基于分布式粒子群算法的翼型优化设计

Airfoil optimization based on distributed particle swarm algorithm

  • 摘要: 采用求解N-S方程作为优化算法中的CFD分析方法,基于标准粒子群优化算法(PSO),将其与遗传算法中的选择机制相结合,形成了一种改进的基于自然选择的粒子群算法(SELPSO),以提高算法的求解精度和改善算法的全局收敛性。为改善串行粒子群算法效率低,耗机时等缺点,文中将分布式计算引入到优化设计过程中,实现了基于分布式粒子群算法的翼型设计优化系统,设计实践表明,文中发展的优化算法对优化设计系统质量和效率都有着大幅度的提高,在工程中具有很好的实用价值。

     

    Abstract: A CFD optimization method is developed by solving Navier-Stokes equations.On the basis of the particle swarm optimization(PSO) algorithm,the selection mechanism of genetic algorithm was combined to PSO.An improved particle swarm optimization algorithm(SELPSO) which based on nature selection was developed to enhance precision and improve the global convergence of the algorithm.Distributed computation was introduced to the optimization process to improve disadvantage of serial computation.The disadvantage is low efficiency.The optimization system based on distributed particle swarm algorithm was established.It was proved that the efficiency and quality of the system was greatly improved by using improved particle swarm optimization algorithm(SELPSO).

     

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