Topologically Optimized and Functionally Graded Cable Nets. New approaches through robotic additive manufacturing

Abstract

Recent advancements in the realm of additive manufacturing technologies have made it possible to directly manufacture the complex geometries that are resultant from topological optimization and functionally graded material processes. Topological optimization processes are well understood and widely used within the realm of structural engineering and have been increasingly adopted in architectural design and research. However, there has been little research devoted to the topological optimization of cable nets and their fabrication through robotic additive manufacturing. This paper presents a design framework for the optimization of additively manufactured tensile cable nets that attempts to bridge between these two domains by reframing the scale of topological optimization processes. Instead of focusing solely on the topology optimization at the macro-scale of cable nets, this research develops a method to optimize the meso-scale topology and defines metamaterial units with different properties to be aggregated into a complex whole. This reorientation from the formal towards the material domain signals an engagement with morphogenetic modes of design that find formal expression through bottom-up material processes. In order to further investigate the emerging potentials of this reorientation, the presented method is validated through physical deformation tests, as well as applied to the design of a furniture-scale case study project realized through the use of robotic additive manufacturing of elastomeric materials