Dataset for "Drag Correlations for Multiphase Flows Using Artificial Neural Networks"

This dataset is a supplement to the ParCFD 2024 conference contribution titled "Drag Correlations for Multiphase Flows Using Artificial Neural Networks". It contains sampling data around a settling spherical particle. The subset ANN_I was derived from a particle-resolved simulation, while the subset ANN_II was generated from a coupled forced-motion Lagrangian Particle Tracking (LPT) simulation. These datasets were used to train two Artificial Neural Networks (ANNs) to predict the resulting drag force for various particle diameter-to-cell size ratios, as described in the corresponding contribution. The dataset also includes simulation results (particle position and particle velocity) obtained when the trained ANNs were used in LPT simulations instead of traditional drag correlations. All files are provided as plain text files.