A Hybrid CFD–ML Approach for Rapid Assessment of Particle Dispersion in a Port-Industrial Environment - Repository

The current repository is deemed to share the data for the training of the ML model and the different scripts used during the preprocess and training phase. Full CFD cases cannot be shared due to the large size, however the cell centers of the mesh will be attached for reference. The files descriptions are:- particle_prediction_dataset_scalar.h5 -> it contains the data needed for training the different ML models. The structure is: X: Input features. Y: Target fields. case_names: identifier for each name. z_slices: height slice values. While the attributes: nx: 1000, grid resolution in x-direction. ny: 1000, grid resolution in y-direction. x_bounds, spatial bounds in x. y_bounds, spatial bounds in y. - best_model.pth -> it contains an example of a final model for the particles field prediction. - C_full -> OpenFOAM file created which contains the cell centers of the full size mesh. - preprocess.py -> example script for preprocessing the raw data from OpenFOAM. - train_mlp_scalar.py -> example script for training the model.