In this paper, verification & validation and uncertainty quantification in uncertainty analysis for computational fluid dynamics (CFD) simulation are compared. A state-of-the-art method for uncertainty quantification problems, i.e., the non-intrusive polynomial chaos (NIPC) method, is introduced and applied to quantifying the uncertainty of two-dimensional stochastic drag flow, together with the Monte-Carlo (MC) method. For the MC method, the random sampling (RS) method and the Latin hypercube sampling (LHS) method are adopted. The uncertainty of the stochastic drag flow induced by the inlet and outlet pressure boundaries is studied, with the boundaries treated as stochastic variables with uniform distribution. It is shown that there is no big difference between LHS and RS, and the NIPC method can simulate the uncertainty propagation better.
XIA Li, ZOU Zaojian, YUAN Shuai, ZENG Zhihua
. Uncertainty Quantification for CFD Simulation of Stochastic Drag Flow
Based on Non-Intrusive Polynomial Chaos Method[J]. Journal of Shanghai Jiaotong University, 2020
, 54(6)
: 584
-591
.
DOI: 10.16183/j.cnki.jsjtu.2019.062
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