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Article
Probabilistic Sensitivity Analysis in Engineering Design Using Uniform Sampling and Saddlepoint Approximation
SAE Technical Papers
  • Agus Sudjianto
  • Xiaoping Du, Missouri University of Science and Technology
  • Wei Chen
Abstract

Sensitivity analysis plays an important role to help engineers gain knowledge of complex model behaviors and make informed decisions regarding where to spend engineering effort. In design under uncertainty, probabilistic sensitivity analysis (PSA) is performed to quantify the impact of uncertainties in random variables on the uncertainty in model outputs. One of the most challenging issues for PSA is the intensive computational demand for assessing the impact of probabilistic variations. An efficient approach to PSA is presented in this article. Our approach employs the Kolmogorov-Smirnov (KS) distance to quantify the importance of input variables. The saddlepoint approximation approach is introduced to improve the efficiency of generating cumulative distribution functions (CDFs) required for the evaluation of the KS distance. To further improve efficiency, optimized uniform samples are used to replace the direct Monte Carlo simulations for determining the cumulant generating function (CGF) in saddlepoint approximation. Efficient construction of a uniform design necessary to generate the “best” samples in a multidimensional space is presented. Our approach is illustrated with a structural design problem. It has the potential to be the most beneficial for high dimensional engineering design problems that involve expensive computer simulations. Copyright © 2005 SAE International.

Department(s)
Mechanical and Aerospace Engineering
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2005 SAE International (Society of Automotive Engineers ), All rights reserved.
Publication Date
1-1-2005
Citation Information
Agus Sudjianto, Xiaoping Du and Wei Chen. "Probabilistic Sensitivity Analysis in Engineering Design Using Uniform Sampling and Saddlepoint Approximation" SAE Technical Papers (2005)
Available at: http://works.bepress.com/xiaoping-du/52/