All ETDs from UAB

Advisory Committee Chair

David L Littlefield

Advisory Committee Members

Alan W Eberhardt

Jong-Eun Kim

Roy P Koomullil

Erwin Montgomery

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Engineering


The development of a finite element model capable of predicting brain injury sustained as a result of an impact load to the head is of considerable importance not only for the development of adequate protection systems but also in deciding an appropriate mode of treatment for an individual. With advancements in imaging technologies, it is now possible to visualize the neuron fiber structures in the brain. In the first half of this project, an analytical micro-mechanical model was developed from the individual isotropic behaviors of the Cerebro-Spinal Fluid (CSF) and brain tissue present in the brain, such that the resultant behavior of the material on the continuum scale is transverse isotropic. To capture the presence of neuron fibers in the brain, the data obtained from Diffusion Tensor MRI (DTI) was incorporated into the finite element model so that, based on the fiber direction in each voxel, orientation dependence of the mesoscale model was captured on the continuum scale. The use of DTI data in conjunction with a mesoscale material model is a novel method that has not been attempted so far because the material data available for brain tissue are mostly isotropic in character. A Lagrangian mesh based solver was developed so that it could be customized to incorporate the DTI data into the finite element model. Loading conditions from literature where experiments have been done on cadavers were used as a means of comparing predicted strains with the observed values. In the second half of this project, to determine the mechanical properties of the brain tissue more realistically, a computational multiscale material model was developed based on the physiology of the tissue. A computational micro-mechanical model was developed which incorporated the presence of neurons, glial cells and CSF. Homogenization of this model yields an anisotropic stiffness tensor that is based on mechanical properties of the individual constituents. Using this anisotropic stiffness tensor from the microscale model, the continuum model was executed with DTI data to capture the orientation dependence of the tissue on the microscale. The results were compared to experiments conducted on cadavers as well as the results obtained using the analytical microscale model.

Included in

Engineering Commons



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