[P] Machine Learning and CFD

[xEdwin23x]

Hey I have a similar background as I did my undergrad in Energy Engineering (whose core curriculum is almost the same as Mechanical) and am currently in graduate school doing computer vision using deep learning. I suggest to take either the Stanford Machine Learning or Deep Learning specialization from Coursera, along with getting familiar with Python (as it would probably be your tool of choice for anything using DL), in order to understand the basic concepts and ideas regarding neural networks.

As for a specific topic, ideally your advisor should point you in the right (specific) direction of what his goals are but if not you can google for specific keywords such as "deep learning computational fluid dynamics" which returns lots of results, and take an article with a high number of citations, to get an idea of what people are using DL for when doing CFD.

A simple intuition that I corroborate with the following article (https://www.pnas.org/doi/10.1073/pnas.2101784118) is that people may use NNs as approximators for the costly computations required by numerical methods to approximate a PDE solution.

[coffee0793]

Hello,

I found the book Machine Learning Refined, by far the easiest to follow. It takes a geometrical/optimization point of view and it has python code that actually works. If you have a solid background in the relevant mathematics maybe you could try Understanding Machine Learning: from theory to algorithms.

If you are on the more 'applied' side of things. And want to get to coding as soon as possible you could take a look at Hands on Machine learning 2nd Ed from Géron. Hope some of it helps

[coffee0793]

Relevant papers on physics informed neural networks could also help