Fracture Modeling Inputs for a Human Body Model via Inference from a Risk Curve: Application for Skull Fracture Potential

Event
SAE 2012 World Congress & Exhibition
Authors Abstract
Content
A three-step process was developed to estimate fracture criteria for a human body model. The process was illustrated via example wherein skull fracture criteria were estimated for the Ford Human Body Model (FHBM)~a finite element model of a mid-sized human male. The studied loading condition was anterior-to-posterior, blunt (circular/planar) cylinder impact to the frontal bone. In Step 1, a conditional reference risk curve was derived via statistical analysis of the tests involving fractures in a recently reported dataset (Cormier et al., 2011a). Therein, Cormier et al., authors reported results for anterior-to-posterior dynamic loading of the frontal bone of rigidly supported heads of male post mortem human subjects, and fracture forces were measured in 22 cases. In Step 2, the FHBM head was used to conduct some underlying model validations relative to the Cormier tests. The model-based Force-at-Peak Stress was found to approximate the test-based Fracture Force. In Step 3, models of Cormier's setup with assumed fracture criteria were made such that they produced the experimentally observed spread of fracture forces. Moreover, iteration was conducted on the model-based stress and strain fracture criteria (viz., σult and ε
). The outcomes were analyzed via the same statistical approach applied in Step 1, and subject to σ
is approximately equal to 125 MPa and εult is approximately equal to 2.2%, the model-based risk curve nearly identically recovered the reference test-based risk curve (i.e., PFE
is approximately equal to 1.03 P
and R₂ = 0.99).
Meta TagsDetails
DOI
https://doi.org/10.4271/2012-01-0562
Pages
21
Citation
Laituri, T., and El-jawahri, R., "Fracture Modeling Inputs for a Human Body Model via Inference from a Risk Curve: Application for Skull Fracture Potential," SAE Int. J. Passeng. Cars - Mech. Syst. 5(1):468-486, 2012, https://doi.org/10.4271/2012-01-0562.
Additional Details
Publisher
Published
Apr 16, 2012
Product Code
2012-01-0562
Content Type
Journal Article
Language
English