Liu, Y., Lee, T.U., Koronaki, A., Pietroni, N. and Xie, Y.M., 2023. Engineering Structures, 284, p.116016. [Link]
Space frame structures are increasingly adopted in contemporary free-form architectural designs due to their elegant appearance and excellent structural performance. However, a space frame structure in a doubly-curved form typically comprises nodes of different shapes. This often requires extensive node customization, hence incurring high manufacturing costs.
In this study, we propose a new clustering–optimization framework to reduce the number of different nodes in space frame structures. In clustering, nodes are divided into different groups, with similar shapes grouped together, using an enhanced k-means clustering technique. In optimization, nodes within the same group are transformed towards congruence while closely approximating the target surface. Together, by interleaving clustering and optimization, our method can minimize the node shape variety under a user-defined error threshold. The effectiveness of the method is validated through a variety of numerical examples. The potential practical application of our method is demonstrated by re-designing a complex, free-form architectural project.
Our method is capable of minimizing the node shape variety in complex architectural projects. Two examples are shown below. In the first test example, all nodes can be made identical using our algorithm. In the second example, the 1535 nodes in the free-form geometry can be optimised into 75 different types. In doing so, the manufacturing costs of the nodes could be significantly reduced.