Narrow-Band Topology Optimization on a Sparsely Populated Grid
Narrow-Band Topology Optimization on a Sparsely Populated Grid
复制标题
DOI：
10.1145/3272127.3275012
复制
发表时间：
2018-11-01
影响因子：
6.2
通讯作者：
Sifakis, Eftychios
中科院分区：
文献类型：
--
作者：
Liu, Haixiang;Hu, Yuanming;Sifakis, Eftychios
自然界中的各种结构都表现出稀疏、薄而复杂的特征。这是具有挑战性的，使用传统的数值方法来研究这些结构特性，因为这些功能需要高度精细的空间分辨率来捕捉，因此，他们招致了过高的计算成本。我们提出了一种新的计算框架，高分辨率的拓扑优化，提供了飞跃的仿真能力，由两个数量级，从国家的最先进的方法。我们的技术可容纳计算域超过10亿个网格体素在一个单一的共享内存的多处理器平台，允许自动出现的结构，丰富的几何特征和卓越的机械性能。为了实现这一目标，我们跟踪薄结构的演变，并模拟其弹性变形的动态窄带区域周围的高密度网站，以避免浪费计算工作的大空隙区域。我们还设计了一个混合精度的多重网格预处理迭代求解器，保持模拟的内存占用紧凑的大小，同时保持双精度的精度。我们已经证明了该算法的有效性，通过优化各种复杂的结构，从自然和工程系统。
A variety of structures in nature exhibit sparse, thin, and intricate features. It is challenging to investigate these structural characteristics using conventional numerical approaches since such features require highly refined spatial resolution to capture and therefore they incur a prohibitively high computational cost. We present a novel computational framework for high-resolution topology optimization that delivers leaps in simulation capabilities, by two orders of magnitude, from the state-of-the-art approaches. Our technique accommodates computational domains with over one billion grid voxels on a single shared-memory multiprocessor platform, allowing automated emergence of structures with both rich geometric features and exceptional mechanical performance. To achieve this, we track the evolution of thin structures and simulate its elastic deformation in a dynamic narrow-band region around high-density sites to avoid wasted computational effort on large void regions. We have also designed a mixed-precision multigrid-preconditioned iterative solver that keeps the memory footprint of the simulation to a compact size while maintaining double-precision accuracy. We have demonstrated the efficacy of the algorithm through optimizing a variety of complex structures from both natural and engineering systems.