Datasets for the paper "A new paradigm for computing hydrodynamic forces on particles in Euler–Lagrange point-particle simulations"

A new paradigm for computing hydrodynamic forces on particles in Euler–Lagrange point-particle simulations
Authors: Berend van Wachem, Hani Elmestikawy, Akshay Chandran, and Max Hausmann

Description

This repository contains the data associated with the above-mentioned publication. The dataset is organized into two main folders:

1. raw_data

This folder includes the raw datasets used for deriving the correlations presented in the paper.

• data_single_particle_correlation/
  Contains data used to fit the correlation relating the filtered Reynolds number ($\tilde{\mathrm{Re}}\mathrm{p}$) to the superficial Reynolds number ($\mathrm{Re}\mathrm{s}$).
  A dedicated README.md file in this subfolder provides a detailed description of the files and data format.

• data_suspension_of_particles_correlation/
  Includes data used to fit the normalized drag force correlation as a function of:

  • volume-filtered fluid velocity: $\varepsilon_\mathrm{f}\,\bar{\boldsymbol{u}}_{f@p}$

  • volume-filtered fluid volume fraction: $\varepsilon_\mathrm{f}$

  • non-dimensional filter width: $\sigma'$

  This subfolder also contains a README.md with detailed documentation of the included data.

2. plot_data

Contains data corresponding to selected figures in the paper, along with a Python script to reproduce these plots. The script is compatible with standard scientific Python libraries (e.g., matplotlib, numpy, pandas).

Funding Acknowledgment

This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the following projects:

• Project-ID 457515061

• Project-ID 457509672

• Project-ID 422037413 – TRR 287

• Project-ID 466092867 – SPP 2331