Efficient Inverse-designed Structural Infill for Complex Engineering Structures: Multi-scale Optimization mesh

Exodus II hex mesh data files of unstructured multi-scale optimization from the paper "Efficient Inverse-designed Structural Infill for Complex Engineering Structures". The mesh files have side sets for applied load case and boundary conditions. The load cases and boundary conditions are found in the paper. The data set contains the results of the three models used in the paper: the Michell cantilever, the Lotte tower, and the GE Jet Engine Bracket.Abstract cited from DOI: https://doi.org/10.48550/arXiv.2307.09518 :"Inverse design of high-resolution and fine-detailed 3D lightweight mechanical structures is notoriously expensive due to the need for vast computational resources and the use of very fine-scaled complex meshes. Furthermore, in designing for additive manufacturing, infill is often neglected as a component of the optimized structure. In this paper, both concerns are addressed using a de-homogenization topology optimization procedure on complex engineering structures discretized by 3D unstructured hexahedrals. Using a rectangular-hole microstructure (reminiscent to the stiffness optimal orthogonal rank-3 multi-scale) as a base material for the multi-scale optimization, a coarse-scale optimized geometry can be obtained using homogenization-based topology optimization. Due to the microstructure periodicity, this coarse-scale geometry can be up-sampled to a fine physical geometry with optimized infill, with minor loss in structural performance and at a fraction of the cost of a fine-scale solution. The upsampling on 3D unstructured grids is achieved through stream surface tracing which aligns with the optimized local orientation. The periodicity of the physical geometry can be tuned, such that the material serves as a structural component and also as an efficient infill for additive manufacturing designs. The method is demonstrated through three examples. It achieves comparable structural performance to state-of-the-art methods but stands out for its significant computational time reduction, much faster than the base-line method. By allowing multiple active layers, the mapped solution becomes more mechanically stable, leading to an increased critical buckling load factor without additional computational expense. The proposed approach achieves promising results, benchmarking against large-scale SIMP models demonstrates computational efficiency improvements of up to 250 times."

《高效逆向设计复杂工程结构的结构填充》一文中，所提及的 Exodus II 六面体网格数据集，该数据集源自于非结构化多尺度优化。网格文件包含了施加荷载情况及边界条件的侧面集。荷载情况和边界条件详见论文。数据集收录了论文中使用的三种模型的结果：米切尔悬臂梁、洛特塔和通用电气喷气发动机支架。摘要引用自 DOI：https://doi.org/10.48550/arXiv.2307.09518："由于需要庞大的计算资源和非常精细的复杂网格，高分辨率和精细细节的3D轻质机械结构的逆向设计在历史上一直成本高昂。此外，在面向增材制造的设计中，填充通常被忽视作为优化结构的一部分。在本文中，通过在由3D非结构化六面体离散化的复杂工程结构上使用去同质化拓扑优化程序，同时采用矩形孔微结构（类似于刚度最优正交秩3多尺度）作为多尺度优化的基础材料，得以通过基于同质化的拓扑优化获得粗尺度优化几何形状。由于微结构的周期性，这种粗尺度几何形状可以上采样至具有优化填充的精细物理几何形状，结构性能损失微乎其微，且成本仅为精细尺度解决方案的一小部分。3D非结构化网格上的上采样通过流表面追踪实现，与优化局部方向保持一致。物理几何形状的周期性可以调整，使材料既作为结构组件，又作为增材制造设计的有效填充。该方法通过三个实例进行展示，其结构性能可与最先进的方法相媲美，但其在计算时间上的显著减少尤为突出，远超基准方法。通过允许多个活动层，映射解决方案的机械稳定性得到增强，从而在不增加额外计算成本的情况下，提高了临界屈曲负载因子。所提出的方法取得了令人鼓舞的结果，与大规模SIMP模型进行基准测试表明，计算效率提高了高达250倍。