2 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Updated 4 years ago
- Python scripts for physics-informed neural networks for corrosion-fatigue prognosis☆40Updated 2 years ago