This paper presents a unified framework for form optimization of tensegrity unit cells by combining discrete-to-continuum homogenization with high-fidelity spectral-element vibration analysis. The discrete strain energy of prestressed bars and cables is equated to the strain energy of an equivalent linear elastic continuum to obtain the effective elasticity tensor. In parallel, the Spectral Element Method (SEM) provides exact, frequency-dependent dynamic stiffness, enabling accurate computation of natural frequencies and frequency response functions without dense spatial meshing. A set of scalar performance measures capturing stiffness, anisotropy, elastic stability, vibrational behavior, and prestress sensitivity is optimized individually using Particle Swarm Optimization (PSO). The results reveal clear trade-offs: stiffness-oriented objectives converge rapidly and show low variability, whereas scale-sensitive or noise-prone ones display larger dispersion and reduced robustness. Correlation analysis indicates minimal redundancy among objectives, with a single strong anticorrelation between modal separation and prestress sensitivity. Frequency-domain comparisons highlight the role of topology: simpler cells yield compact spectral responses, whereas more complex ones develop pronounced high-frequency resonances after dynamic-driven optimization. Overall, PSO proves effective for discovering meaningful metric-specific designs, while objective scaling and structural complexity motivate normalization, robust evaluation, and extended searches. The contribution is twofold: a practical homogenization–SEM pipeline that couples static and dynamic indicators, and a systematic assessment of robustness and trade-offs in tensegrity form optimization under fixed connectivity. • Integrated homogenization–SEM framework for tensegrity stiffness and vibration. • PSO explores eight structural metrics for tensegrity form optimization under fixed connectivity. • Metrics produce distinct tensegrity geometries and prestress distributions. • Topology complexity drives stiffness–dynamics trade-offs in optimization. • Practical guidelines for multi-objective PSO and robust prestress design.
Guachetá-Alba et al. (Thu,) studied this question.