Topological optimization of porous solids

这一提案的前传集中分析了3D网状实体(例如**松质骨)的拓扑图。拓扑学(对地方的研究，希腊语)与形态(对形状的研究)相对，指的是一个整体的组成部分相互联系的**方式，而不考虑它们的大小、形状和规模。例如，河床和分支血管的拓扑结构是相似的；自行车和方向盘的拓扑结构是不同的。拓扑图是结构的力学性能、行为和用途的基础。在松质骨的情况下，它在优化骨骼强度的同时，同时使其重量最小化，并降低其对生物体的维护成本，发挥着关键作用。**在人造工程结构中，拓扑很少被考虑，但通过使用昂贵的材料、更大量的材料、**或结构内更复杂的元素组合，**次优拓扑的影响可以被部分补偿。根据**骨小梁拓扑学研究的经验，该项目使用基于仿生拓扑学的设计来生成**轻质而坚固的结构，这些结构可以按任何尺寸缩放并制造用于各种工程**应用，从假肢医疗设备到土木工程。正如我们从骨小梁中了解到的，它的**自然的、功能驱动的拓扑优化是缓慢和迭代的。在这里，我们建议借助于人工智能(深度学习-基于神经网络的算法)来加速和**细化架构式人工结构的拓扑优化过程，其中基本原理借鉴了骨骼**生物学。这是对一种经过**数百万年进化提炼的高效结构进行反向工程的一个例子。

The prequel of this proposal focused on the analysis of the topological blueprint of 3D reticulated solids (e.g.,**trabecular bone). Topology (a study of place, Greek) as opposed to morphology (a study of shape), refers to the**way in which the components of a whole are related to each other, regardless of their size, shape and scale. For**example, the topologies of a river bed and of a branching blood vessel are similar; the topologies of a bicycle**wheel and of a steering wheel are different. Topological blueprint is fundamental for mechanical properties,**behavior and purpose of the structure. In the case of trabecular bone, it plays a critical role in optimizing bone**strength while at the same time minimizing its weight and reducing its cost of maintenance for the organism.**Among human-made engineered structures, topology is rarely taken into account, but the implications of**suboptimal topology can be partially compensated for by using expensive materials, larger amounts of material,**or more sophisticated assemblages of the elements within the structure. Following lessons learned from the**study of trabecular bone topology, this project uses biomimetic topology-based design for generation of**light-weight and strong structures that can be scaled to any size and manufactured for a variety of engineering**applications, from prosthetic medical devices to civil engineering. As we learned from trabecular bone, its**natural, function-driven topological optimization is slow and iterative. Here, we suggest to accelerate and**refine the process of topological optimization of architected artificial structures with the aid of artificial**intelligence (deep learning - neural network-based algorithm) where basic principles are borrowed from bone**biology. This is an example of reverse-engineering of a highly effective structure that has been refined by**millions of years of evolution.