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Research Article
Apr 15, 2019

Time-Dependent Reliability-Based Robust Design Optimization Using Evolutionary Algorithm

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5, Issue 2

Abstract

Due to the uncertain and dynamic parameters from design, manufacturing, and working conditions, many engineering structures usually show uncertain and dynamic properties. During the product design and development stages, designers often encounter reliability and robustness measures of dynamic uncertain structures. Time-varying and high nonlinear performance brings a new challenge for the reliability-based robust design optimization. This paper proposes a multi-objective integrated framework for time-dependent reliability-based robust design optimization and the corresponding algorithms. The integrated framework is first established by minimizing the mean value and coefficient of variation of the objective performance at the same time subject to time-dependent probabilistic constraints. The time-dependent probabilistic constraints are then converted into deterministic constraints using the dimension reduction method. The evolutionary multi-objective optimization algorithm is finally employed for the deterministic multi-objective optimization problem. Several examples are investigated to demonstrate the effectiveness of the proposed method. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4042921.

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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 2June 2019

History

Received: Jul 18, 2018
Revision received: Feb 12, 2019
Published online: Apr 15, 2019
Published in print: Jun 1, 2019

Authors

Affiliations

School of Mechanical and Electrical Engineering; Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China e-mail: [email protected]
Zhonglai Wang [email protected]
School of Mechatronics Engineering; Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China e-mail: [email protected]
Zhihua Wang [email protected]
School of Mechanical and Electrical Engineering; Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China e-mail: [email protected]

Funding Information

National Natural Science Foundation of China10.13039/501100001809: 11472075

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