Machine learning techniques for presumed PDF models in combustion

This project examines different machine learning techniques for the modeling of mixture fraction and progress variable joint probability density functions.

Python environment and notebook

1. Install the python environment:

$ pipenv install

2. Run the Jupyter notebook, workflow.ipynb

Citation

@article{Henrydefrahan2018,
    author    = {Henry de Frahan, M. T. and Yellapantula, S. and King, R. and Day, M. and Grout, R.},
    title     = {Deep learning for presumed probability density function models},
    journal   = {arXiv:1901.05557},
    year      = {2019}
}