joshiji789 / PINN-s-for-Heat-Transfer-ProblemLinks
In recent years, the use of physics-informed neural networks (PINNs) has gained popularity across several engineering disciplines due to their effectiveness in solving linear and non-linear partial differential equations (PDE) and real-world problems despite noisy data. The basic approach used to solve the PINNs is to construct the neural networ…
☆8Updated 2 years ago
Alternatives and similar repositories for PINN-s-for-Heat-Transfer-Problem
Users that are interested in PINN-s-for-Heat-Transfer-Problem are comparing it to the libraries listed below
Sorting:
- In his project, we proposed a new acquisition function for kriging-based reliability analysis, namely expected uncertainty reduction (EUR…☆11Updated 3 years ago
- Efficiently solve the 2D heat equation using a Physics-Informed Neural Network (PINN). Simulate and predict temperature distributions wit…☆11Updated last year
- This repository contains the Python code for the paper "Transfer learning-based PINN model of 3D temperature field prediction for blue la…☆16Updated 11 months ago
- PINN (Physics-Informed Neural Networks) for the 2D heat equation☆11Updated last year
- The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks☆37Updated 2 years ago
- ☆76Updated last year
- Boosting the training of physics informed neural networks with transfer learning☆26Updated 4 years ago
- ☆129Updated 2 years ago
- A Surrogate Model with Data Augmentation and Deep Transfer Learning for Temperature Field Prediction of Heat Source Layout☆10Updated 4 years ago
- Codes of our journal paper: Indirect identification of bridge frequencies using a four-wheel vehicle: Theory and three-dimensional simula…☆16Updated 3 weeks ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆90Updated last year
- ☆10Updated 2 years ago
- FEM enhanced neural network☆15Updated 2 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆35Updated 2 years ago
- This repo contains a PyTorch-based AE-ConvLSTM model for fluid flow prediction. It can forecast 5–10 time steps per forward pass and over…☆24Updated last month
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- DeepXDE and PINN☆121Updated 3 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- Research/development of physics-informed neural networks for dynamic systems☆25Updated 7 months ago
- ☆37Updated last year
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆56Updated 4 years ago
- ☆12Updated last year
- This is a PINN based approach in solving high temperature heat transfer equations in manufacturing industries, with a focus on reducing t…☆12Updated last year
- Physics-guided Convolutional Neural Network☆67Updated 4 years ago
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆16Updated 3 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆60Updated 3 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆70Updated 3 years ago
- Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network☆18Updated 4 months ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆57Updated last year
- Identification of Bouc–Wen type models using the transitional Markov chain Monte Carlo method☆11Updated 4 months ago