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The statistical analysis of vehicle crash accident data is generally problematic. Data from commonly used sources is almost never without error and complete. Consequently, many analyses are contaminated with modeling and system identification errors. In some cases the effect of influential factors such as crash severity (the most significant component being speed) driver behavior prior to the crash, etc. on vehicle and occupant outcome is not adequately addressed. The speed that the vehicle is traveling at the initiation of a crash is a significant contributor to occupant risk. Not incorporating it may make an accident analysis irrelevant; however, despite its importance this information is not included in many of the commonly used crash data bases, such as the Fatality Analysis Reporting System (FARS). Missing speed information can result in potential errors propagating throughout the analysis, unless a method is developed to account for the missing information.

Reliable testing of a mechanical system requires the procedures used for the evaluation to be repeatable and reproducible. However, it is never possible to exactly repeat or reproduce the tests that are used for evaluation. To overcome this limitation, a statistical evaluation procedure can generally be used. However, most of the statistical procedures use scalar values as input without the ability to handle vectors or time-histories. To overcome these limitations, two numerical/statistical methods for determining if the impact time-history response of a mechanical system is repeatable or reproducible are evaluated and elaborated upon. Such a system could be a vehicle, a biological human surrogate, an Anthropometric Test Device (ATD or dummy), etc. The responses could be sets of time-histories of accelerations, forces, moments, etc., of a component or of the system. The example system evaluated is the BioRID II rear impact dummy.

The effects of stress in brain material was investigated with experimental and computational idealizations of the head. A water-filled cylinder impacted by a free traveling mass serves to give insight into what could happen to the brain during impact. Under an impact of sufficient velocity, cavitation can occur on the cylinder boundary opposite impact. Limited internal vaporization of the fluid may also occur during severe impact events. Cavitation occurred in these experiments at accelerations greater than 150 g's. Head forms of different sizing will experience an acceleration magnitude inversely proportional to the size difference to produce a similar pressure/cavitation response.

Multiple axial knee impacts and/or a single lateral pelvis impact were performed on a total of 19 cadavers. The impacting surface was padded with various materials to produce different force-time and load distribution characteristics. Impact load and skeletal acceleration data are presented as functions of both time and frequency in the form of mechanical impedance. Injury descriptions based on gross autopsy are given. The kinematic response of the pelvis during and after impact is presented to indicate the similarities and differences in response of the pelvis for various load levels. While the impact response data cannot prescribe a specific tolerance level for the pelvis, they do indicate variables which must be considered and some potential problems in developing an accurate injury criterion.

The response of the head to impact was investigated using live anesthetized and postmortem Rhesus monkeys and repressurized cadavers. The stationary test subject was struck by a guided moving impactor of 10 kg for monkeys; 25 or 65 kg for cadavers. The impactor striking surface was fitted with padding to vary the contact force-time characteristics. The experimental technique used a nine-accelerometer system rigidly mounted on the head to measure head motion, transducers placed at specific points below the skull to record epidural pressure, repressurization of both the vascular and cerebral spinal systems of the cadaver model, and high-speed cineradiography (at 400 or 1000 frames per second) of selected test subjects. The results of the tests demonstrate the potential importance of skull deformation and angular acceleration on the injury produced in the live Rhesus and the damage produced in both the post-mortem Rhesus and the cadaver as a result of impact.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

For the purposes of analyzing and understanding the general effects of a set of different vehicle attributes on overall crash outcome a fleet model is used. It represents the impact response, in a one-dimensional sense, of two vehicle frontal crashes, across the frontal crash velocity spectrum. The parameters studied are vehicle mass, stiffness, intrusion, pulse shape and seatbelt usage. The vehicle impact response parameters are obtained from the NCAP tests. The fatality risk characterization, as a function of the seatbelt use and vehicle velocity, is obtained from the NASS database. The fatality risk is further mapped into average acceleration to allow for evaluation of the different vehicle impact response parameters. The results indicate that the effects of all the parameters are interconnected and none of them is independent. For example, the effect of vehicle mass on fatality risk depends on seatbelt use, vehicle stiffness, available crush, intrusion and pulse shape.