Elastomeric materials that mimic real soft human tissues are sought to provide realistic experimental devices to simulate the human bodys response to concussive loading so that better protective equipment can be developed. Tissue injury occurs under large dynamic strains, in excess of 20%. Consequently, the dynamic mechanical behavior of tissue simulant materials and tissues themselves are often measured using a Kolsky Bar, which can achieve such large strains at strain rates commensurate with dynamic injuries, about 100 s-1. Obtaining valid Kolsky bar results on soft materials is challenging, however, due to poor dynamic equilibrium, friction, and inertial effects. To avoid these difficulties, an inverse method was employed to determine the dynamic response of a soft, prospective biomimetic elastomer. Kolsky bar tests were performed, and detailed specimen shape history measurements were made using high-speed 3D digital image correlation. Dynamic force data were also obtained. Individual tests were then modeled with the finite element method, and the dynamic stiffness of the elastomer was identified by matching the simulation results with test data using optimization. Using a hyper-elastic material model for the elastomer, the effects of stiffness, friction coefficient, Poisson ratio and material damping were investigated. The average dynamic response was found to be essentially equivalent to the quasi-static response at compressive strains up to 60%, within the ± 18% uncertainty of the method. Thus this particular elastomer does not exhibit the positive rate sensitivity that has been reported for actual soft human tissue. The study shows how the negative effects of friction and inertia can be eliminated using inverse techniques, but also how numerical damping in the finite element model can complicate efforts to identify a unique dynamic stiffness.
Citation: Journal of the Mechanical Behavior of Biomedical Materials
Pub Type: Journals
Kolsky Bar, Tissue Simulant, Digital Image Correlation, Finite Element Analysis, Inverse Method