Flow-Aware Simulation Technique (FAST) for AI-Enabled, Physics-Integrated Turbulence Computations

Data-driven approaches have generated tremendous excitement in turbulence modeling, but enthusiasm has often outpaced scientific rigor. Many current AI/ML turbulence models lack physical interpretability, exhibit limited generalizability across flow regimes, and do not reflect the true dynamical nature of turbulence. A new strategy is needed—one that leverages AI while remaining fully compliant with the physics of flow evolution. This talk proposes a flow-aware AI paradigm that integrates data-driven learning with physical constraints and local flow-regime awareness. Recognizing that turbulence spans a wide spectrum of coherent and stochastic behaviors, we propose an adaptive framework that allows AI to dynamically select modeling pathways—switching between physics-based closures and selective scale resolution as conditions demand. This approach improves robustness in complex flow regimes, enabling AI to enhance rather than replace traditional models. The presentation will clarify the limitations of current ML methods and illustrate how physics-aware hybridization can accelerate accurate and efficient turbulence simulations. The goal is not to abandon classical turbulence modeling, but to augment it with AI-enabled predictive insight, producing simulations that are consistently reliable, interpretable, and deployment-ready in unseen flows. 

Speaker : Prof. Sharath Girimaji

Biography:

Dr. Sharath S. Girimaji is a Professor of Aerospace Engineering and Department Head of Ocean Engineering at Texas A&M University, where he holds the Wofford Cain Chair position. His research expertise spans turbulence modeling, computational fluid dynamics, compressible and high-speed flows, and complex fluid dynamics. Dr. Girimaji received his B.Tech from Indian Institute of Technology Madras (1983) and his M.S. and Ph.D. from Cornell University (1990). Before joining academia, he spent nine years as a research scientist at NASA Langley Research Center. He has graduated 25 PhD students to date. He is a Fellow of the American Physical Society (APS) and an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA).