Data-driven modelling of hypersonic flows in non-equilibrium

Abstract: At very large Mach numbers, fluid flows are strongly influenced by non-equilibrium gas effects such as finite-rate chemical reactions or internal mode excitation arising from extreme temperatures. These effects have an order-one influence on quantities of interest, such as stability properties, transition and heating and must be taken into account to achieve effective designs, reliable predictions, and successful flow control. Accurate simulations of these flows rely on detailed thermochemical gas models (look-up libraries), which dramatically increase the cost of the underlying calculations. In this talk I will first present state-of-the-art detailed simulations of such complex flows and the incurring cost, motivating the second part of the talk where I will present a novel model-agnostic data-driven technique to extract a surrogate of the thermochemical models, reducing the cost of the simulations considerably while maintaining accuracy.

Bio: Prof. Sayadi received her PhD from Stanford University at 2012. After which she spend a few years as a postdoctoral researcher in internationally renowned institutions: Ecole Polytechnique, Imperial College London and RWTH-Aachen university. Since 2018 she holds a position of Chargee de Recherche (CNRS) at Sorbonne University and is also a research group leader at ITV, RWTH Aachen University. Her research interests are in HPC, Data-driven model design and model reduction, and optimisation of interfacial and reactive flows.