Optimizing compressive load capacity for differing tensegrity geometries. (June 2021)

• Record Type: Journal Article
• Authors: Roth, James K.; McCarthy, Timothy J.
• Is Part Of: Computers & structures. Volume 249(2021)
• Publication Date: 2021-06
• Subjects: Tensegrity -- Genetic algorithm -- Optimization -- Compressive load -- Aspect ratio; Structural engineering -- Data processing -- Periodicals; Electronic data processing -- Structures, Theory of -- Periodicals; 624.171
• DOI: 10.1016/j.compstruc.2021.106523
• Languages: English
• ISSNs: 0045-7949

Abstract

Highlights: A novel method established and tested for realistic analysis of loaded tensegrities. Robust solution method utilises Rhinoceros 3D, Grasshopper and Kangaroo Physics. Form-finding coupled with genetic algorithms obtain optimum shape and load capacity. 600% improvement on previously published load capacities via optimal pretensioning. Abstract: Tensegrity structures present new possibilities to the field of structural engineering, owing to their ability to efficiently distribute compressive loads associated with their non-orthogonal design. Previous research has shown that when pretensioned, tensegrities exhibit higher resistance to compressive loading. However, over-tensioning can have adverse effects, reducing the tensegrities overall resistance to compressive loading. The geometry of a tensegrity affects how the structure reacts to loading, and the prestress and loading can concurrently affect geometry. This paper uses genetic algorithms to optimize the pretension loads in the cables of a tensegrity to deliver the highest overall vertical load capacity. The results are applied to determine the ultimate load-carrying capacity of tensegrities under a compressive load and determine the optimal aspect ratio at which this is achieved. By optimizing the pretension, the tensegrity can withstand compressive loads up to six times those that have been previously reported in literature.