Emerging trends in machine learning for computational fluid dynamics
This is an incremental review paper that surveys the intersection of ML and CFD for researchers in these fields.
The paper discusses how emerging machine learning trends are creating opportunities to enhance computational fluid dynamics, highlighting existing synergies and assessing areas with potential future benefits.
The renewed interest from the scientific community in machine learning (ML) is opening many new areas of research. Here we focus on how novel trends in ML are providing opportunities to improve the field of computational fluid dynamics (CFD). In particular, we discuss synergies between ML and CFD that have already shown benefits, and we also assess areas that are under development and may produce important benefits in the coming years. We believe that it is also important to emphasize a balanced perspective of cautious optimism for these emerging approaches