SUMMARY

The human skull is a remarkable structure that exhibits a host of complexities in its dynamics. This work presents a fundamental investigation in which aspects that influence the dynamic behavior of the skull are analyzed computationally and experimentally. First, a finite element model construction routine is developed that produces geometrically accurate three-dimensional vibration models of cranial segments where the cortical tables and the diploe have their own material domains. Numerical models of different cranial regions are generated and compared against experimental modal properties to extract the effective elastic parameters of the composite layers, with the parameters and modal damping ratios showcased for a selection of cranial segments including the parietal, frontal, occipital, and temporal bones. This numerical-experimental framework is also extended for the case of cranial sutures, which are joints that connect adjacent cranial regions, that may significantly affect the overall stiffness and damping. Lastly, the effect of fluid loading is studied by degassing the segments, which removes the air from the bone pores and replaces it with water, bringing the bone state closer to in vivo conditions. The additional effect of external fluid loading emulating the brain and/or clinical setups that often feature a water bath for ultrasound delivery is also considered. To demonstrate the use of the identified elastic parameters, two case studies are presented. In the first, the elastic properties of the cranial segments are assumed as representative parameters for a full human skull. A high-fidelity numerical model of the skull is developed, and the experimental and numerical modal properties are obtained for the dry and degassed bone states with representative vibration modes identified and compared. In the second study, the degassed elastic parameters are applied to analyze the transcranial radiation of guided waves, which in recent years has received growing interest, by means of time transient finite element simulations and submersed experimental results, confirming the use of the high-fidelity modeling, analysis, and parameter identification framework presented herein.