Structural optimization of offshore jacket platforms considering structure-pile-soil interactions, using a continuous genetic algorithm

Offshore platforms must withstand large structural, operational, and environmental loads for decades while maintaining adequate structural safety and minimizing construction costs. In this regard, structural optimization can serve as an efficient approach. In this research, a meta-innovation method, based on a genetic algorithm, is used to optimize the cross-sectional characteristics (diameter and thickness of members) of an offshore jacket-type platform. With this aim, several decision variables, including the diameter and thickness of members, were considered by defining constraints such as design criteria (stress and buckling for members and drifts of the whole platform), by adding the weight of the platform as a parameter to reflect the construction cost. As minimizing the weight of the platform may affect its stability on the seabed, the nonlinear effect of structure-pile-soil interaction on the optimization process is also considered. To model this interaction, nonlinear P-y, T-z, and Q-z springs have been considered, based on API standards and the geotechnical characteristics of the soil. The results show that considering the structure-pile-soil interaction results in more accurate results. In other words, the dynamic properties of the platform, influenced by the soil-pile interaction, will alter the optimization of the jacket platform to reduce its structural cost.