Effect of pyrolysis and oxidation characteristics on lauric acid and stearic acid dust explosion hazards

The effect of pyrolysis and oxidation characteristics on the explosion sensitivity and severity parameters, including the minimum ignition energy MIE, minimum ignition temperature MIT, minimum explosion concentration MEC, maximum explosion pressure P_max, maximum rate of pressure rise (dP/dt)_max and deflagration index K_st, of lauric acid and stearic acid dust clouds was experimentally investigated. A synchronous thermal analyser was used to test the particle thermal characteristics. The functional test apparatuses including the 1.2 L Hartmann-tube apparatus, modified Godbert-Greenwald furnace, and 20 L explosion apparatus were used to test the explosion parameters. The results indicated that the rapid and slow weight loss processes of lauric acid dust followed a one-dimensional diffusion model (D1 model) and a 1.5 order chemical reaction model (F1.5 model), respectively. In addition, the rapid and slow weight loss processes of stearic acid followed a 1.5 order chemical reaction model (F1.5 model) and a three-dimensional diffusion model (D3 model), respectively, and the corresponding average apparent activation energy E and pre-exponential factor A were larger than those of lauric acid. The stearic acid dust explosion had higher values of MIE and MIT, which were mainly dependent on the higher pyrolysis and oxidation temperatures and the larger apparent activation energy E determining the slower rate of chemical bond breakage during pyrolysis and oxidation. In contrast, the lauric acid dust explosion had a higher MEC related to a smaller pre-exponential factor A with a lower amount of released reaction heat and a lower heat release rate during pyrolysis and oxidation. Additionally, due to the competition regime of the higher oxidation reaction heat release and greater consumption of oxygen during explosion, the explosion pressure P_m of the stearic acid dust was larger in low concentration ranges and decayed to an even smaller pressure than with lauric acid when the concentration exceeded 500 g/m³. The rate of explosion pressure rise (dP/dt)_m of the stearic acid dust was always larger in the experimental concentration range. The stearic acid dust explosion possessed a higher P_max, (dP/dt)_max and K_st mainly because of a larger pre-exponential factor A related to more active sites participating in the pyrolysis and oxidation reaction. Consequently, the active chemical reaction occurred more violently, and the temperature and overpressure rose faster, indicating a higher explosion hazard class for stearic acid dust.     

Risk factors for the severity of injury incurred in crashes involving on-duty police cars

Objective: This article explores the risk factors associated with police cars on routine patrol and/or on an emergency run and their effects on the severity of injuries in crashes.

Methods: The binary probit model is used to examine the effects of important factors on the risk of injuries sustained in crashes involving on-duty police cars.

Results: Several factors significantly increase the probability of crashes that cause severe injuries. Among those causes are police officers who drive at excessive speeds, traffic violations during emergency responses or pursuits, and driving during the evening (6 to 12 p.m.) or in rainy weather. Findings also indicate some potential issues associated with an increase in the probability of crashes that cause injuries. Younger police drivers were found to be more likely to be involved in crashes causing injuries than middle-aged drivers were. Distracted driving by on-duty police officers as well as civilian drivers who did not pull over to let a police car pass in emergency situations also caused serious crashes.

Conclusions: Police cars are exempted from certain traffic laws under emergency circumstances. However, to reduce the probability of being involved in a crash resulting in severe injuries, officers are still obligated to drive safely and follow safety procedures when responding to emergencies or pursuing a car. Enhancement of training techniques for emergency situations or driving in pursuit of an offender and following the safety procedures are essential for safety in driving during an emergency run by police.     

基于Logistic的不同车型碰撞行人事故严重程度致因分析

为定量分析不同车型碰撞行人事故严重程度影响因素,以美国北卡罗来纳州2007-2016年人车碰撞事故数据为样本,将其分为小轿车、SUV、货车碰撞行人事故3类,以事故严重程度为因变量,交通参与者属性、道路、环境条件和事故特征为候选自变量,分别建立累计logistic模型进行对比分析,探究人、车、路和环境因素对人车碰撞事故严...     

An in-depth analysis of self-reported cycling injuries in single and multiparty bicycle crashes in Denmark

Introduction: Cycling is one of the main forms of transportation in Denmark. However, while the number of traffic crash fatalities in the country has decreased over the past decade, the frequency of cyclists killed or seriously injured has increased. The high rate of serious injuries and fatalities associated with cycling emphasizes the increasing need for mitigating the severity of such crashes. Method: This study conducted an in-depth analysis of cyclist injury severity resulting from single and multiparty bicycle-involved crashes. Detailed information was collected using self-reporting data undertaken in Denmark for a 12-month period between 1 November 2012 and 31 October 2013. Separate multilevel logistic (MLL) regression models were applied to estimate cyclist injury severity for single and multiparty crashes. The goodness-of-fit measures favored the MLL models over the standard logistic models, capturing the intercorrelation among bicycle crashes that occurred in the same geographical area. Results: The results also showed that single bicycle-involved crashes resulted in more serious outcomes when compared to multiparty crashes. For both single and multiparty bicycle crash categories, non-urban areas were associated with more serious injury outcomes. For the single crashes, wet surface condition, autumn and summer seasons, evening and night periods, non-adverse weather conditions, cyclists aged between 45 and 64 years, male sex, riding for the purpose of work or educational activities, and bicycles with light turned-off were associated with severe injuries. For the multiparty crashes, intersections, bicycle paths, non-winter season, not being employed or retired, lower personal car ownership, and race bicycles were directly related to severe injury consequences. Practical Applications: The findings of this study demonstrated that the best way to promote cycling safety is the combination of improving the design and maintenance of cycling facilities, encouraging safe cycling behavior, and intensifying enforcement efforts.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

Investigation of injury severities in single-vehicle crashes in North Carolina using mixed logit models

IntroductionRoadway departure (RwD) crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, are one of the most lethal crash types. According to the FHWA, between 2015 and 2017, an average of 52 percent of motor vehicle traffic fatalities occurred each year due to roadway departure crashes. An avoidance maneuver, inattention or fatigue, or traveling too fast with respect to weather or geometric road conditions are among the most common reasons a driver leaves the travel lane. Roadway and roadside geometric design features such as clear zones play a significant role in whether human error results in a crash. Method: In this paper, we used mixed-logit models to investigate the contributing factors on injury severity of single-vehicle ROR crashes. To that end, we obtained five years' (2010–2014) of crash data related to roadway departures (i.e., overturn and fixed-object crashes) from the Federal Highway Administration's Highway Safety Information System Database. Results: The results indicate that factors such as driver conditions (e.g., age), environmental conditions (e.g., weather conditions), roadway geometric design features (e.g., shoulder width), and vehicle conditions significantly contributed to the severity of ROR crashes. Conclusions: Our results provide valuable information for traffic design and management agencies to improve roadside design policies and implementing appropriately forgiving roadsides for errant vehicles. Practical applications: Our results show that increasing shoulder width and keeping fences at the road can reduce ROR crash severity significantly. Also, increasing road friction by innovative materials and raising awareness campaigns for careful driving at daylight can decrease the ROR crash severity.     

城市土地置换过程中土壤有机污染物健康影响度评价

城市化过程中日益严峻的土壤污染已成为制约城市土地可持续开发利用的主要因素,而有机物已成为土壤中重要的污染物. 在我国目前缺乏相关环境质量标准的背景下,选择某区域土地置换开发为案例,尝试采用人体健康影响度评价法,对城市土地置换中土壤有机污染物可能给未来入住人群健康带来的潜在危害进行了分析与定量评价,识别出该区域土壤有机污染物以2,4-二硝基酚、五氯酚以及PAHs为主. 需要指出的是,参与评价的有机污染物仅为被检出有机污染物总量的一部分,因此评价结果中的健康影响度可能较实际数值偏低. 随着环境管理工作的深入进行,在城市土地置换过程中应逐步加强环境健康风险评价的研究.       

车用高分子材料不同地区户外曝晒试验相关性研究

目的将3种高分子材料以及3种车用外饰材料分别投放在中国海南琼海和美国佛罗里达州2种典型湿热环境中进行户外曝晒试验,研究气候相似的2种地区的试验相关性。方法通过测试相同时间间隔下不同材料在2处试验场曝晒过程中的黄变程度,表征材料的老化现象。采用斯皮尔曼等级相关系数的统计方法,研究材料在2个地区相同时间节点的试验结果的相关性,并利用时间同轴的作图方法比较2个地区严酷度的差异。结果琼海与佛罗里达州2个地区在各个时间节点的相关系数接近于1,且在材料黄变方面呈现一定比例关系。结论琼海和佛罗里达州2个地区的试验结果呈现出较好的相关性,且严酷度比值约为琼海︰佛罗里达=1︰1.19。     

The crash severity impacts of fixed roadside objects

INTRODUCTION: This study analyzes the in-service performance of roadside hardware on the entire urban State Route system in Washington State by developing multivariate statistical models of injury severity in fixed-object crashes using discrete outcome theory. The objective is to provide deeper insight into significant factors that affect crash severities involving fixed roadside objects, through improved statistical efficiency along with disaggregate and multivariate analysis. METHOD: The developed models are multivariate nested logit models of injury severity and they are estimated with statistical efficiency using the method of full information maximum likelihood. RESULTS: The results show that leading ends of guardrails and bridge rails, along with large wooden poles (e.g. trees and utility poles) increase the probability of fatal injury. The face of guardrails is associated with a reduction in the probability of evident injury, and concrete barriers are shown to be associated with a higher probability of lower severities. Other variables included driver characteristics, which showed expected results, validating the model. For example, driving over the speed limit and driving under the influence of alcohol increase the probability of fatal accidents. Drivers that do not use seatbelts are associated with an increase in the probability of more severe injuries, even when an airbag is activated. IMPACT ON INDUSTRY: The presented models show the contribution of guardrail leading ends toward fatal injuries. It is therefore important to use well-designed leading ends and to upgrade badly performing leading ends on guardrails and bridges. The models also indicate the importance of protecting vehicles from crashes with rigid poles and tree stumps, as these are linked with greater severities and fatalities.