Optimization of steel catenary risers using bio-inspired algorithms

Abstract

The design of a riser is very time consuming, since a large number of parameters (e.g.: thickness, top angle, and material properties) are involved and tight safety requirements must be met. This leads to the study of tools, such as optimization algorithms, that can speed up the process of elaborating a feasible riser project for certain conditions. Considering that some of the parameters in the design of a riser can assume a discrete set of values, the utilization of mathematical programming algorithms becomes unfeasible. It is then necessary to use metaheuristic algorithms, such as Genetic Algorithm and Particle Swarm Optimization.In this context, this paper presents a study on the application of bio-inspired algorithms,including GA and PSO, to the design optimization of steel catenary risers. The problem consists of finding the riser material and wall thickness that minimize the cost to fabricate a viable riser, in conformance with the requirements of technical standards. The main hypotheses that were adopted are presented, along with the description of the methodology employed. The results show that a significant reduction in riser cost is achieved when the riser is divided in multiple segments with different thickness and material. The efficiency of the utilized algorithms in finding an optimum riser design for the specified conditions is onfirmed by the obtained numerical results.