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Previous full-scale pedestrian impact experiments using post-mortem human surrogates (PMHS) and sled-mounted vehicle bucks have shown that vehicle shape relative to pedestrian anthropometry may influence pedestrian kinematics and injury mechanisms. While a parametric study examining these factors could elucidate the complex relationships that govern pedestrian kinematics, it would be impractical with PMHS tests due to the relative expense involved in performing numerous experiments on subjects with varying anthropometry. Finite element (FE) modeling represents a more feasible approach since numerous experiments can be conducted with a fraction of the expense. However, there have been no studies to date depicting kinematic validation of a human pedestrian FE model in full-scale collisions using different vehicle and pedestrian geometries. Therefore, this study used an FE model of the Polar-II pedestrian dummy that was previously validated against full-scale test data.

Two post-mortem human subjects were subjected to dynamic, non-injurious (up to 20% chest deflection) anterior shoulder belt loading at 0.5 m/s and 0.9 m/s loading rates. The human surrogates were mounted to a stationary apparatus that supported the spine and shoulder in a configuration comparable to that achieved in a 48 km/h sled test at the time of maximum chest deformation. A hydraulically driven shoulder belt was used to load the anterior thorax which was instrumented with a load cell for measuring reaction force and uniaxial strain gages at the 4th and 8th ribs. In addition, the deformation of the chest was measured using a 16- camera Vicon 3D motion capture system. In order to investigate the chest deformation pattern and ribcage loading in greater detail, a human finite element (FE) model of the thorax was used to simulate the tests.

Material and structural properties of human tissues under impact loading are needed for the development of physical and computational models used in pedestrian and vehicle occupant protection. Obtaining these global properties directly from the data of biomechanical tests is a challenging task due to nonlinearities of tissue-test setup systems. The objective of this study was to develop subject-specific finite element (FE) techniques for material identification of human tissues using Successive Response Surface Methodology. As example, the test data of a human femur in three-point bending is used to identify parameters of cortical bone. Good global and local predictions of the optimized FE model demonstrate the utility and effectiveness of this new material identification approach.