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Adaptive single-loop reliability-based design optimization and post optimization using constraint boundary sampling

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An Erratum to this article was published on 13 August 2018

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Abstract

The single-loop method (SLM) for reliability-based design optimization (RBDO) can be inaccurate when constraint functions are highly nonlinear because it uses gradient information calculated at the approximated most probable point (MPP) of the previous iteration. To overcome this limitation, this paper presents a new adaptive SLM (ASLM) that can automatically select the gradient at the approximate MPP of the previous iteration or the design point of the current iteration. If the design movement is large, the normalized gradient is calculated at the current design point, and the approximate MPP is calculated using the mean value method, and if small, the gradient is calculated at the approximate MPP of the previous iteration. In this study, a post optimization (PO) technique using constraint boundary sampling (CBS) is also proposed to improve the accuracy of ASLM. In the proposed method, ASLM is performed first, and then PO is applied to find a more accurate RBDO optimum using the Kriging model generated by samples accumulated during ASLM and sequentially added by CBS when the Kriging model is not accurate enough. Numerical studies show that the proposed ASLM is more efficient than the existing RBDO methods and the proposed PO improves its accuracy.

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  • 13 August 2018

    There are two corrections to make to the original article.

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Author information

Authors and Affiliations

  1. KSLV-II R&D Head Office, Korea Aerospace Research Institute, Daejeon, 34133, Korea

    Sang-Hyeon Choi

  2. Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea

    Sang-Hyeon Choi & Ikjin Lee

  3. R&D Center, Hanwha Defense Systems, Changwon, 51540, Korea

    Gwangwon Lee

Authors
  1. Sang-Hyeon Choi
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  2. Gwangwon Lee
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  3. Ikjin Lee
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Correspondence to Ikjin Lee.

Additional information

Recommended by Associate Editor Gang-Won Jang

Sang-Hyeon Choi is a Senior Researcher of KSLV-II R&D Head Office at Korea Aerospace Research Institute (KARI), and a Ph.D. candidate of Mechanical Engineering at KAIST, Korea. He joined KARI in 2006. His current research interests include reliabilitybased design optimization and surrogate modeling.

Ikjin Lee is an Associate Professor of Mechanical Engineering at KAIST, Korea. He received his Ph.D. in Mechanical Engineering at the University of Iowa. He joined KAIST in 2013. His current research interests include system reliability analysis and design optimization, surrogate modeling, and system robustness analysis and design.

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Choi, SH., Lee, G. & Lee, I. Adaptive single-loop reliability-based design optimization and post optimization using constraint boundary sampling. J Mech Sci Technol 32, 3249–3262 (2018). https://doi.org/10.1007/s12206-018-0627-5

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