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Research Article
Aug 14, 2018

Reliability Methods for Bimodal Distribution With First-Order Approximation1

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5, Issue 1

Abstract

In traditional reliability problems, the distribution of a basic random variable is usually unimodal; in other words, the probability density of the basic random variable has only one peak. In real applications, some basic random variables may follow bimodal distributions with two peaks in their probability density. When binomial variables are involved, traditional reliability methods, such as the first-order second moment (FOSM) method and the first-order reliability method (FORM), will not be accurate. This study investigates the accuracy of using the saddlepoint approximation (SPA) for bimodal variables and then employs SPA-based reliability methods with first-order approximation to predict the reliability. A limit-state function is at first approximated with the first-order Taylor expansion so that it becomes a linear combination of the basic random variables, some of which are bimodally distributed. The SPA is then applied to estimate the reliability. Examples show that the SPA-based reliability methods are more accurate than FOSM and FORM. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4040000.

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Information

Published In

Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5Issue 1March 2019

History

Received: Nov 5, 2017
Revision received: Apr 15, 2018
Published online: Aug 14, 2018
Published in print: Mar 1, 2019

Authors

Affiliations

Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, 258A Toomey Hall, 400 West 13th Street, Rolla, MO 65409-0500 e-mail: [email protected]
Xiaoping Du [email protected]
Professor Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, 272 Toomey Hall, 400 West 13th Street, Rolla, MO 65409-0500 e-mail: [email protected]

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