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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. METHOD: 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. CONCLUSION: The current version of the stochastic model can be used to evaluate new safety measures using a population of frontal crashes for senior occupants.

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OBJECTIVE: Frontal crashes in which the vehicle has poor structural engagement, such as small-overlap and oblique crashes, account for a large number of fatalities. These crash modes are characterized by large intrusion and vehicle yaw rotation. RESULTS from previous studies have shown mixed results regarding the importance and effects of these parameters. The aim of this study was to evaluate how vehicle yaw rotation, instrument panel intrusion, and the time history of the pulse angle influence chest injury outcomes. METHOD: This study was conducted using kinematic boundary conditions derived from physical crash tests, which were applied on a finite element simulation model of a vehicle interior including a finite element human model. By performing simulations with different levels of simplified boundary conditions and comparing the results to a simulation with a full set of boundary conditions, the influence of the simplifications was evaluated. The injury outcome measure compared between the simulations was the expected number of fractured ribs. The 3 simplifications simulated were (1) removal of vehicle yaw rotation, (2) removal of vehicle yaw rotation plus an assumption of a constant pulse angle between the x- and y-acceleration, and (3) removal of instrument panel intrusion. The kinematic boundary conditions were collected from 120 physical tests performed at the Insurance Institute of Highway Safety; 77 were small-overlap tests, and 43 were moderate overlap tests. For each test, the full set of boundary conditions plus the 3 simplifications were simulated. Thus, a total of 480 simulations were performed. RESULTS: The yaw rotation influences occupant interaction with the frontal airbag. For the approximation without this kinematic boundary component, there was an average error in injury outcome of approximately 13% for the moderate overlap cases. Large instrument panel intrusion increases the risk of rib fracture in nearside small-overlap crashes. The mechanism underlying this increased fracture risk is a combination of increased airbag load and a more severe secondary impact to the side structure. Without the intrusion component, the injury risk was underestimated by 8% for the small-overlap crashes. CONCLUSION: The approximation with least error was version 2; that is, a model assuming a constant pulse angle, including instrument panel intrusion but no vehicle yaw rotation. This approximation simulates a sled test with a buck mounted at an oblique angle. The average error for this approximation was as low as 2-4%.

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OBJECTIVE: In the widely used National Automotive Sampling System (NASS)-Crashworthiness Data System (CDS) database, summary metrics that describe crashes are available. Crash angle or principal direction of force (PDOF) is estimated by the crash examiner and velocity changes (ΔV) in the x- and y-directions are calculated by the WinSMASH computer program using PDOF and results from rigid barrier crash testing combined with deformations of the crashed car. In recent years, results from event data recorders (EDRs) have been added to the database. The aim of this study is to compare both PDOF and ΔV between EDR measurements and WinSMASH calculations. METHODS: NASS-CDS inclusion criteria were model-year 2000 through 2010 automobiles, frontal crashes with ΔV higher than 16 km/h, and the pulse entirely recorded in the EDR module. This resulted in 649 cases. The subject vehicles were further examined and characterized with regard to frontal structure engagement (large or small overlap) as well as collision properties of the partner (impact location; front, side, or back) or object. The EDR crash angle was calculated as the angle between the lateral and longitudinal ΔV at the time of peak longitudinal ΔV. This angle was compared to the NASS-CDS investigator's estimated PDOF with regard to structural engagement and the collision partner or object. Multiple linear regression was used to establish adjustment factors on ΔV and crash angle between the results calculated based on EDR recorded data and that estimated in NASS-CDS. RESULTS: According to this study, simulation in the newest WinSMASH version (2008) underestimates EDR ΔV by 11 percent for large overlap crashes and 17 percent for small overlap impacts. The older WinSMASH version, used prior to 2008, underestimated each one of these two groups by an additional 7 percentage points. Another significant variable to enhance the prediction was whether the crash examiner had reported the WinSMASH estimated ΔV as low or high. In this study, none of the collision partner groups was significantly different compared to front-to-front impacts. However, with a larger data set a couple of configurations may very well be significantly different. In this study, the crash angle denoted by PDOF in the NASS database underestimates the crash angle calculated from recent EDR modules by 35 percent. CONCLUSION: On average the ΔV and crash angle are underestimated in NASS-CDS when analyzing the data based on collision partner/object and structural engagement. The largest difference is found in small overlap crashes and the least difference in collision scenarios similar to barrier tests. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

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Despite the use of seat belts and modern safety systems, many automobile occupants are still seriously injured or killed in car crashes. Common configurations in these crashes are oblique and small overlap frontal impacts that often lead to chest injuries.To evaluate the injury mechanism in these oblique impacts, an investigation was carried out using mathematical human body model simulations. A model of a simplified vehicle interior was developed and validated by means of mechanical sled tests with the Hybrid III dummy. The interior model was then combined with the human body model THUMS and validated by means of mechanical PMHS sled tests. Occupant kinematics as well as rib fracture patterns were predicted with reasonable accuracy.The final model was updated to conform to modern cars and a simulation matrix was run. In this matrix the boundary conditions, ΔV and PDOF, were varied and rib fracture risk as a function of the boundary conditions was evaluated using a statistical framework.In oblique frontal impacts, two injury producing mechanisms were found; (i) diagonal belt load and (ii) side structure impact. The second injury mechanism was found for PDOFs of 25°-35°, depending on ΔV. This means that for larger PDOFs, less ΔV is needed to cause a serious chest injury.

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BACKGROUND: More than half of car crash fatalities are belted occupants, and the majority of these occur as a consequence of frontal crashes. In an earlier study of crash configuration characteristics, we have shown that 48% of fatalities occurred in frontal small overlap (SO) crashes in which less than 30% of the vehicle front was engaged. Only 23% of fatalities occurred in large overlap (LO) crashes engaging the drive train, similar to most barrier front crash testing procedures. The main purpose of this study was to analyze the characteristics of injury mechanisms and injuries in fatal SO and LO car crashes in Sweden. METHOD: Retrospective examination and analysis of 61 fatally injured occupants from 53 car crashes within a sample area covering 40% of the population of Sweden was conducted. RESULTS: A clear difference in injury mechanisms and injuries was found between SO and LO crashes. The major injury mechanisms in SO crashes are explained by an oblique torso movement and rotation toward the outboard side, which causes a high proportion of serious lateral chest and head injuries. In contrast, LO crashes were generally characterized by serious anterior chest injuries in elderly occupants (> or =60 years). CONCLUSION: Current government and consumer barrier crash test procedures are not designed to estimate the performance of cars and restraint systems for the type of crashes which caused the majority of occupant fatalities in this data set.

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