Modularity is appealing for solving many problems in optimization. It brings the benefits of manufacturability and reconfigurability to structural optimization, and enables a trade-off between the computational performance of a Periodic Unit Cell (PUC) and the efficacy of non-uniform designs in multi-scale material optimization. Here, we introduce a novel strategy for concurrent minimum-compliance design of truss modules topologies and their macroscopic assembly encoded using Wang tiling, a formalism providing independent control over the number of modules and their interfaces. We tackle the emerging bilevel optimization problem with a combination of meta-heuristics and mathematical programming. At the upper level, we employ a genetic algorithm to optimize module assemblies. For each assembly, we obtain optimal module topologies as a solution to a convex second-order conic program that exploits the underlying modularity, incorporating stress constraints, multiple load cases, and reuse of module(s) for various structures. Merits of the proposed strategy are illustrated with three representative examples, clearly demonstrating that the best designs obtained by our method exhibited decreased compliance: from 56% to 69% compared to the PUC designs.
翻译:模块化对于解决优化方面的许多问题具有吸引力。 它将制造和重新配置的诸多问题的好处带来结构优化, 并使得定期单元细胞(PUC)的计算性能和非统一设计在多尺度材料优化中的功效之间实现平衡。 在这里, 我们引入了一种新的战略, 用于同时使用Wang Tyling编码的Turus模块表层及其大型组装的最小合规性设计, 这是一种形式主义, 独立控制模块及其界面的数量。 我们通过混合超重和数学编程来解决新出现的双层优化问题。 在上层, 我们使用基因算法优化模块组件组件组装。 对于每个组装, 我们获得了最佳模块组装模式表的解决方案, 用于利用基本模块化, 包括压力限制、 多重负荷案例 和 模块的再利用 。 三个有代表性的例子说明了拟议战略的优点, 清楚地表明我们方法获得的最佳设计显示的合规率下降: 从56%到69 %, 与 PUC 设计相比较。