Use of simplified geometrical models of a cornea for optimization purposes

Abstract

Particle Swarm Optimization (PSO) is an artificial intelligence technique (AI) that can be used to find approximate solutions to numerical problems of maximization and minimization. In this study, it was used a PSO algorithm to compare displacements from human cornea sample subjected to internal pressure of 45 mmHg with Results of numerical simulations were provided which identified optimized values for hyperelastic properties of the cornea (µ and α). By means of the results from numerical simulations via inverse analysis by the Finite Element Method (FEM), in conjunction with the PSO algorithm, optimized values of µ = 0.047 and α = 106.7 were found. When compared with optimized results from commercial software, errors around 0.15% were found. Results showed that, varying the values of particle inertia coefficients in the PSO algorithm, simulated displacements have improved when compared to experimental data. This demonstrates the potential use of PSO algorithm in conjunction with the FEM inverse analysis for hyperelastic materials characterization, using simplified geometrical models