Optimization Algorithm-Based Approach for Modelling Large Deflection of Cantilever Beam Subjected to Tip Load
This provides a universal method for modeling large deflections in cantilever beams, which is important for applications like compliant mechanisms and soft robots, but it is incremental as it applies an existing optimization technique to a known bottleneck.
The paper tackled the problem of modeling large deflections in cantilever beams, which is complicated by geometric nonlinearity, by proposing an optimization algorithm-based approach (OABA) using particle swarm optimization to predict beam tip locus and deflection curves, achieving a maximum error of 4.35% for normalized deflections up to 0.75.
Beam mechanism and beam theory have attracted substantial attention from researchers, as they have been widely used in many fields such as compliant mechanisms and soft robots. The modeling of beam mechanisms becomes complicated due to the geometric nonlinearity that is proved to be significant with large deflection. A new method, called optimization algorithm-based approach (OABA), is proposed to predict the large deflection of cantilever beams, in which an optimization algorithm is exploited to find the locus of the beam tip. With the derived locus of the beam tip, the deflection curve of the cantilever beam can be calculated. The optimization algorithm in this paper is embodied in a particle swarm optimization (PSO) algorithm. Experimental results show that the proposed method can precisely predict the deflection of the uniform and non-uniform cantilever beams. The maximum error is limited to 4.35% when the normalized maximum transverse deflection reaches 0.75. Given that, the proposed OABA would be a universal approach to model the large deflection of cantilever beams subjected to tip loads.