An efficient approach for quantifying parameter uncertainty in the SST turbulence model
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Publication:667443
DOI10.1016/j.compfluid.2019.01.017zbMath1410.76140OpenAlexW2908649920MaRDI QIDQ667443
Publication date: 12 March 2019
Published in: Computers and Fluids (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.compfluid.2019.01.017
Bayesian inferenceuncertainty quantificationsurrogate modelhigh dimensional model representationRANS turbulence modelGaussian process machine learning
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