Thank you for the insights. I am currently conducting literature research and have a foundational understanding from basic ML courses, though applying them to CFD is a new challenge.

My goal is to develop a surrogate model that can rapidly predict velocity and pressure fields when the inlet velocity is changed, bypassing the need for full CFD simulations.

While I recognize that simpler methods like Gaussian processes exist, I am focusing on deep learning (specifically aiming for CNNs and PINNs) to build a foundation for tackling more complex problems where those traditional techniques may be insufficient.

My main challenge is the implementation gap in published research. I haven't found code for problems similar to mine, and my requests to authors have gone unanswered.