Research

Our research group is dedicated to solving challenges in the physics and modeling of fluid applications for aerospace using transformative methods. We integrate mathematical theory with high-performance numerical simulations and experiments to address complex problems across a broad spectrum—from UAVs and commercial airliners to hypersonic vehicles.

  • Methods for causal learning, model discovery & control of chaotic systems

  • A.I. closure models for computational fluids in aerospace

  • Dynamics of turbulent flows

Screen Shot 2021-02-03 at 21.20.33.png

Methods for causal learning, model discovery & control of chaotic systems

  • Information-theoretic formulation of causality, modeling & control

  • Causal learning for analysis of complex systems

  • Causality-preserving model discovery for prediction of chaotic systems

  • Causality-driven control of chaotic systems

  • Quantum computing algorithms for chaotic solutions

 

A.I. closure models for computational fluids in aerospace

  • Artificial Intelligence closure model discovery for large-eddy simulation

  • Applications to UAVs, commercial airliners, rotorcraft, supersonic & hypersonic vehicles.

AI_v3.png
caus.jpg

Dynamics of turbulent flows

  • Fundamental understanding of turbulent flows: scaling laws, underlying physical mechanisms, conceptual models,…

  • Non-equilibrium turbulence: pressure gradients effects, flow separation, statistically unsteady effects, wall roughness, compressibility effects,…