Open Access

ARTICLE

An Efficient Reliability-Based Optimization Method Utilizing High-Dimensional Model Representation and Weight-Point Estimation Method

by Xiaoyi Wang¹, Xinyue Chang², Wenxuan Wang^1,*, Zijie Qiao³, Feng Zhang^3,*

1 School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China
2 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China
3 School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an, China

* Corresponding Authors: Wenxuan Wang. Email: ; Feng Zhang. Email:

(This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)

Computer Modeling in Engineering & Sciences 2024, 139(2), 1775-1796. https://doi.org/10.32604/cmes.2023.043913

Received 15 July 2023; Accepted 25 October 2023; Issue published 29 January 2024

Abstract

The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested loop reliability optimization model is completely transformed into a deterministic design optimization model that can be solved by a series of mature constrained optimization methods without any additional calculations. Two numerical examples of a planar 10-bar structure and an aviation hydraulic piping system with 28 design variables are analyzed to illustrate the performance and practicability of the proposed method.

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Keywords

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