An Inverse Reliability Analysis Method for Reliability-Based Design Optimization with Random and Dependent Interval Variables Constrained within Ellipsoids

Abstract

In practical design problems, interval variables exist. Many existing methods can handle only independent interval variables. Some interval variables, however, are dependent. In this work, dependent interval variables constrained within a multi-ellipsoid convex set are considered and incorporated into reliability-based design optimization (RBDO). An efficient RBDO method is proposed by employing the sequential single-loop procedure, which separates the coupled reliability analysis procedure from the deterministic optimization procedure. In the reliability analysis procedure, a single-loop optimization for the inverse reliability analysis is performed, and an efficient inverse reliability analysis method for searching for the worst-case most probable point (WMPP) is developed. The search method contains two stages. The first stage deals the situation where the WMPP is on the boundary of the feasible region, while the second stage accommodates the situation where the WMPP is inside the feasible region by interpolation. Three examples are used for a demonstration.

Department(s)

Mechanical and Aerospace Engineering

Comments

Missouri University of Science and Technology, Grant 51475425

Keywords and Phrases

Dependent interval variable; inverse reliability analysis; multi-ellipsoid convex model; reliability-based design optimization; worst-case most probable point

International Standard Serial Number (ISSN)

1029-0273; 0305-215X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Taylor and Francis Group; Taylor and Francis, All rights reserved.

Publication Date

02 Dec 2019

Link to Full Text

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