Abstract
Particle Swarm Optimization (PSO) was foregrounded by finite element (FE) modeling to predict the material properties of the human cornea through inverse analysis. Experimental displacements have been obtained for corneas of a donor approximately 50 years old, and loaded by intraocular pressure (IOP). FE inverse analysis based on PSO determined the material parameters of the corneas with reference to first-order, Ogden hyperelastic model. FE analysis was repeated while using the commonly-used commercial optimization software HEEDS, and the rates of the same material parameters were used to validate PSO outcome. In addition, the number of optimization iterations required for PSO and HEEDS were compared to assess the speed of conversion onto a global-optimum solution. Since PSO-based analyses produced similar results with little iteration to HEEDS inverse analyses, PSO capacity in controlling the inverse analysis process to determine the cornea material properties via finite element modeling was demonstrated.
Highlights
Particle Swarm Optimization (PSO), based on socio-psychological principles inspired by swarm intelligence and social behavior, has been widely applied to engineering (Marwala, 2010)
Material parameters obtained from PSO have been compared with those by HEEDS
Boundary rates were defined to constrain the search space between maximum and minimum rates for each PSO iteration. This limitation is required since rates that exceed maximum and minimum boundaries lead to unrealistic material parameters and convergence issue for the finite element (FE) solver
Summary
Particle Swarm Optimization (PSO), based on socio-psychological principles inspired by swarm intelligence and social behavior, has been widely applied to engineering (Marwala, 2010). PSO method was first forwarded in 1995 (Poli, Kennedy & Blackwell, 2007) and soon found applications in several areas Marwala, Boulkaibet, & Adhikari (2016) combined PSO with finite element (FE) modeling to get the best fit for numerically-predicted load-deformation behavior with experimental data obtained for a simple beam. More demanding structural mechanics applications were undertaken in later studies which demonstrated PSO reliability. It may Maringá, v. 39, n. 3, p. 325-331, July-Sept., 2017 effectively be combined with FE methods in inverse modeling problems (Tang, Chen, & Peng, 2009; Oliveira eta al., 2011; Chen, Tang, Ge, An, & Guo, 2013; Reutlinger, Bürki, Brandejsky, Ebert, & Büchler, 2014)
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