Session: 04-02-03 Rigid Risers III

Paper Number: 79084

79084 - Weight Optimisation of Steel Catenary Riser Using Genetic Algorithm and Finite Element Analysis 

Steel catenary risers, SCR, are a good candidate for deepwater exploration due to their relatively low cost, less demand for subsea intervention, and compliance to the motions of the floating structures. However, SCR’s deployment in deepwater is facing challenges such as the increased top tension yielding failure and concern over fatigue performance. The objective of this paper is to achieve a global optimal weight of a steel catenary riser while ensuring its compliance to ultimate limit state ULS, yielding criteria, and fatigue limit criteria. The method explores the integration of both OrcaFlex and the genetic algorithm (GA). OrcaFlex is known for its capability in conducting global dynamic analysis of marine systems, while genetic algorithm (GA) is used as the optimization technique for the global optimal solution searched, because of its capability in handling a variety of complex nonlinear optimization problems and to self-moderate the number of calls to the fitness function and constraint thereby reducing the computation time. The total structural weight is the objective function, and the yielding failure criteria, ultimate limit state (ULS), and fatigue limit state (FLS) are employed as nonlinear constraints. In order to accurately assess the strength requirements, OrcaFlex is used to predict the dynamic responses and fatigue life of the SCR. An interface between GA and OrcaFlex has been programmed in MALAB to exchange data iteratively until an optimal solution is searched. The wall thickness, length, and declination angle at the hanging-off point are chosen as design variables due to their strong influence on the configuration and dynamic responses of an SCR. This method was illustrated using a prospective 10-inch SCR to be installed in 2000 meters deepwater offshore field off the coast of the oil-rich Niger Delta region, Nigeria. The obtained results have shown to be an effective method in searching for the optimum solution as it shows a 13 percent reduction in the total riser weight.

KEYWORDS: Finite element analysis, OrcaFlex, Genetic algorithm, Optimization, Steel catenary riser

Presenting Author: Joshua Abam Newcastle University

Authors:

Joshua Abam Newcastle University
Yongchang Pu Newcastle University
Zhiqiang Hu Newcastle University