Neck Injury Risk in Rear-End Impacts. Risk Factors and Neck Injury Criterion Evaluation with Madymo Modelling and Real-Life Data
Soft-tissue neck injuries, also termed AIS 1 neck injuries, are common after low-speed rear-end impacts. These injuries, which can be long-lasting, have increased in frequency during the past few decades. There is no consensus regarding injury mechanisms; however, injury criteria have been proposed, without yet being fully evaluated. Factors influencing the injury risk are identified, but rarely quantified. Validated injury criteria, and precise knowledge of factors influencing injury risk, are essential when developing restraints to reduce AIS 1 neck injuries in a variety of rear-end impact conditions. This thesis aims to evaluate, with valid models, risk factors and injury criteria applicable to improving safety systems for low-speed rear-end impacts.
Madymo models of the BioRID and car seats were developed and validated. Sensitivity analyses were used to identify and evaluate occupant and seat-related factors; the BioRID I, in four seats selected from a neck-disability risk ranking, was exposed to two crash pulses. Paired comparison designs were applied to the NICmax outcomes in ranking the four seats: this was compared with a neck-disability risk ranking of seats. The real-life data used comprised a variety of unspecified rear-end impact conditions; therefore, a broad set of crash pulses was used to reduce the influence of crash pulse parameters on the NICmax. Linear regressions between NICmax and crash-pulse parameters were executed. The BioRID II, in three seats, was exposed to recorded crash pulses from 79 impacts, which involved 110 occupants with known injury outcome. Seat geometry and seating posture were varied to obtain a range of NICmax values for each occupant. Using diagnostic tests, the NICmax predictability of long-term AIS 1 neck injuries was evaluated. Finally, the BioRID II, in the three seats, was exposed to 20 recorded crash pulses with potential to cause neck injuries, and the influence of head restraint positions on long-term AIS 1 neck injury risk was analysed.
The sensitivity analyses revealed recliner characteristics to be the most influential parameter for the high crash pulse; the head restraint position was the most influential for the low one. Exposing the seats to the crash-pulse demonstrated that the NICmax identified the ranks of the four seats in ranking. The regression analyses showed that the change of velocity during the first 85 ms of the impact correlated with NICmax; therefore, the Δv 85 ms can potentially quantify impact severity.
The diagnostic tests showed that the NICmax predicted long-term AIS 1 neck injuries for variations in seat geometry and seating posture. The relation between NICmax and injury outcome was used to establish risk curves for the NICmax. Evaluating the influence of head restraint position, it was found that neck injury risk is decreased by 0.1 for approximately 2.5 cm of backset reduction. Only for the most severe impacts, can a higher positioned head restraint significantly reduce the injury risk.
Combining Madymo modelling and real-life data, and applying statistical methods, proved to be useful for evaluating risk factors and the Neck Injury Criterion.