[JohnFen]

Your grad school project sounds very similar, yes, although we work with discrete objects rather than fluids. Fluid dynamics is much, much more complicated.

We actually use more than one neural network for this. The software is designed so the NN component is a plugin. The reason we do this is because some types of neural nets work better for some tasks than others.

Most (but not all) of our nets are convolutional.

Since you've already done some work with this sort of thing, I'm unsure about what level of overview would be of value to you, but this looks reasonable for a technically competent person who is new to the topic:

https://towardsdatascience.com/a-comprehensive-guide-to-conv...

As with all neural nets, the "secret sauce" isn't the code, it's the training.