PINN-DVM

This repository contains the implementation of PINN-DVM, corresponding to:

Linying Zhang, et al.
Simulation of rarefied gas flows using physics-informed neural network combined with discrete velocity method.

Physics of Fluids 35, 077124 (2023).

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Purpose

PINN-DVM couples Physics-Informed Neural Networks (PINNs) with the Discrete Velocity Method (DVM) to solve the linearized BGK equation.
This repo reproduces the cases reported in the paper:

• Couette flow
• Fourier flow
• Triangular duct flow
• Cavity flow

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Repository Usage

Each case lives in its own folder. To run a case, cd into that folder and execute:

python main.py

Dependencies

Please install the following Python packages:

• numpy

• pandas

• matplotlib

• pyDOE

• tensorflow

TensorFlow version per case

• Couette flow & Fourier flow: tensorflow==1.10
• Triangular duct flow & Cavity flow: tensorflow==2.1

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Citation

If you use this code, please cite:

Zhang, Linying, et al. Simulation of rarefied gas flows using physics-informed neural network combined with discrete velocity method. Physics of Fluids 35, 077124 (2023). https://doi.org/10.1063/5.0156404

BibTeX

@article{10.1063/5.0156404,
    author = {Zhang, Linying and Ma, Wenjun and Lou, Qin and Zhang, Jun},
    title = {Simulation of rarefied gas flows using physics-informed neural network combined with discrete velocity method},
    journal = {Physics of Fluids},
    volume = {35},
    number = {7},
    pages = {077124},
    year = {2023},
    month = {07},
    issn = {1070-6631},
    doi = {10.1063/5.0156404},
    url = {https://doi.org/10.1063/5.0156404},
}