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An integrated reliability-based design optimization of offshore towers

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  • Karadeniz, Halil
  • ToÄŸan, Vedat
  • Vrouwenvelder, Ton

Abstract

After recognizing the uncertainty in the parameters such as material, loading, geometry and so on in contrast with the conventional optimization, the reliability-based design optimization (RBDO) concept has become more meaningful to perform an economical design implementation, which includes a reliability analysis and an optimization algorithm. RBDO procedures include structural analysis, reliability analysis and sensitivity analysis both for optimization and for reliability. The efficiency of the RBDO system depends on the mentioned numerical algorithms. In this work, an integrated algorithms system is proposed to implement the RBDO of the offshore towers, which are subjected to the extreme wave loading. The numerical strategies interacting with each other to fulfill the RBDO of towers are as follows: (a) a structural analysis program, SAPOS, (b) an optimization program, SQP and (c) a reliability analysis program based on FORM. A demonstration of an example tripod tower under the reliability constraints based on limit states of the critical stress, buckling and the natural frequency is presented.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:10:p:1510-1516
    DOI: 10.1016/j.ress.2009.02.008
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    References listed on IDEAS

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    1. Norbert Kuschel & Rüdiger Rackwitz, 1997. "Two basic problems in reliability-based structural optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 46(3), pages 309-333, October.
    2. 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.
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    1. 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.
    2. ToÄŸan, Vedat & Karadeniz, Halil & DaloÄŸlu, AyÅŸe T., 2010. "An integrated framework including distinct algorithms for optimization of offshore towers under uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 847-858.
    3. Ashuri, T. & Zaaijer, M.B. & Martins, J.R.R.A. & van Bussel, G.J.W. & van Kuik, G.A.M., 2014. "Multidisciplinary design optimization of offshore wind turbines for minimum levelized cost of energy," Renewable Energy, Elsevier, vol. 68(C), pages 893-905.
    4. Okoro, Aghatise & Khan, Faisal & Ahmed, Salim, 2023. "Dependency effect on the reliability-based design optimization of complex offshore structure," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. Qiang Cheng & Hongwei Zhao & Yongsheng Zhao & Bingwei Sun & Peihua Gu, 2018. "Machining accuracy reliability analysis of multi-axis machine tool based on Monte Carlo simulation," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 191-209, January.
    6. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    7. Torii, A.J. & Lopez, R.H. & Miguel, L.F.F., 2019. "A second order SAP algorithm for risk and reliability based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    8. Liu, Zhitao & Tan, CherMing & Leng, Feng, 2015. "A reliability-based design concept for lithium-ion battery pack in electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 169-177.

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