Abstract
In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.
Highlights
In recent years, optimization methods have been widely used in the design of aircraft, ships, machinery and other engineering structures
To verify the applicability of the improved particle swarm optimization (IPSO) algorithm, four functions shown in formulas (13)-(16) are studied
The optimization results of the IPSO algorithm are much closer to the theoretical results with a faster convergence rate in the initial optimization
Summary
Optimization methods have been widely used in the design of aircraft, ships, machinery and other engineering structures. Intelligent optimization is a heuristic optimization algorithm with high speed and strong practical applicability It includes the genetic algorithm (GA), ant colony optimization (ACO) algorithm, particle swarm optimization (PSO) algorithm and so on. (2012), the individual evaluation value was adjusted by the PSO algorithm, and the best ship-type was obtained. (2009) built an evaluation model for collision risk factors and found the optimal collision rate by PSO algorithm. (2009) introduced the method of dynamically changing inertia weight in the velocity evolutionary equation and developed a modified PSO algorithm to study the parameter identification of a creep constitutive model of rock. Li (2012) calculated the inertia weight of the PSO algorithm by self-adaptation, proposed an improved PSO algorithm to evaluate the objective function, and obtained the best hull form. After the completion of the optimization, the best hull form is obtained
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