Reduced models for parietal fluxes in hypersonic rarefied flows: from bridging functions to machine learning models
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Precise calculations of the trajectory of reentry vehicle require fast reentry codes based on surrogate models instead of high fidelity flow solvers. The standard method is that of bridging functions that allow to compute the parietal coefficients as functions of their values in the limit continuous and free molecular flows and of the Knudsen number of the flow. This talk will review some standard bridging functions, and then will present recent application of Machine Learning based techniques to derive more precise models that can potentially be applied to any kind of geometry and to any level of rarefaction.
