基于仿生子结构的十字交叉节点拓扑优化研究

针对十字交叉节点自重大且传统拓扑优化效果不佳的问题，应用仿生学原理提出一种仿生子结构划分方法，并进行了深入的拓扑优化及3D打印制造研究。首先通过SolidWorks软件建立十字交叉节点原始模型，并以蜂巢为仿生对象进行拓扑优化子结构划分，然后应用HyperWorks有限元软件进行给定荷载条件下的拓扑优化分析，优化目标设置为最大化刚度，约束条件设置为体积约束，其中仿生蜂巢子结构体积约束与其他次要子结构体积约束分别设置为0.8及0.2；最后通过OSSmooth模块进行FEA reanalysis处理，提取拓扑优化结果进行分析，并将拓扑节点有限元模型转化为STL文件，通过3D打印制造出拓扑节点的缩尺模型。研究结果表明：利用仿生子结构拓扑优化方法可仅使用2个子结构便快速得到最佳拓扑构型，其拓扑节点相较于原始节点最大位移降低了7.73%，最大等效应力降低了27.06%，质量降低了34.45%，应用此方法显著提升了结构优化效率和优化效果，将拓扑结果应用3D打印技术进行制造，解决了复杂形体采用传统工艺难以制造的问题。

Research on topology optimization of cross joint based on bionic substructure

Aiming at the problem of large dead weight of cross joint and poor effect of traditional topology optimization, a bionic substructure partition method was proposed based on bionics principle, and the structure topology optimization and 3D printing manufacturing of cross joint were studied. First, the original model of cross joint was established by SolidWorks software. The honeycomb was used as the bionic object to topology optimization substructures division. Then, HyperWorks finite element software was used to carry out topology optimization analysis under given load conditions. The optimization objective was set to maximize the stiffness, and the constraint condition was set to volume constraint. The volume constraints of bionic honeycomb substructure and the other secondary substructure were set to 0.8 and 0.2 respectively. Finally, FEA reanalysis was processed by OSSmooth module, and the results of topology optimization were extracted and analyzed. The finite element model of topology joint was transformed into STL file, and the scale model of topology joint was produced by 3D printing. The results show that the optimal topological configuration can be obtained quickly by using only two substructures. The maximum displacement of the topology joint is reduced by 7.73%, the maximum equivalent stress is reduced by 27.06% and the weight is reduced by 34.45% compared to the original joint. The application of this method improves the efficiency and effect significantly for structural optimization. The topology result is produced by 3D printing technology, which solves the problem that complex shape is difficult to be produced by traditional technology.