Transformer-PINN Rock Crack Prediction

Code for paper: Mechanism of micro-damage evolution in rocks under multiple coupled cyclic stresses

Requirements

Python 3.8+, PyTorch 2.0+, numpy, pandas, scikit-learn, matplotlib

Install: pip install -r requirements.txt

Input

5D feature vector: pH (1-7), FN (5-40), FT (10-40), T (25-900), phase (0 or 1)

Output

72D angular distribution representing crack count per 5-degree bin

Usage

Training:

python train.py

Inference:

python inference.py

Files

model.py - network architecture

data_loader.py - data processing

train.py - training script

inference.py - prediction script

Physics

Mogi-Coulomb yield criterion

Weibull strength distribution

Energy-based damage evolution

D0 = 1 - (1-Dft)(1-Dch)(1-Dth)

lambda = 1 - D0