# \[ANN\] Kinetic.jl: advection-diffusion physics with SciML

**URL:** <https://discourse.julialang.org/t/ann-kinetic-jl-advection-diffusion-physics-with-sciml/53277>\
**Category:** Package Announcements\
**Created:** [January 13, 2021, 9:31am UTC](https://discourse.julialang.org/t/ann-kinetic-jl-advection-diffusion-physics-with-sciml/53277 "2021-01-13T09:31:34Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![vavrines](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/vavrines/32/8024_2.png) [@vavrines](https://discourse.julialang.org/u/vavrines)\
**Post date:** [January 13, 2021, 9:31am UTC](https://discourse.julialang.org/t/ann-kinetic-jl-advection-diffusion-physics-with-sciml/53277/1 "2021-01-13T09:31:34Z")

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Hi there!

I would like to announce the [Kinetic.jl](https://github.com/vavrines/Kinetic.jl), a portable finite volume toolbox for advection-diffusion type equations and scientific machine learning. It is interested in theoretical and numerical studies of many-particle systems of gases, photons, plasmas, neutrons, etc. The finite volume method (FVM) is implemented via arrays of structs (AoS). Any advection-diffusion-type equation can be solved within the framework. Special attentions have been on the Boltzmann equation (with discrete velocity and particle methods) and its asymptotic limits (Euler, Navier-Stokes, etc).

This project was initiated only for my own research, so I didn’t advertise it at the beginning. Since it becomes a rather all-sided toolbox, I’d like to introduce the current version (0.7.0) here. Anyone who is interested in applied mathematics or computational physics is welcomed to give it a try! We welcome any kind of communication and cooperation : )

The codebase is still in rapid development. Future goals include:

- support more physical models
- improve the GPU parallelization

Cheers,  
Tianbai

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [January 13, 2021, 4:13pm UTC](https://discourse.julialang.org/t/ann-kinetic-jl-advection-diffusion-physics-with-sciml/53277/2 "2021-01-13T16:13:10Z")

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Awesome to see it released! I saw the paper awhile back:

> **[Using neural networks to accelerate the solution of the Boltzmann equation](https://arxiv.org/abs/2010.13649)**
>
> One of the biggest challenges for simulating the Boltzmann equation is the evaluation of fivefold collision integral. Given the recent successes of deep learning and the availability of efficient tools, it is an obvious idea to try to substitute the...

Exciting stuff.

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**Author:** ![vavrines](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/vavrines/32/8024_2.png) [@vavrines](https://discourse.julialang.org/u/vavrines)\
**Post date:** [January 13, 2021, 4:57pm UTC](https://discourse.julialang.org/t/ann-kinetic-jl-advection-diffusion-physics-with-sciml/53277/3 "2021-01-13T16:57:24Z")

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Thx!!!  
Also put one example in the paper here ([https://github.com/vavrines/KitML.jl/blob/main/example/relaxation.jl](https://github.com/vavrines/KitML.jl/blob/main/example/relaxation.jl))  
for anyone who is interested 😊