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

Journal Article
2012-01-0562
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 16, 2012 by SAE International in United States
Fracture Modeling Inputs for a Human Body Model via Inference from a Risk Curve: Application for Skull Fracture Potential
Sector:
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.
Language: English

Abstract:

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).