Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

Opgenoord, Max M.  J.; Allaire, Douglas L.; Willcox, Karen E.

doi:10.1115/1.4034224

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

Journal Article · Mon Sep 12 00:00:00 EDT 2016 · Journal of Mechanical Design

DOI:https://doi.org/10.1115/1.4034224· OSTI ID:1423944

Opgenoord, Max M. J. ^[1]; Allaire, Douglas L. ^[2]; Willcox, Karen E. ^[3]

Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Aeronautics and Astronautics; Massachusetts Institute of Technology
Texas A & M Univ., College Station, TX (United States). Dept. of Mechanical Engineering
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Aeronautics and Astronautics

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.

View Accepted Manuscript (DOE)

Research Organization:: Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

Grant/Contract Number:: SC0009297; SC0009637

OSTI ID:: 1423944

Journal Information:: Journal of Mechanical Design, Journal Name: Journal of Mechanical Design Journal Issue: 11 Vol. 138; ISSN 1050-0472

Publisher:: ASMECopyright Statement

Country of Publication:: United States

Language:: English

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