vavrines/Kinetic.jl
Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.
This tool helps engineers and scientists simulate how fluids behave, from individual particles to large-scale flows. You input the physical properties of your fluid system and the problem setup, and it provides detailed numerical simulations of fluid movement and interactions. It's designed for researchers and professionals working on complex fluid dynamics challenges.
144 stars.
Use this if you need to accurately model and simulate complex fluid behaviors and particle transport, especially when combining traditional physics with machine learning approaches.
Not ideal if you're looking for a simple, off-the-shelf fluid simulation for basic engineering problems without a need for deep customization or machine learning integration.
Stars
144
Forks
19
Language
Julia
License
MIT
Category
Last pushed
Dec 06, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/vavrines/Kinetic.jl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lululxvi/deepxde
A library for scientific machine learning and physics-informed learning
pnnl/neuromancer
Pytorch-based framework for solving parametric constrained optimization problems,...
wilsonrljr/sysidentpy
A Python Package For System Identification Using NARMAX Models
dynamicslab/pysindy
A package for the sparse identification of nonlinear dynamical systems from data
google-research/torchsde
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.