Analytical variance-based global sensitivity analysis in simluation-based design under uncertainty

Wei Chen*, Ruichen Jin, Agus Sudjianto

*Corresponding author for this work

Research output: Contribution to conferencePaper

4 Scopus citations

Abstract

The importance of sensitivity analysis in engineering design cannot be over-emphasized. In design under uncertainty, sensitivity analysis is performed with respect to the probabilistic characteristics. Global sensitivity analysis (GSA), in particular, is used to study the impact of variations in input variables on the variation of a model output. One of the most challenging issues for GSA is the intensive computational demand for assessing the impact of probabilistic variations. Existing variance-based GSA methods are developed for general functional relationships but require a large number of samples. In this work, we develop an efficient and accurate approach to GSA that employs analytic formulations derived from metamodels of engineering simulation models. We examine the types of GSA needed for design under uncertainty and derive generalized analytical formulations of GSA based on a variety of metamodels commonly used in engineering applications. The benefits of our proposed techniques are demonstrated and verified through both illustrative mathematical examples and the robust design for improving vehicle handling performance. global sensitivity analysis, metamodeling, simulation-.

Original languageEnglish (US)
Pages953-962
Number of pages10
StatePublished - Dec 1 2004
Event2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Salt Lake City, UT, United States
Duration: Sep 28 2004Oct 2 2004

Other

Other2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CountryUnited States
CitySalt Lake City, UT
Period9/28/0410/2/04

Keywords

  • Analytical formulation
  • Based design
  • Tensor basis product function
  • Uncertainty

ASJC Scopus subject areas

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Chen, W., Jin, R., & Sudjianto, A. (2004). Analytical variance-based global sensitivity analysis in simluation-based design under uncertainty. 953-962. Paper presented at 2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, UT, United States.