Sizing Optimization Using Genetic Algorithm to Achieve Minimal Offshore Structure

Abstract

Accelerating marginal field development must consider the economic factor. While the structural strength must remain capable and robust when subjected to environmental loads. To meet the desired objective in design phase, optimization is used. With the rapid growth of computing technology, the optimization method is developed as more advanced and reduced iteration time. However, the structural evaluation of jacket structure is a complex problem. The usual process of structure evaluation is through finite element analysis, and it is still time-consuming. Thus, surrogate models can evaluate the structure, lowering computational time. This study optimizes the jacket structure to get an affordable and robust minimal jacket structure. Sizing optimization will be performed on the jacket's leg and bracing thickness. For single-objective optimization, weight structure is considered the objective function, and multi-objective optimization adds production cost as the second objective function. The surrogate model uses the radial basis function to predict the relation between design variables and ultimate limit strength. The functions generated from the surrogate model will act as behaviour constraints in the optimization process. For consideration, X-type and V-type bracing configurations are compared. Different results were obtained from the single objective and multi-objective optimization process.

Keywords

• genetic algorithm, jacket structure, minimal offshore structure, optimization, radial basis function