核电站核事故核素污染评估模式

利用修正了的高斯模式探讨核电站核素污染事故中的核素扩散。分析了边界条件,气象条件和核素衰变规律对核素扩散污染的影响,并进一步讨论了核素的污染范围,距源距离及核素的沉积量,可作为确定应急安全的理论依据。     

因果分析与系统安全性风险评价方法

综合了故障树分析和事件树分析的方法,提出因果分析的框架,研究了基于因果分析建立事故脚本的方法。在此基础上,还对因果分析的概率风险评价方法进行研究,并利用该评价方法,对电机过热的安全性问题进行分析,给出了分析计算的结果     

试论环境犯罪中因果关系的确立原则

修订后的《刑法》在环境刑事立法上虽有重大发展，但摁环境犯罪的特殊性而使传统的刑法因果关系理论受到冲击，新因果关系确立原则－因果关系推定原则应运而生。我国应以最高人民法院发布司法解释的形式确立因果关系推定原则，将其适用于污染环境的犯罪行为和部分破坏环境的犯罪行为的因果关系确立中。     

Highway-rail grade crossings accident prediction using Zero Inflated Negative Binomial and Empirical Bayes method

Introduction: Recently the Federal Railroad Administration (FRA) released a new model for accident prediction at railroad grade crossings using a Zero Inflated Negative Binomial (ZINB) model with Empirical Bayes (EB) adjustments for accident history (2). This new model is adopted from the work that was conducted by the authors (3–6). The unique feature of the new FRA model is that it has a single equation for all three warning devices (crossbuck, flashing light, and gates) and uses the same variables regardless of the warning devices at the crossing. Since the New FRA model incorporates the warning device category as one of the variables in its model equation, the predicted accident frequency is higher when a crossing has crossbucks than flashing lights, and higher when it has flashing lights than gates. While this model is significantly better than the old USDOT model (7), its shortcoming is that the single equation does not accurately represent the field condition. Method: This paper presents the ZINEBS model (Zero Inflated Negative binomial with Empirical Bayes adjustment System). The ZINEBS model gives three different equations depending on the type of warning device used at the crossings (gates, flashing lights, and crossbucks). The three equations use variables, some of which are common across all warning devices, while other variables are specific to a warning device. The predicted values for the ZINEBS model show a closer agreement with the field data than the new FRA model. This observation was true for all three warning device types analyzed. Practical Applications: Based on the results of this study, the ZINEBS compliments the new FRA model and should be used when the single equation is not adequately representing the role of traffic control device types and relevant variables associated with that device type.     

Revising HFACS for SMEs in the chemical industry: HFACS-CSMEs

Chemical accidents have occurred frequently in recent years, and most have occurred in small and medium-sized enterprises (SMEs). SMEs in the chemical industry face greater challenges than large enterprises with regard to accident prevention. However, SMEs have been unable to effectively learn from accidents due to the limited resources. The accident causation model is an effective tool to help the analyst learn from accidents. As a systematic accident causation model, the causes classification in the human factors analysis and classification system (HFACS) can match the characteristics of SMEs, but the cause of chemical accidents can be ineffectively identified by HFACS. In this study, HFACS was revised for the SMEs in the chemical industry, mainly consisting of three parts. First, based on the definition of factors in the original HFACS, the extended HFACS framework was obtained, which include 78 manifestations with the characteristics of the chemical accidents. Second, 101 accidents occurring in a SME in the chemical industry from 2012 to 2016 were analyzed though the extended HFACS framework. Finally, a new model, known as the HFACS-CSMEs, was obtained by further revising the manifestations and causes classification according to the statistical results of the accident analysis. HFACS-CSMEs consists of 15 cause factors and 56 manifestations, which can effectually identify and distinguish the causes in chemical accidents. Moreover, the easy-to-understand and statistically acceptable features of HFACS-CSMEs can cater to the SMEs regarding accident analysis. HFACS-CSMEs solves the problem that HFACS cannot be directly applied to chemical accidents and provides new ideas about preventing accidents in SMEs in the chemical industry.     

Effect of the zero-tolerance drinking and driving law on mortality due to road traffic accidents according to the type of victim,sex, and age in Rio de Janeiro,Brazil: An interrupted time series study

Objective: The objective of this study was to estimate the effect of the Brazilian zero-tolerance drinking and driving law on mortality rates due to road traffic accidents according to the type of victim, sex, and age.

Methods: An interrupted time series design was used to compare yearly mortality rates due to road traffic accidents in Rio de Janeiro, Brazil, before and after the zero-tolerance drinking and driving law came into effect on June 19, 2008. Yearly mortality rates were compared according to the type of victim: pedestrian, cyclist, motorcyclist, and vehicle occupant. We used the Prais-Winsten procedure of autoregression in the analysis of time series; the outcome of this analysis was the annual percentage change in the rates. Overall and stratified analyses were conducted to investigate whether the zero-tolerance drinking and driving law may have had a distributional effect on mortality rates due to road traffic accidents depending on sex and age group; a significance level of P < .01 was accepted.

Results: From 1999 to 2016, there were 15,629 deaths due to road traffic accidents in Rio de Janeiro. The effect of the zero-tolerance drinking and driving law on overall mortality rates due to road traffic accidents in Rio de Janeiro was not statistically significant. However, among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes and aged ≥20 years, the effect of the zero-tolerance drinking and driving law was to decrease mortality due to road traffic accidents at a yearly rate.

Conclusion: There is evidence of reduced mortality rates due to road traffic accidents among cyclists and motorcyclists aged ≥60 years and among pedestrians of both sexes aged ≥20 years in the second major Brazilian capital 9 years after the zero-tolerance drinking and driving law was adopted.     

An urban pipeline accident model based on system engineering and game theory

Urban pipeline accidents are caused by complex social-technical factors, in which urban communities and pipeline systems are involved. Such accidents can thus be investigated from the viewpoint of system engineering. System-Theoretic Accident Model and Processes (STAMP) is a systemic method for safety assessment, which has been adopted in many domains. This approach can provide deep insights of accident causes by considering direct and indirect factors. Meanwhile, competition and cooperation between stakeholders in accidents are observed. Therefore, these parties can also be analyzed with the game theory. That is, stakeholders in STAMP can be regarded as players in game. The aim of this paper is to provide a new insight to analyze urban pipeline accidents by considering both STAMP and game theory. In this paper, we proposed an accident model for urban pipelines, with a case study of China-Qingdao pipeline accident occurred in 2013. We concluded that accident reasons can be investigated in-depth and lessons can be learned from analyzing causal factors by using STAMP. Based on results generated from STAMP, we applied the game theory to analyze roles that government and companies act in the China-Qingdao urban pipeline accident. The results show that current punishment and incentive systems are incomplete, lacking of the driving force and constraining force for the stakeholders involved in the accident.     

Combinations of factors contribute to young driver crashes

Introduction: Motor-vehicle crashes are a leading cause of death in adolescence and young adults. A multitude of factors, including skill level, inexperience, and risk taking behaviors are associated with young drivers’ crashes. This research investigated whether combinations of factors underlie crashes involving young drivers. Method: A retrospective longitudinal study was conducted on population-wide one- and two-car crashes in Great Britain during years 2005–2012 per driver age (17–20, 21–29, 30–39, 40–49) and sex. Reporting officers provided their assessment of the factors contributing to crashes. Principal components analysis was conducted to identify combinations of factors underlying young drivers’ crashes. Factor combinations, including challenging driving conditions, risk taking behaviors, and inexperience were implicated in young drivers’ crashes. Results: Combinations of factors reveal new insights into underlying causes of crashes involving young drivers. One combination revealed that slippery roads due to poor weather pose greater risk to young drivers who are inexperienced and likely to exceed the appropriate speed. The findings motivate new policy recommendations, such as educating young drivers about the importance of adjusting their speed to the road conditions.     

A process mapping model for calculating indirect costs of workplace accidents

This article follows an earlier one in which four criteria and four bases for the development of an indirect-cost calculation model adapted to the accuracy requirements and time constraints of workplace decision-makers were established. A two-level model for calculating indirect costs using process mapping of the organizational response to a workplace accident is presented. The model is based on data collected in interviews with those employees in charge of occupational health and safety in 10 companies of various sizes in different industry sectors. This model is the first to use process mapping to establish the indirect costs of workplace accidents. The approach allows easy identification of the duration and frequency of actions taken by stakeholders when a workplace accident occurs, facilitates the collection of the information needed to calculate indirect costs and yields a usable, precise result. A simple graphic representation of an organization's accident processes helps the user understand each accident's cost components, allowing the identification and reduction of inefficiencies in the overall process. Impact on Industry: By facilitating data collection and shortening the time needed to assess indirect costs of workplace accidents, this indirect cost calculation tool is better suited for workplace use than those currently available.