Evaluation of military helmets and roof padding on head injury potential from vertical impacts

Objective: Soldiers in military vehicles subjected to underbelly blasts can sustain traumatic head and neck injuries due to a head impact with the roof. The severity of head and neck trauma can be influenced by the amount of head clearance available to the occupant as well as factors such as wearing a military helmet or the presence of padding on the interior roof. The aim of the current study was to examine the interaction between a Hybrid III headform, the helmet system, and the interior roof of the vehicle under vertical loading.

Methods: Using a head impact machine and a Hybrid III headform, tests were conducted on a rigid steel plate in a number of different configurations and velocities to assess helmet shell and padding performance, to evaluate different vehicle roof padding materials, and to determine the relative injury mitigating contributions of both the helmet and the roof padding. The resultant translational head acceleration was measured and the head injury criterion (HIC) was calculated for each impact.

Results: For impacts with a helmeted headform hitting the steel plate only, which represented a common scenario in an underbelly blast event, velocities of ≤6 m/s resulted in HIC values below the FMVSS 201U threshold of 1,000, and a velocity of 7 m/s resulted in HIC values well over the threshold. Roof padding was found to reduce the peak translational head acceleration and the HIC, with rigid IMPAXX foams performing better than semirigid ethylene vinyl acetate (EVA) foam. However, the head injury potential was reduced considerably more by wearing a helmet than by the addition of roof padding.

Conclusions: The results of this study provide initial quantitative findings that provide a better understanding of helmet–roof interactions in vertical impacts and the contributions of the military helmet and roof padding to mitigating head injury potential. Findings from this study will be used to inform further testing with the future aim of developing a new minimum head clearance standard for occupants of light armored vehicles.     

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

Aims: Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

Methods: A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004–2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

Results: Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

Conclusions: Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.     

Undercounting of large trucks in federal and state crash databases: Extent of problem and how to improve accuracy of truck classifications

Objective: Prior research suggested that single-unit trucks are undercounted when using vehicle body codes in the Fatality Analysis Reporting System (FARS). This study explored the extent of the misclassification and undercounting problem for crashes in FARS and state crash databases.

Methods: Truck misclassifications for fatal crashes were explored by comparing the Trucks Involved in Fatal Accidents (TIFA) database with FARS. TIFA used vehicle identification numbers (VINs) and survey information to classify large trucks. This study used VINs to improve the accuracy of large truck classifications in state crash databases from 5 states (Delaware, Maryland, Minnesota, Nebraska, and Utah).

Results: The vehicle body type codes resulted in a 19% undercount of single-unit trucks in FARS and a 23% undercount of single-unit trucks in state databases. Tractor-trailers were misclassified less often. Misclassifications occurred most frequently among single-unit trucks in the weight classes of 10,001–14,000 pounds.

Conclusions: The amount of misclassification of large trucks is large enough to potentially affect federal and state decisions on traffic safety. Using information from VINs results in more complete and accurate counts of large trucks involved in crashes. The National Transportation Safety Board recommended actions to improve federal and state crash data.     

Rating the Aggressivity of Australian Passenger Vehicles Towards Other Vehicle Occupants and Unprotected Road Users

Two measures of aggressivity of Australian passenger vehicles have been developed. The first measures the aggressivity to occupants of other cars. This type of aggressivity rating is based on two-car crashes between passenger vehicles and measures the injury risk each make/model in the collisions poses to the drivers of the other vehicles. The second measures aggressivity to unprotected road users. These aggressivity ratings reflect the threat of severe injury to pedestrians, bicyclists and motorcyclists by die make/model of vehicle colliding with them. This analysis was based on nearly 102,000 drivers involved in tow-away crashes with the makes/models which were the focus of the study and on nearly 22,000 injured pedestrians, bicyclists, and motorcyclists. The results suggest that crasbworthiness and aggressivity are two different aspects of a vehicle's safety performance, with good performance on one dimension not necessarily being associated with good performance on the other.     

洪水作用下汽车的起动流速研究

针对洪水作用下汽车的起动条件开展了一系列的研究:首先分析部分淹没状态下汽车的受力情况,结合滑动平衡的临界起动条件建立相关方程,导出了洪水中汽车起动流速公式;然后在室内水槽中对三款模型车进行了一系列的起动试验。试验结果表明:对于同一款模型车,平行于水流方向放置时,起动流速与水深的相关性较好;并且水深越大,起动流速越小。接着运用试验资料率定了起动流速公式中的相关参数。最后采用模型相似率及率定后的计算公式估算了原型车辆在不同水深下的起动流速,两种方法所得的结果较为接近,故预测结果较为可靠。     

冷凝膜油气回收技术在轻质油汽车装车中的应用

介绍了油气回收技术的基本原理,着重介绍了冷凝膜回收工艺技术的特点,及冷凝膜回收装置在中国石化青岛石油化工有限责任公司轻质油汽车装车的应用情况,分析了存在的问题及改进建议。     

利用北斗卫星监控和管理危化品运输系统的实现

介绍了北斗卫星实时监控系统的概况、功能特点及应用分析,根据石油危化品运输增长的现状及企业安全生产的需要,阐明系统的实现对石油危化品运输过程中的生产安全监控和应急调度指挥有重大的实际意义。     

不同载荷下轮式车辆运输振动数据预测模型研究

目的为便于执行GJB 150A进行车辆运输振动试验,研究了不同载荷下运输振动数据预测模型。方法对模型的特点和适用范围进行了分析;运用该模型分析了不同载荷下运输振动试验的试验数据规律。结果随着载荷的增加,运输振动逐渐减小,能够反映轮式车辆不同载荷下的运输振动规律,给出了运用该模型对不同载荷下车辆运输振动数据的预测方法。结论该模型简单实用,在执行GJB 150A进行运输振动试验过程中,若直接引用标准中的数据,可以采用该模型对不同载荷下的运输振动试验数据进行预测。     

高原环境对车辆动力性的影响及动力提升措施

在总结我国高原气候和地理环境特点的基础上,从反映车辆动力性能的指标出发,以加速时间、最大爬坡度和最高车速入手,理论分析了对整车高原动力性影响较大的因素,主要包括有效热效率、循环喷油量、滚动阻力系数、空气密度对空气阻力的影响等。通过分析高原环境对这些因素的影响,总结出了高原环境对车辆动力性的影响机理,并进一步提出了整车高原动力性改进的技术措施,认为先进增压、燃烧优化、高压共轨燃油喷射、高原环境标定、热平衡控制和富氧进气燃烧等技术措施成为提高车辆动力性的有效技术措施。