Genetically Finding Algorithm for a Tensegrity Structure

Abstract:

In the form-finding process of a tensegrity structure, some constraints and assumptions are usually introduced for initial geometry and/or pre-determined member types to ensure the uniqueness of solution. The tensegrity structures are indeterminate problems in most cases. In this study, a novel and versatile numerical form-finding procedure which requires only a minimal knowledge of initial structure configuration is adopted. The procedure needs only the prototype of each member, i.e. either compression or tension, and the connectivity information of members. The connectivity of members and its prototype information are encoded to form an individual population used in genetic algorithm searching problems. As for the fitness evaluation to each population, the existence of self-stressed state in each population is sought. At the end, some numerical examples are given to show the efficiency of the present study and its ability in searching new configurations of tensegrity structures with less design variables.

• Periodical: Advanced Materials Research (Volumes 450-451)
• Pages: 861-864
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.450-451.861
• Online since: January 2012
• Authors: Buntara Sthenly Gan, Manabu Yamamoto
• Keywords: Form-Finding, Genetic Algorithm (GA), Self-Stressed, Tensegrity

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