Generative Pre-Trained Physics-Informed Neural Networks Implementation

Python code for solving partial differential equations (PDEs) using deep learning. Specifically, we provide implementations for solving the following PDEs

some exercises in phasefield modelling solved in MATLAB

Allen-Cahn Equation

Physics-informed neural networks (PINNs)

OpenFOAM solver for the Allen-Cahn phase field equation coupled with thermal diffusion for simulating solidification phase transformation microstructures

This repository demonstrates the use of whole array technique in Fortran programming language for phase-field codes. The codes are 2D.

A short overview of my bachelor thesis

The repository contains phase field codes using index array programming technique. The codes are 2D and are not optimized.

Implementation of the PFHub Benchmarks on Nucleation using MMSP

Spec: https://pages.nist.gov/pfhub/benchmarks/benchmark7.ipynb/

The repository contains phase field codes using internal procedures. The codes are 2D and are not optimized