Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty
Author(s)
Allaire, Douglas L.; Opgenoord, Max Maria Jacques; Willcox, Karen E
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Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as a function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.
Date issued
2016-09Department
Massachusetts Institute of Technology. Department of Aeronautics and AstronauticsJournal
Journal of Mechanical Design
Publisher
ASME International
Citation
Opgenoord, Max M. J., Douglas L. Allaire, and Karen E. Willcox. “Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty.” Journal of Mechanical Design 138.11 (2016): 111410. © 2016 by ASME
Version: Final published version
ISSN
1050-0472