Age-Dependent Material Modelling of the Human Cranium: Predicting Cortical Bone Response Using Bayesian Networks and Experimental Validation - Back, Anton; Granholm, Stina; Larsson, Lukas; Viberg, Hanna (My University, 2025)
The risk of skull fracture due to impact increases with age. This project investigates how age affects the mechanical behaviour of cortical bone in the human skull, with the aim of enhancing the accuracy of finite element head models used in fracture prediction. Material properties were derived from experimental data by Wood (1969), which included tensile tests on post-mortem human subjects (PMHS) across a wide range of ages. A Bayesian statistical model was developed in order to analyse the influence of age on strain rate, and material properties such as modulus of elasticity, breaking stress, and breaking strain. The results showed a strong correlation between strain rate and modulus of elasticity, while direct correlations with age were inconclusive due to wide posterior distributions. Stress-strain curves were generated based on the Bayesian model and used to create age-specific material cards in LS-DYNA simulations. These curves accounted for varying strain rates, allowing more realistic simulation of impacts. To validate the finite element models, simulations were compared to experimental impact data from Raymond et al.(2009), in which PMHS were subjected to blunt impacts to the side region of the head. Fracture risk was evaluated using a survival analysis-based approach for creating risk functions, and compared against experimental outcomes. Although some prediction discrepancies were observed, the trends suggest that aged individuals experience slightly higher strain under the same loading conditions, implying an increased risk of fracture. The study demonstrates the potential for age-sensitive material models to improve simulations of the human head. It also highlights the need for updated experimental datasets and additional consideration of other anatomical variables such as skull and scalp thickness in future work
Keywords: Bayesian; HBM; Cranium; Risk function