title: Development and validation of a generic finite element vehicle buck model for the analysis of driver rib fractures in real life nearside oblique frontal crashes.
abstract: OBJECTIVE
  Frontal crashes still account for approximately half of all fatalities in passenger cars, despite several decades of crash-related research. For serious injuries in this crash mode, several authors have listed the thorax as the most important. Computer simulation provides an effective tool to study crashes and evaluate injury mechanisms, and using stochastic input data, whole populations of crashes can be studied. The aim of this study was to develop a generic buck model and to validate this model on a population of real-life frontal crashes in terms of the risk of rib fracture.
  
  
  METHODS
  The study was conducted in four phases. In the first phase, real-life validation data were derived by analyzing 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 parameterized finite 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 reverse engineering based on NCAP tests. Finally, in the fourth phase, the stochastic FE model was used to simulate a population 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 occupants and less for senior occupants. However, if the effect of underestimation of rib fractures in the NASS/CDS material is accounted for using statistical simulations, the risk of rib fracture based on the stochastic FE model matches the risk based on the NASS/CDS data for senior occupants.
  
  
  CONCLUSIONS
  The current version of the stochastic model can be used to evaluate new safety measures using a population of frontal crashes for senior occupants.
authors.affiliation: ÅF Industry, P.O. Box 1551, SE-401 51 Göteborg, Sweden; Department of Surgical and Perioperative Science, Umeå University, SE-901 87, Sweden; Industrial Doctoral School, Umeå University, SE-901 87, Sweden. Electronic address: johan.iraeus@afconsult.com.
authors.forename: Johan
authors.initials: J
authors.lastname: Iraeus
authors.affiliation: Department of Surgical and Perioperative Science, Umeå University, SE-901 87, Sweden.
authors.forename: Mats
authors.initials: M
authors.lastname: Lindquist
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D016208:Databases, Factual; D020342:Finite Element Analysis; D006801:Humans; D015233:Models, Statistical; D012253:Rib Fractures / Q000453:epidemiology / Q000209:etiology* / Q000517:prevention & control*; D018570:Risk Assessment / Q000706:statistics & numerical data; D012449:Safety; D013269:Stochastic Processes
keywords: Generic model; HBM; Logistic regression; Rib fracture; Stochastic simulation; THUMS