CFDPython
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CFDPython  research  

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Jupyter Notebook  TeX  
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CFDPython
 Which one is best for numerical simulations for fluid mechanics [mostly linear terms].

Poisson's Equation is the most powerful tool not yet in your toolbox
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 NavierStokes 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 SpalartAllmaras model:
https://www.cfdonline.com/Wiki/Introduction_to_turbulence/R...

Complexity Explained
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 SpiderMan points at SpiderMan meme.

AeroPython: Classical Aerodynamics with Python
See also by the same professor CFD Python: 12 Steps to NavierStokes: https://github.com/barbagroup/CFDPython
research

Complexity Explained
I wrote a paper called "Counting Complexity" (https://github.com/treenotation/research/tree/master/papers/...).
In it are the beginnings of a new simple universal weigh to measure complexity.
The "realworld benefits" are that you can compare 2 systems that accomplish the same problem and objectively choose the less complex one, much like you could use the measurement of "weight" to pick a lighter material for something like a plane.
What are some alternatives?
AeroSandbox  Aircraft design optimization made fast through modern automatic differentiation. Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.
AeroPython  Classical Aerodynamics of potential flow using Python and Jupyter Notebooks
Nalu  Nalu: a generalized unstructured massively parallel low Mach flow code designed to support a variety of open applications of interest built on the Sierra Toolkit and Trilinos solver Tpetra solver stack. The open source BSD, clause 3 license model has been chosen for the code base. See LICENSE for more information.
homemademachinelearning  🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
poissoncanvas  Explore poisson equation with HTML canvas
Flow  Flow is a sparse gridbased fluid simulation library for realtime applications.
poisson  Solve Poisson equation on arbitrary 2D domain using the finite element method.
wordlesolver  For educational purposes, a simple script that assists in solving the word game Wordle.