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基于改进非支配排序遗传算法的复合材料身管多目标优化 被引量:7

Multi-objective Optimization of Composite Barrel Based on the Improved Non-dominated Sorting Genetic Algorithm
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摘要 针对复合材料身管设计时多个性能指标设计要求,基于有限元模型和优化设计方法,建立了复合材料身管多目标优化模型,优化的目标为身管一阶固有频率和身管质量,复合材料各层缠绕角和缠绕厚度为优化设计变量,优化方法采用改进的非支配排序遗传算法(NSGA-Ⅱ);通过优化求解,获得了复合材料身管的Pareto最优解集;优化算例表明,采用NSGA-Ⅱ获得的Pareto前沿面曲线分布均匀,其所对应的复合材料身管设计方案在刚度和重量方面均有改善。 A multi-objective optimization model of composite barrel was developed based on the finite element model and optimization method for the multi-objective design requirements during barrel design process. The fundamental frequency and structure weight of barrel are defined as two optimiza- tion objectives. The winding angle and thickness of the composite layers are defined as design variables. And the improved non-dominated sorting genetic algorithm (NSGA- Ⅱ ) is employed as an optimization method. The Pareto solution set of composite barrel is obtained by optimal solving. The optimization examples show that the uniformly distributed Pareto front is obtained by using NSGA- Ⅱ, and the corresponding design solution of composite barrel is improved in stiffness and weight.
出处 《兵工学报》 EI CAS CSCD 北大核心 2006年第4期617-621,共5页 Acta Armamentarii
关键词 复合材料 火炮 复合材料身管 有限元 遗传算法 多目标优化 composite material gun composite barrel finite element method (FEM) genetic algorithm(GA) multi-objective optimization
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参考文献3

  • 1蔡为仑.复合材料设计[M].北京:科学出版社,1989.
  • 2Srinivas N,Deb K.Multiobjective optimization using nondominated sorting in genetic algorithms[R].Kanput:Department of Mechanical Engineering,Indian Institute of Technology,1993.
  • 3Deb K Amirt Pratap,Sameer Agarwal,Meyarivan T.A fast and elitist multiobjective genetic algorithm:NSGA-Ⅱ[J].IEEE Transactions on Evolutionary Computation,2002,6 (2):182 -197.

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