Anomalous Platelet Transport & Fat-Tailed Distributions

Project

This project implements the statistical analysis presented in Kotsalos et al.: Anomalous Platelet Transport & Fat-Tailed Distributions (https://arxiv.org/abs/2006.11755). The python script (meta_process.py) is tailored on the tools developed by Kotsalos et al. (see: https://arxiv.org/abs/1911.03062, https://arxiv.org/abs/1903.06479). These tools for the direct numerical simulations of cellular blood flow are available as part of Palabos library (https://palabos.unige.ch/).

Execute the code

python3 meta_process.py PLTs 1.0 distros 1 49 10 10 100 600 1 tBB 50 0.125 2

# generated file
>> PLTs_1.0_distros_1_49_10_10_100_600_1_tBB_50_0.125_2.log
# from the generated file, one can study the distributions,
# and check the behaviour of the tails of PLT velocities (as presented in the paper).

1. PLTs: refers to the corpuscles to analyse (RBCs or PLTs).
2. 1.0: is the sampling window in ms (see PLTs_tau_1.0).
3. distros: refers to the type of analysis to do (MFP: Mean Free Path/Time, distros: PLT velocities distributions, MSD: Mean Square Displament & Diffusion Coefficient from DNS data, distFromWalls: average distance from walls from DNS data).
4. 1 49: wall-bounded direction, positions of walls in um.
5. 10 10: exclude this amount of um from the walls (avoid wall effects in the analysis).
6. 100 600: The DNS (Direct Numerical Simulations) was executed for 1000 ms physical time. The analysis is done between 100 and 600 ms.
7. 1: refers to the numbers of zones to split the domain.
8. tBB: top wall boundary condition for the Random Walks.
9. 50: channel lateral dimensions in um
10. 0.125: DNS fluid time step in us, according to the Lattice Boltzmann Method.
11. 2: number of cores to use in finding the tail lower bound (x_min).

See python script and paper for more details and explanations.

Few explanations

The python script reads the positions of PLTs (center of mass) through time (stored in PLTs_tau_X directory). Every file in the directory stores the individual trajectory of a PLT in the form: (t,x,y,z). This is how our simulations are built:

1. t: refers to fluid time steps. It should be multiplied by the fluid time-step to return physical time.
2. x,z: vorticity, flow directions, respectively
3. y: wall-bounded direction The above order can change with the right modifications.

The given PLTs directory inlcudes the positions of 95 platelets from a simulation executed for 1s physical time, in a box of 50^3 um^3, and constant shear rate 100 s^-1. The DNS are sampled at 1ms window, and the numerical time step is 0.125 us according to the Lattice Boltzmann Method (see paper for a complete overview).

License

This work is licensed under a Creative Commons Attribution 4.0 International License.