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新颖又古老的互承型结构的形状生成是其广泛应用的首要亟待解决问题.介绍了影响构型的基本参数,任意参数的变化均会造成整体形状的改变,致使传统建模方法无法有效实现这种结构模型的生成.通过对基本单元分析,探索了以遗传算法为代表的群体随机搜索方法和以Broyden-Fletcher-Goldfarb-Shanno(BFGS)拟牛顿法为代表的单点搜索优化方法解决互承结构形状生成问题的有效性.算例表明后者对指定构型及参数的互承结构成形具有更高的效率.
The shape generation of novel and ancient mutual-support structure is the most important problem to be solved widely.It is introduced that the basic parameters affect the configuration, the change of any parameter will cause the change of the overall shape, which makes the traditional modeling method can not be effectively implemented Based on the basic unit analysis, this paper explores the method of group random search represented by genetic algorithm and the single-point search optimization method represented by Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method The validity of the problem of bearing structure shape generation shows that the latter method is more efficient for forming the mutual configuration of the specified structure and parameters.