AI/ML Implications in CFD for Aircraft Design
Hey guys, I've got about a year of experience with OpenFOAM. I've run different types of simulations — SIMPLE, PIMPLE, incompressible, compressible, laminar, turbulent — on 2D airfoils and 3D aircraft, like the NASA N2A HWB model, with decent mesh quality and case setup. The post-processed results matched the reference data pretty well. Just sharing this to give some context on where I'm at with OpenFOAM, but I'm still learning and exploring more of it.
Lately I've been seeing AI/ML being used in CFD, and since I come from a non-coding background (I'm a Mechanical Engineer), AI/ML and neural networks still feel like a black box to me. I don't really know how they work under the hood.
So I wanted to ask — how can I actually use AI/ML and neural networks in aviation-related CFD work?
For context, my future work will mostly revolve around optimization studies, detailed aircraft analysis, and static/dynamic stability analysis of aircraft. So I'm hoping to understand how AI/ML can help speed things up, and ideally how to align with whatever the industry is currently doing in this space.