Injury Metrics, Real World Crash Reconstruction, and Robust Injury Prediction for a Human Body Model in Side Impact
Abstract
Motor vehicle crashes (MVCs) are a significant public health problem. Worldwide, MVCs kill over 1.2 million people each year. Improved understanding of the occupant loading conditions in real world crashes is critical for injury prevention and new vehicle design. Real world crash reconstructions using vehicle and human body finite element models (HBM) have the potential to elucidate injury mechanism, predict injury risk, and evaluate injury mitigation system effectiveness. The purpose of the work presented herein was to create a novel paradigm in finite element (FE) MVC injury analysis to evaluate injury risk in real world crash scenarios.
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finite element analysis, Human body model, injury metrics, injury prediction, injury risk, real world motor vehicle crash
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Wake Forest University