Non-intrusive semi-analytical uncertainty quantification using Bayesian quadrature with application to CFD simulations
File(s)
Accepted version
Author(s)
Duan, Yu
North Ridao, Miriam
Eaton, Matthew
Bluck, Michael
Type
Journal Article
Abstract
To improve the safety, reliability, and performance of complex engineering systems, it is crucial to understand and quantify uncertainties. This paper presents a framework to non-intrusively and semi-analytically quantify the parametric uncertainty within CFD simulations using Bayesian quadrature (BQ). An in-house uncertainty quantification (UQ) code based upon this mathematical framework is developed. The code is then validated by applying it to quantify the uncertainty due to a varying parameter in a simple analytical test function. The mean and variance obtained using BQ are compared with those obtained from the analytical solution and stochastic simulation using the Latin hypercube sampling (LHS) method. The validation test case shows that BQ outperforms the LHS approach in terms of computational efficiency and accuracy. The UQ code is then utilised to characterise the uncertainty (due to the unknown inlet flow profile) of CFD predicted operating parameters of an industrial scale butterfly valve, as well as the uncertainties (due to the unknown high-wavenumber damping factor ) of a SAS-SST simulated bluff-body flow. It is found that the entry flow profile presents non-ignorable effects on the valve operating parameters. Meanwhile, the variance of the valve operating parameters changes with the valve opening. For the bluff-body flow, large variances of predicted flow properties exist in the region where the separate shear layer dominates because of varying. Moreover, the effect of is more significant on the turbulence quantities, as it acts on the generation of turbulent eddies directly.
Date Issued
2022-02-01
Date Acceptance
2021-12-07
Citation
International Journal of Heat and Fluid Flow, 2022, 93, pp.1-17
ISSN
0142-727X
Publisher
Elsevier BV
Start Page
1
End Page
17
Journal / Book Title
International Journal of Heat and Fluid Flow
Volume
93
Copyright Statement
© 2021 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/T003332/1
Subjects
Mechanical Engineering & Transports
0901 Aerospace Engineering
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
Publication Status
Published
Article Number
108917
Date Publish Online
2021-12-21