Neck Validation of Multibody Human Model under Frontal and Lateral Impacts using an Optimization Technique

Paper #:
  • 2015-01-1469

Published:
  • 2015-04-14
DOI:
  • 10.4271/2015-01-1469
Citation:
Wang, Y., Kim, T., Li, Y., and Crandall, J., "Neck Validation of Multibody Human Model under Frontal and Lateral Impacts using an Optimization Technique," SAE Technical Paper 2015-01-1469, 2015, https://doi.org/10.4271/2015-01-1469.
Abstract:
Multibody human models are widely used to investigate responses of human during an automotive crash. This study aimed to validate a commercially available multibody human body model against response corridors from volunteer tests conducted by Naval BioDynamics Laboratory (NBDL). The neck model consisted of seven vertebral bodies, and two adjacent bodies were connected by three orthogonal linear springs and dampers and three orthogonal rotational springs and dampers. The stiffness and damping characteristics were scaled up or down to improve the biofidelity of the neck model against NBDL volunteer test data because those characteristics were encrypted due to confidentiality. First, sensitivity analysis was performed to find influential scaling factors among the entire set using a design of experiment. Second, the identified scaling factors were adjusted using a gradient-based optimization technique to minimize a Biofidelity rank score (smaller the better), which is one of common technique for correlation analysis between PMHS responses and ones of a dummy or a model. In the sensitivity analysis 4 scaling factors out of 7 were found to be influential to the response of the neck model. The Biofidelity rank score was reduced from 1.63 to 0.90 through the optimization. The validated neck model showed more biofidelic responses in terms of resultant head acceleration, head rotation angle, and head relative displacement with respect to T1. The improved neck model through this study will provide more accurate head kinematics than the initial model during a vehicle-pedestrian collision, and the more accurate head kinematics will be enable more accurate prediction of the head injury risk, especially in the application of pedestrian collisions. Lastly, the methodology of this study can be applied to any other body region of a multibody model to improve its biofidelity.
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