Uncertainty Propagation Using Conditional Random Fields in Large-Eddy Simulations of Scramjet Computations

Abstract

The development of scramjet engines is crucial for attaining efficient and stable propulsion under hypersonic flight conditions.Design for well-performing scramjet engines requires accurate flow simulations in conjunction with uncertainty quantification (UQ).We advance the start-of-the-art in bringing together UQ and large-eddy simulations for scramjet computations, with a focus on the HIFiRE Direct Connect Rig combustor.In particular, we perform uncertainty propagation for spatially dependent "fiele quantities of interest by treating them as random fields, and numerically compute low-dimensional Karhunen-Loeve expansions (KLEs) using a finite number of simulations on non-uniform grids.We also describe a formulation and procedure to extract conditional KLEs that characterize the stochasticity induced by uncertain parameters at given designs.This is achieved by building a single KLE via samples drawn jointly from the parameter and design spaces, and leverage polynomial chaos expansions to insert input dependencies into the KLE.The ability to access conditional KLEs will be immensely useful for subsequent efforts in design optimization under uncertainty.

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