Bayesian uncertainty quantification of turbulence models based on high-order adjoint

DOI10.1016/j.compfluid.2015.07.019zbMath1390.76113OpenAlexW1014719144WikidataQ59760403 ScholiaQ59760403MaRDI QIDQ1645947

Costas Papadimitriou, Dimitrios I. Papadimitriou

Publication date: 22 June 2018

Published in: Computers and Fluids (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.compfluid.2015.07.019

zbMATH Keywords

parameter estimationturbulence modelingBayesian inferenceadjoint methodsuncertainty quantification

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical turbulence modeling (76F55)

Related Items (2)

Determining \textit{a priori} a RANS model's applicable range via global epistemic uncertainty quantification ⋮ Regularized ensemble Kalman methods for inverse problems

Uses Software

• Spalart-Allmaras

Cites Work

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