A modeling and optimization method for heterogeneous objects based on complex networks theory

作者：Zhang, Denghui^*; Zhou, Yiqi; Guo, Yang

来源：Cluster Computing, 2019, 22(2): S2645-S2654.

DOI：10.1007/s10586-017-1378-2

• CAD
• Complex networks
• Mixed genetic algorithm
• 3D printing

Heterogeneous objects (HEO) which refer to product models with spatially different material compositions or structures have attracted extensive attention from different disciplines due to emerging techniques in design and manufacturing in the last decade. The recent additive manufacturing technologies have bridges the gap between the design and manufacture for HEO. The models are the core for additive manufacturing, while designing heterogeneous objects is still a complex task. In this paper, a novel HEO modeling method based on complex networks theory is first proposed. It models the hollowing Voronoi cell as nodes and force relationship among them as edges. The nodes are weighted by the stress distribution in the mode. The force-directed algorithm is applied to construct the initial porous model. A mixed genetic algorithm is then used to accurately adjust the count and distribution of porous structures, which is necessary to reduce consumption and printing costs. The volume minimized HEO model is archived finally.

• 出版日期2019-3
• 单位山东大学