On the mechanical characterization and modeling of polymer gel brain substitute under dynamic rotational loading

The use of highly sensitive soft materials has become increasingly apparent in the last few years in numerous industrial fields, due to their viscous and damping nature. Unfortunately these materials remain difficult to characterize using conventional techniques, mainly because of the very low internal forces supported by these materials especially under high strain-rates of deformation. The aim of this work is to investigate the dynamic response of a polymer gel brain analog material under specific rotational-impact experiments. The selected polymer gel commercially known as Sylgard 527 has been studied using a specific procedure for its experimental characterization and numerical modeling. At first an indentation experiment was conducted at several loading rates to study the strain rate sensitivity of the Sylgard 527 gel. During the unloading several relaxation tests were performed after indentation, to assess the viscous behavior of the material. A specific numerical procedure based on moving least square approximation and response surface method was then performed to determine adequate robust material parameters of the Sylgard 527 gel. A sensitivity analysis was assessed to confirm the robustness of the obtained material parameters. For the validation of the obtained material model, a second experiment was conducted using a dynamic rotational loading apparatus. It consists of a metallic cylindrical cup filled with the polymer gel and subjected to an eccentric transient rotational impact. Complete kinematics of the cup and the large strains induced in the Sylgard 527 gel, have been recorded at several patterns by means of optical measurement. The whole apparatus was modeled by the Finite Element Method using explicit dynamic time integration available within Ls-dyna (R) software. Comparison between the physical and the numerical models of the Sylgard 527 gel behavior under rotational choc shows excellent agreements. (C) 2016 Elsevier Ltd. All rights reserved.