CHARACTERIZATION OF RECYCLED RUBBER USING PARTICLE SWARM OPTIMIZATION TECHNIQUES

Abstract

ABSTRACT A material based on recycled rubber has been developed to use as a protective coating on road barriers with the aim of improving motorcyclists' security against crash impacts. This material is based on grounded rubber from used tires added by extrusion using low-density polyethylene as adhesive. Compression tests have been performed for different densities of the recycled material to fully describe the mechanical characteristics under high strain rates (in the rank 0.057–5.7 s −1 ), and a constitutive model composed of a hyperelastic Mooney Rivlin part and a viscoelastic part based on the generalized Maxwell model has been taken to characterize this behavior. Hyperelastic parameters have been obtained by means of the least-squares fitting technique, and particle swarm optimization (PSO) has been used to obtain viscoelastic parameters. The PSO algorithm is shown to be a good optimization method, simple, versatile, and consisting of few parameters that accelerate to the optimal solution. Therefore, this article presents a new and efficient approach to obtaining the parameters for the viscoelastic model. The behavior of the experimental material confirms the theoretically obtained results, so the procedure presented in the article is validated successfully.