Data for the paper: Drag, lift and torque correlations for axi-symmetric rod-like non-spherical particles in locally linear shear flows

These are the data files for the paper: Drag, lift and torque correlations for axi-symmetric rod-like non-spherical particles in locally linear shear flows authored by: Victor Chéron, Fabien Evrard, and Berend van Wachem #Files<br> Temporally averaged drag, lift and torque coefficients are written in .txt files stored in the folder ResultsCoefficients.<br> Python scripts used to derive the correlations are stored in the folder PythonScripts.<br> Results of an example simulation are provided in the folder SimulationResults.<br> A Python script with the final correlations of the manuscript is also included. #ResultsCoefficients<br> The .txt files are split per coefficient, aspect ratio and shear rate, which can be identified by the name of the .txt file<br> The results obtained for the torque coefficient of the particle of aspect ratio 2.5 for a uniform flow configuration are given in the file:<br> ### Uniform-Torque-Angles-Size2-5.txt<br> The results obtained for the lift coefficient of the particle of aspect ratio 10 for a shear rate 0.2 configuration are given in the file:<br> ### Shear02-Lift-Angles-Size10.txt<br> In these files, the results are ordered per orientation angle and particle Reynolds number. #PythonScripts<br> The python scripts for processing the data are split among three main functions in two files:<br> - Getter.py (reads the .txt files storing the coefficients - separate functions for the drag, lift and torque coefficients - as well as fill up the missing points for spherical particles using the Kurose and Komori correlations)<br> - generalmain (calls the Getter.py function). The Getter.py is called from the generalmain.py file. (run python3<br> generalmain.py). This will return a 1D column vector ordering the variables used to derive the correlations:<br> - Coefficients<br> - Reynolds number<br> - Orientation Angle<br> - Shear rate<br> - Aspect ratio<br> - Additional coefficients. The Python script ManuscriptCorrelations.py has the correlations as derived in the manuscript. This routine can be used to query the correlations, for plotting them or using them in a simulation. <br> #SimulationResults<br> Simulation results of one case are provided:<br> - Aspect ratio 2.5, particle Reynolds number 200, orientation angle 90, Shear rate 0.2<br> The fields and particles information are stored in hdf5 file format.<br> A .xmf wrapper file is provided to read the simulation results in paraview.<br> Data up to 40 seconds of real time are provided due to storage limits. <br> This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 448292913.