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This research investigates the variation of pedestrian stance in pedestrian-automobile impact using a validated multi-body vehicle and human model. Detailed vehicle models of a small family car and a sport utility vehicle (SUV) are developed and validated for impact with a 50th percentile human male anthropometric ellipsoid model, and different pedestrian stances (struck limb forward, feet together, and struck limb backward) are investigated. The models calculate the physical trajectory of the multi-body models including head and torso accelerations, as well as pelvic force loads. This study shows that lower limb orientation during a pedestrian-automobile impact plays a dominant role in upper body kinematics of the pedestrian. Specifically, stance has a substantial effect on the subsequent impacts of the head and thorax with the vehicle. The variation in stance can change the severity of an injury incurred during an impact by changing the impact region.

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.