One-way coupled Lagrangian Particle Tracking for CFD simulations. Includes many auxiliary tools.
Project description
project-arrakis
Python based particle tracking algorithms for CFD data
A highly parallelized set of Lagrangian particle tracking (LPT) algorithms based on Python to post-process steady and unsteady CFD data. An advanced programming interface (API) is developed for uncertainty quantification of optical velocimetry data.
Installation:
Run the following command in the terminal to install the package:
pip install project-arrakis
LPT Algorithms:
A sample code to start off is presented in main.py
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file project_arrakis-0.1.2-py3-none-any.whl.
File metadata
- Download URL: project_arrakis-0.1.2-py3-none-any.whl
- Upload date:
- Size: 45.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
23dd36890f0e57a6e965b44c4434ce8846250b0d1166fa5763ebaa94efb7d508
|
|
| MD5 |
ef6f144a5905cc9d8bf5f73051e3e534
|
|
| BLAKE2b-256 |
cdaec659456f4e51881e2f736a27e8997c87d87a85b098a50c9cfd7f52f03c9b
|
