Emerging Trends in Machine Learning for Computational Fluid Dynamics
Ricardo Vinuesa, Steven L. Brunton
Abstract
The renewed interest from the scientific community in machine learning (ML) is opening many new areas of research. Here we focus on trends in ML that are providing opportunities to advance the field of computational fluid dynamics (CFD). 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.
Topics & Concepts
Computational fluid dynamicsPerspective (graphical)OptimismComputer scienceField (mathematics)Focus (optics)Data scienceManagement scienceArtificial intelligenceEngineeringAerospace engineeringPsychologyMathematicsPhysicsSocial psychologyPure mathematicsOpticsModel Reduction and Neural NetworksFluid Dynamics and Vibration AnalysisFluid Dynamics and Turbulent Flows