Reliability-oriented Sensitivity Analysis using Shapley Additive Explanations and Polynomial Chaos Expansion

Pramudita Satria Palar, Ashwin Renganathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper introduces a novel sensitivity metric specifically designed for reliability analysis, utilizing Shapley Additive Explanations (SHAP) from game theory. The primary objective of this study is to present a reliability-oriented sensitivity index (ROSI) called SHAP-ROSI, which enables analysts to assess the relative impact of input variables on the failure probability. Unlike conventional SHAP which deals with global domains, the proposed metric calculates averaged SHAP values only within the failure domain. Not only does SHAP-ROSI serve as a reliability-oriented sensitivity metric, but it also provides valuable insights into the underlying mechanisms of how each input contributes to the failure probability through visualization in the form of a dependence plot. We conducted experiments on a three-variable analytical problem, a six-variable truss problem, and a seven-variable transonic airfoil problem to evaluate the efficacy of the proposed metric. The results demonstrate that the ranking produced by SHAP-ROSI aligns with the widely used Sobol indices. Furthermore, the SHAP visualization offers valuable information on which variables should be controlled to minimize the failure probability.

Original languageEnglish (US)
Title of host publicationAIAA SciTech Forum and Exposition, 2024
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107115
StatePublished - 2024
EventAIAA SciTech Forum and Exposition, 2024 - Orlando, United States
Duration: Jan 8 2024Jan 12 2024

Publication series

NameAIAA SciTech Forum and Exposition, 2024


ConferenceAIAA SciTech Forum and Exposition, 2024
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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