OPTIMUM DESIGN OF COMPOSITE RISERS USING A GENETIC ALGORITHM

Abstract

Most of recent oil and gas discoveries in Brazil occurred in deepwater fields. Fiber reinforced composite materials present interesting characteristics for offshore applications, such as high specific strength and stiffness, high corrosion resistance, good thermal insula- tion, high structural damping properties, and fatigue resistance. This work deals with the optimum design of laminated composite risers using a genetic algorithm. The design of lam- inated composite risers is very difficult since the strength and stiffness of these components depend on the number of layers and the material, thickness, and orientation of each layer. Thus, the use of the conventional trial-and-error strategy is not adequate and it is necessary to apply optimization techniques. In this work the design variables are the number of layers and the thickness and orientation of each layer. A multi-objective formulation is adopted to minimize the weight and maximize the buckling safety factor of the composite riser. The opti- mization model includes strength and stability constraints and considers multiple load cases. The global analysis of the riser is carried out using the catenary equations and the stress com- putation in the critical locations is performed using the Classical Lamination Theory (CLT) and the theory of thin-walled tubes. The Tsai-Wu failure criteria is used to compute the safety factor. It is important to note that, due to manufacture constraints, the design variables can only assume discrete values. Therefore, a genetic algorithm is used for optimization since it can easily handle discrete variables. In addition to classical genetic operators, as crossover and mutation, this algorithm also includes operators specially designed to handle laminate structures, such as layer swap and layer deletion. The proposed formulation is applied in the design optimization of composite catenary risers with different water depths and top angles.