Crash reconstructions using finite element (FE) vehicle and human body models (HBMs) allow researchers to investigate injury mechanisms, predict injury risk, and evaluate the effectiveness of injury mitigation systems, ultimately leading to a reduced risk of fatal and severe injury in motor vehicle crashes (MVCs). To predict injuries, regional-level injury metrics were implemented into the Total Human Model for Safety (THUMS) full body HBM. THUMS was virtually instrumented with cross-sectional planes to measure forces and moments in the femurs, upper and lower tibias, ankles, pelvis (pubic symphysis, ilium, ischium, sacrum, ischial tuberosity, and inferior and superior pubic ramus), and the cervical, thoracic, and lumbar vertebrae and intervertebral discs. To measure accelerations, virtual accelerometers were implemented in the head, thoracic vertebrae, sternum, ribs, and pelvis. Three chest bands and an abdominal band were implemented to measure chest and abdominal deflection. Organ injury is assessed with volumetric strain-based metrics in the lung, liver, and spleen. The kinematic and kinetic data described were batch-processed using a custom-built program known as the Injury Prediction Post-Processor (IPPP) to evaluate common injury metrics and risk probabilities from literature. A total of 30 injury metrics are currently implemented in the IPPP, including Head Injury Criterion (HIC), Combined Thoracic Index (CTI), and cross-sectional forces and moments. We have observed improved ability and accuracy in predicting real-world injury using stress and strain analysis compared to traditionally employed criteria for anthropomorphic test devices (ATDs).


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    Title :

    Regional Level Crash Induced Injury Metrics Implemented within THUMS v4.01


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2016 World Congress and Exhibition ; 2016



    Publication date :

    2016-04-05




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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