Objective: Frontal crashes still account for approximately half of all fatalities in passenger cars, despite severaldecades of crash-related research. For serious injuries in this crash mode, several authors have listed the thoraxas the most important. Computer simulation provides an effective tool to study crashes and evaluate injurymechanisms, and using stochastic input data, whole populations of crashes can be studied. The aim of this studywas to develop a generic buck model and to validate this model on a population of real-life frontal crashes interms of the risk of rib fracture.
Method: The study was conducted in four phases. In the first phase, real-life validation data were derived byanalyzing NASS/CDS data to find the relationship between injury risk and crash parameters. In addition,available statistical distributions for the parameters were collected. In the second phase, a generic parameterizedfinite element (FE) model of a vehicle interior was developed based on laser scans from the A2MAC1 database.In the third phase, model parameters that could not be found in the literature were estimated using reverseengineering based on NCAP tests. Finally, in the fourth phase, the stochastic FE model was used to simulate apopulation of real-life crashes, and the result was compared to the validation data from phase one.
Results: The stochastic FE simulation model overestimates the risk of rib fracture, more for young occupantsand less for senior occupants. However, if the effect of underestimation of rib fractures in the NASS/CDSmaterial is accounted for using statistical simulations, the risk of rib fracture based on the stochastic FE modelmatches the risk based on the NASS/CDS data for senior occupants.
Conclusion: The current version of the stochastic model can be used to evaluate new safety measures using apopulation of frontal crashes for senior occupants.
stochastic, finite element, logistic regression, rib fracture, generic, THUMS, HBM