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

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.

Automated summary

A tradeoff between cost and safety is essential in the reliability-based design of offshore support structures. This study proposes a dependence-based double-loop optimization framework for complex structural systems in uncertain harsh environments. It demonstrates the importance of multivariate dependence modeling and optimal copula selection, as well as the efficiency provided by the adaptive Polynomial Chaos Kriging (PCK) metamodel. The method described in this paper provides a road map for a dependency-based optimal design of complex ocean structures, allowing for strategic decision-making under uncertainty, considering cost and safety.