Form-finding of frame-supported tensile membrane structures using stochastic optimisation

For tensile membrane structures (TMS), form-finding is the first step in design, in which the structure adopts a unique equilibrium shape based on the initial configuration of the structure and the applied initial prestress. However, the choice of a single robust numerical method for form-finding remains debatable, particularly due to the intensive computation involved. The present work proposes a novel form-finding method for TMS using a swarm intelligence algorithm. Particle swarm optimisation (PSO) is used here as the optimiser in the formfinding analysis, formulated as a (area or potential energy) minimisation problem. The computations involve stochastic PSO runs, until the structure converges to an equilibrium configuration. The proposed form-finding method is demonstrated for two study structures with different optimisation objectives. The proposed PSO-based form-finding technique is found to save significant computation cost, when compared to the most commonly used form-finding algorithm of dynamic relaxation. The PSO-based algorithm is also found to lessen arbitrary parameter selections and to be more robust to the selection of an initial TMS configuration.