Implementation of Particle Swarm Optimization Algorithm in Matlab Code for Hyperelastic Characterization

The purpose of this paper is to demonstrate the applicability Particle Swarm Optimization algorithm determine material parameters in incompressible isotropic elastic strain-energy functions using combined tension and torsion loading. Simulation rubber behavior was conducted from governing equations deformation a cylinder composed hyperelastic materials. Four different forms function were considered based respectively on polynomial, exponential logarithmic terms reproduce load force (N) torque (M) trends natural experimental data. After highlighting minimization objective generated fitting process, study revealed that particle swarm optimization could be successfully used identify best characterize rubber-like