This project examines different machine learning techniques for the modeling of mixture fraction and progress variable joint probability density functions.
- Install the python environment:
$ pipenv install
- Run the Jupyter notebook,
workflow.ipynb
@article{Henrydefrahan2019,
title={Deep learning for presumed probability density function models},
author={Henry de Frahan, Marc T and Yellapantula, Shashank and King, Ryan and Day, Marc S and Grout, Ray W},
journal={Combustion and Flame},
volume={208},
pages={436--450},
year={2019},
publisher={Elsevier}
}