A Surrogate Accelerated Bayesian Inverse Analysis of the HyShot II Supersonic Combustion Data
نویسندگان
چکیده
We implement and assess a Markov chain Monte Carlo method with a surrogate forward computational model for determining the flight conditions of the HyShot II supersonic re-entry vehicle given pressure measurements. The surrogate models we examine are non-intrusive, i.e., sampling-based, and include (1) a dimension-reduced global polynomial surrogate, (2) ordinary Kriging, and (3) a low-rank separated representation for high-dimensional functions. We find that the errors in the specific surrogates are overwhelmed by errors due to finite sample size and the ill-posedness of the inverse problem.
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