We conduct fundamental research in fluid mechanics. We aim to explain the physical mechanisms of multi-phase and wall-bounded turbulent flows with applications in aerodynamics and propulsion. To that end, we develop numerical methods and algorithms for parallel supercomputers for state-of-the-art Direct Numerical Simulations (DNS) and Large-Eddy Simulations (LES) of turbulent flows using high-performance computing (HPC) and artificial neural networks (ANN).

We have recently discovered a new law of fluid mechanics – the law of incipient separation (AIAA J. 2021 & PoF 2023). We have developed “Fast” numerical methods for flows over curved surfaces (FastRK3 – JCP 2020) and multiphase flows (FastP* – JCP 2014; FastRK3P* – JFM 2023) which are tens of times faster than previous methods while preserving the computational accuracy. We have explained the physical mechanisms in droplet-laden homogeneous  isotropic and shear turbulence (JFM 2016 & JFM 2023), and, for such flows, we have developed a new LES approach for droplet-laden flows mixed with artificial neural networks (MANN-LES – IJMF 2021).

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