Optimization for Giant magnetostrictive smart component based on multi-objective genetic algorithm

X. Sui, Zhang-Rong Zhao, Xu-Ming Wang, Xia-Jun Meng
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Abstract

In order to machine the non-cylinder piston pinhole, a new method is proposed by applying the Giant magnetostrictive materials (GMM) component. An optimization design model combining the smart component genetic algorithm with the finite element method for GMM smart component is established. Nondominated sorting genetic algorithm (NSGA) is used to optimize the model. The optimum results show that the NSGA combining with finite element method is a good way to carry out the optimization design of GMM smart component.
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基于多目标遗传算法的超磁致伸缩智能元件优化
提出了一种利用超磁致伸缩材料(GMM)元件加工非圆柱活塞针孔的新方法。建立了GMM智能部件遗传算法与有限元法相结合的优化设计模型。采用非支配排序遗传算法(NSGA)对模型进行优化。优化结果表明,NSGA结合有限元法进行GMM智能部件的优化设计是一种很好的方法。
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