Xing, Mengdi. Tensile behavior and mechanical anisotropy of branched cerebral vasculature within gray matter. Retrieved from https://doi.org/doi:10.7282/T3JW8GXZ
DescriptionWith increasing effort to prevent, diagnose, and treat traumatic brain injury (TBI), a large amount of research has been dedicated to the investigation of axon-containing white matter for the study of TBI onset and progression, as well as the elastographic techniques used for diagnoses. However, the mechanical response of gray matter with embedded vasculature has not been thoroughly studied. The cerebral vessels play a vital role not only in the mechanical stiffening of the structure of the brain but also in supplying it with the oxygen and nutrients. By incorporating a multiscale approach to the finite element (FE) models, it is possible to determine the transfer of loads from macroscale to microscale and study the progression of traumatic injury in the brain. In the present thesis, an FE representative volume element (RVE) model of the gray matter is developed that incorporates a branching tree structure composed of arteries. Both the gray matter and the vasculature are represented with hyperelastic material models aiming at capturing the complex response of the biological materials under large strains. The RVE model of the composite material results in anisotropy stemming from not only the different material properties, but also attributed to the complex microstructure. Tensile stretches are applied to illustrate the stiffening effect of the vasculature as well as to determine the anisotropic material properties. The response of the whole volume is monitored under various external loadings. In this thesis, a general Fung-type constitutive model is adopted, which is one of the most widely used types of anisotropic material to describe the response behavior of the composites. By implementing a scriptable geometry generation routine, different vasculature geometries are investigated to elucidate the effect of the vascular geometry on the response of the gray matter RVE. By integrating an accurate geometry of the underlying vasculature, and the micromechanical response of the composite material consisting of the gray matter and the vasculature, the study of potential mechanisms of injury and the development of a micro architecture based RVE used in TBI multiscale simulations becomes feasible.