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Dependency effect on the reliability-based design optimization of complex offshore structure

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  • Okoro, Aghatise
  • Khan, Faisal
  • Ahmed, Salim

Abstract

A tradeoff between cost and safety is essential in the reliability-based design of offshore support structures operating in uncertain harsh environments. This study proposes a dependence-based double-loop optimization framework for complex structural systems under such environmental conditions. It considers the dependency of the environmental variables using a Drawable Vine (D-vine) copula. The reliability (inner loop of the design cycle) is modeled using the adaptive Polynomial Chaos Kriging (PCK) as a metamodel. The study employs a hybrid optimization approach that combines Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) in the outer loop optimization phase. The dependency effect is demonstrated on a steel column and a deep water segmented Steel Catenary Riser (SCR) at various hang angles to the offshore structure. The study shows the importance of multivariate dependence modeling in Reliability-Based Design Optimization (RBDO). It also highlights the significance of: (i) optimal copula selection, (ii) the impact of variable order in the D-vine copula's dependence tree, and (iii) the efficiency provided by the PCK metamodel. The method described in this paper provides a road map for a dependency-based optimal design of complex ocean structures. Also, it allows for strategic design decision-making under uncertainty, considering cost and safety.

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  • 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).
    • Handle: RePEc:eee:reensy:v:231:y:2023:i:c:s095183202200641x
    DOI: 10.1016/j.ress.2022.109026
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    4. Jiang, Zhiyuan & Huang, Xianzhen & Wang, Bingxiang & Liao, Xin & Liu, Huizhen & Ding, Pengfei, 2024. "Time-dependent reliability-based design optimization of main shaft bearings in wind turbines involving mixed-integer variables," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

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