Efficient sampling approaches for stochastic response surface method

Gaorong Sun*, Fenfen Xiong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Stochastic response surface methods (SRSM) based on polynomial chaos expansion (PCE) has been widely used for uncertainty propagation. It is necessary to select efficient sampling technique to estimate the PCE coefficients in SRSM. In this paper, the three advanced sampling approaches, namely, Gaussian Quadrature point (GQ), Monomial Cubature Rule (MCR), and Latin Hypercube Design (LHD) are introduced and investigated, whose performances are tested through several examples. It is shown that the results of UP for the three sampling approaches show great agreements to those of Monte Carlo simulation. Specifically, GQ yields the most accurate result of UP, followed by MCR and LHD, while MCR shows the best efficiency for lower PCE order.

Original languageEnglish
Title of host publicationMaterials Processing Technology II
Pages2481-2487
Number of pages7
DOIs
Publication statusPublished - 2012
Event2nd International Conference on Advanced Engineering Materials and Technology, AEMT 2012 - Zhuhai, China
Duration: 6 Jul 20126 Jul 2012

Publication series

NameAdvanced Materials Research
Volume538-541
ISSN (Print)1022-6680

Conference

Conference2nd International Conference on Advanced Engineering Materials and Technology, AEMT 2012
Country/TerritoryChina
CityZhuhai
Period6/07/126/07/12

Keywords

  • Gauss quadrature
  • Latin hypercube design
  • Mon omial cubature rule
  • Stochastic response surface method

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