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Structural dynamic shape optimization and sensitivity analysis based on RKPM

机译:基于RKPM的结构动力形状优化与灵敏度分析

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A numerical method of structural dynamic shape optimization is presented by using reproducing kernel particle method (RKPM), by which the mesh distortion that exists in shape optimal method based on finite element can be eliminated completely and the optimal model for structural dynamic optimization design is built. The discreteness-based design sensitivity analysis in both natural frequency and dynamic response is proposed by using direct differentiation method and discrete derivatives on the basis of structural dynamic analysis, in which the penalty method is employed into imposing the essential boundary conditions, and the derivatives of shape functions with respect to design variables are derived. The algorithm of dynamic sensitivity analysis is testified by numerical example, and the numerical results obtained are in good agreement with those obtained using semi-analytical method and global finite differences method. Finally, by integrating the algorithm mentioned based on RKPM with parameterized descriptive method of boundary shape, two examples for structural dynamic shape optimization are performed.
机译:提出了一种基于再生核粒子法(RKPM)的结构动力学形状优化的数值方法,可以完全消除基于有限元的形状优化方法中存在的网格变形,建立结构动力学优化设计的优化模型。 。在结构动力分析的基础上,采用直接微分法和离散导数,提出了基于离散度的设计灵敏度分析方法。得出关于设计变量的形状函数。通过数值算例验证了该算法的有效性,所得到的数值结果与使用半解析法和整体有限差分法得到的数值结果吻合良好。最后,通过将基于RKPM的算法与边界形状的参数化描述方法相结合,进行了结构动力形状优化的两个示例。

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