CFDPython VS poisson

There are many different ways to do what you'd like. The easiest starting point would probably be this tutorial: https://github.com/barbagroup/CFDPython

But that won't handle turbulence. The real "turbulence problem" is that computing actual turbulent flows requires enormous computational resources. So instead of solving the Navier-Stokes equations, related equations with lower computational cost are solved. Because of how these equations are developed, they require modeling of "unclosed" terms, and this is a likely source of inaccuracy.

If you want something relatively simple, you could take the RANS approach and use the Spalart-Allmaras model:

https://www.cfd-online.com/Wiki/Introduction_to_turbulence/R...

https://www.cfd-online.com/Wiki/Spalart-Allmaras_model

I sniff an air of condescension; what’s your goals therein? Are you posturing your ‘maths’ knowledge?

I thought I was explicit in my criticism of “notation only” explanations, but perhaps a positive example would be more explicit.

https://github.com/barbagroup/CFDPython

This repo explains computational fluid dynamics (an example of a complex system!) from “what is a python function” to “2d Navier stokes”.

It shows the work of how to discretize ‘latex beautified’ notation, shows the relationship between the computations and the notation, and even explains when their LaTex strays from “conventional use of notation” and why.

The authors even throw in traditional handwritten board lecture videos if that helps you learn better.

complexityexplained reads like it’s written by the Spider-Man points at Spider-Man meme.

See also by the same professor CFD Python: 12 Steps to Navier-Stokes: https://github.com/barbagroup/CFDPython

Here is my implementation in python of the Poisson equation on an arbitrary 2D domain using the finite element method. I used this for teaching a course in partial differential equations:

https://github.com/daleroberts/poisson