Journal of Shanghai Jiaotong University ›› 2020, Vol. 54 ›› Issue (6): 584-591.doi: 10.16183/j.cnki.jsjtu.2019.062

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Uncertainty Quantification for CFD Simulation of Stochastic Drag Flow Based on Non-Intrusive Polynomial Chaos Method

XIA Li a,ZOU Zaojian a,b,YUAN Shuai a,ZENG Zhihua a   

  1. a. School of Naval Architecture, Ocean and Civil Engineering; b. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Online:2020-06-28 Published:2020-07-03

Abstract: 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.

Key words: uncertainty quantification, computational fluid dynamics (CFD), polynomial chaos method, Latin hypercube sampling

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