Design optimization of jacket offshore platform considering fatigue damage using Genetic Algorithm

Abstract

Due to the substantial volume of materials used in the structural members of jacket platforms, weight optimization is of critical importance. A Genetic Algorithm is a powerful tool that allows for consideration of many parameters in the optimum design of platforms simultaneously, a feature hardly found in ordinary circumstances. Regarding the cyclic loads derived from waves, fatigue is one of the most fundamental issues in the design and optimization of offshore platforms. In this study, using the Genetic Algorithm, a real platform is optimized with two optimization scenarios named (CF) and (WCF). The CF-Optimization considers constraints, including fatigue life in connections, stress and buckling design requirements in structural members, horizontal displacement at the working point level, and structural adequacy control of connections, while the WCF-Optimization ignores fatigue constraint in the mentioned constraints. The results show that (CF) and (WCF) optimizations reduced the structural weight of the platform by the ratios of 13% and 15%, respectively. Moreover, an investigation of the results obtained from WCF-Optimization reveals that ignoring fatigue could significantly lead to unreliable results in the design optimization of the jacket platform.