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Reliability-Based Optimization of structural systems

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  • Markus Gasser
  • Gerhart Schuëller

Abstract

A method to carry out a Reliability-Based Optimization (RBO) of especially nonlinear structural systems is introduced. Statistical uncertainties involving both structural and loading properties are considered. The concept is based on the separation of structural reliability analyses and the optimization procedures. Two approaches are discussed, depending on the interaction of reliability analysis and mathematical programming and the way of representation of the limit state functions (LSF) of the structure. As, for cases of practical significance, the LSF is known only pointwise it is approximated by Response Surfaces (RS). For the response calculations Finite Element (FE) procedures are utilized. Failure probabilities are determined by applying variance reducing Monte Carlo simulation (MCS) techniques such as Importance Sampling (IS). Following the reliability analysis, the optimization procedure is controlled by the NLPQL algorithm. A numerical example in terms of a template ocean platform exemplifies the procedures. Copyright Physica-Verlag 1997

Suggested Citation

  • Markus Gasser & Gerhart Schuëller, 1997. "Reliability-Based Optimization of structural systems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 46(3), pages 287-307, October.
    • Handle: RePEc:spr:mathme:v:46:y:1997:i:3:p:287-307
    DOI: 10.1007/BF01194858
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    Cited by:

    1. Ma, Yuan-Zhuo & Jin, Xiang-Xiang & Wu, Xi-Long & Xu, Chang & Li, Hong-Shuang & Zhao, Zhen-Zhou, 2023. "Reliability-based design optimization using adaptive Kriging-A single-loop strategy and a double-loop one," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Yuan, Xiukai & Qian, Yugeng & Chen, Jingqiang & Faes, Matthias G.R. & Valdebenito, Marcos A. & Beer, Michael, 2023. "Global failure probability function estimation based on an adaptive strategy and combination algorithm," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Yuan, Xiukai & Lu, Zhenzhou, 2014. "Efficient approach for reliability-based optimization based on weighted importance sampling approach," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 107-114.
    4. Karadeniz, Halil & ToÄŸan, Vedat & Vrouwenvelder, Ton, 2009. "An integrated reliability-based design optimization of offshore towers," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1510-1516.
    5. Li, Fen & Lu, Zhenzhou & Feng, Kaixuan, 2021. "Improved chance index and its solutions for quantifying the structural safety degree under twofold random uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    6. Liu, Wang-Sheng & Cheung, Sai Hung, 2017. "Reliability based design optimization with approximate failure probability function in partitioned design space," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 602-611.
    7. Ling, Chunyan & Lu, Zhenzhou & Zhang, Xiaobo, 2020. "An efficient method based on AK-MCS for estimating failure probability function," Reliability Engineering and System Safety, Elsevier, vol. 201(C).

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