Identification of material properties of human brain under large shear deformation: Analytical versus finite element approach

Abstract

Brain injuries have severe consequences and can be life-threatening. Computational models of the brain with accurate geometries and material properties may help in the development of injury countermeasures. The mechanical properties of brain under various loadings have been reported in many studies in the literature over the past 60 years. Step-and-hold tests under simple loading conditions have often been used to characterize viscoelastic and nonlinear behavior of brain under high-rate deformation; however, the stress relaxation curves used for material identification of brain are typically obtained by neglecting the initial strain ramp and by assuming a uniform strain distribution in the sample. Using finite element simulations of human brain shear tests, this study shows that these simplifications may have a significant effect on the measured material properties. Models optimized using only the stress relaxation curve predict much lower stress during the strain ramp due to an inaccurate elastic function. In addition, material models optimized using analytical models, which assume a uniform strain distribution, under-predict peak forces in finite element simulations. Models optimized using finite element simulations show similar relaxation behavior as the optimized analytical model, but predict a stiffer elastic response (about 46%). Identification of brain material properties using finite element optimization techniques is recommended in future studies. © 2010 Springer-Verlag.