Sizing and prestress optimization of Class-2 tensegrity structures for space boom applications

Kaan Yildiz*, George A. Lesieutre

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Design of real engineering structures can benefit from an optimization step in which various parameters can be determined to satisfy a given set of requirements and constraints. Optimization of spatial assemblies such as truss or frame structures involves sizing optimization to minimize the mass of the structure. Optimization of tensegrity structures is more challenging as prestress levels should be optimized as well. In this paper, sizing and prestress optimization of Class-2 tensegrity booms are addressed using a particle swarm optimization approach. Nonlinear finite-element models of tensegrity structures and solution methods provide a starting point. Furthermore, a continuum beam modeling technique for tensegrity structures with repeating units is also useful. The particle swarm optimization algorithm is described and two numerical examples are presented. The first example studies the design and single-objective optimization of a deployable Class-2 tensegrity boom with reinforcing cables to maximize the bending stiffness-to-mass ratio. The results indicate that the optimum structure is capable of competing well with the state-of-the-art deployable booms in terms of stiffness-to-mass ratio. The second example investigates a multi-objective optimization problem of a Class-2 tensegrity boom. The objective functions are selected as minimization of the mass and tip displacement, respectively. The objective functions are at least partially conflicting; therefore, Pareto-optimal solutions are obtained to guide future design decisions. The results show the potential of tensegrity structures for implementation as space structures and the robustness of the particle swarm optimization algorithm, even for multi-objective optimization problems.

Original languageEnglish
Pages (from-to)1451-1464
Number of pages14
JournalEngineering with Computers
Volume38
Issue number2
DOIs
Publication statusPublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2020, Springer-Verlag London Ltd., part of Springer Nature.

Keywords

  • Multi-objective
  • Optimization
  • Particle swarm optimization
  • Tensegrity

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