德国工伤保险事故预防机制评介

工伤保险事故预防机制就是工伤保险制度中促进预防工伤事故和职业病的一系列的措施和办法。笔者从管理、经济、法律、技术、心理5个方面具体分析德国工伤保险事故预防机制的具体特点,其中,对管理方面的上层管理机构、研究机构、培训机构、监督机构的设置及其人员配置、企业内部的劳动安全机构及其人员配备进行了研讨;以经济途径为重点从工伤保险费的征收与支出两方面进行了评介;在安全技术方面着重对管理内容即监督事故的隐患、咨询、进行职业病预防、监测与调查、产品安全标准鉴定等进行了介绍;简述了心理方面所开展的安全宣传、教育和培训工作以及相关法律手段。综合分析了工伤保险事故预防机制的形成和运作方式,对其成功经验进行了总结。     

基于TCT的平面交叉口安全评价方法研究

事故率法是评价平面交叉口交通安全水平常用的方法之一,但因其存在基于事故统计方法固有的因事故的稀有性而使评价周期过长、因事故统计的不完全性致使评价结论欠真、缺乏事故严重性程度的考虑等缺点。笔者针对事故率法评价交叉口安全水平存在的上述问题,在概要介绍交通冲突技术并对交通冲突技术的有效性进行分析的基础上,提出了使事故率法与交通冲突技术相结合,用交通冲突代替交通事故改善交叉口事故率法的理论设想。进而,结合质量控制法,研究了同类型交叉口的交通冲突率的临界值的确定,提出了基于交通冲突技术和交叉口交通冲突率的评价方法。     

道路交通安全知识提取方法及其递进式模型的研究

道路交通数据资源日益膨胀和复杂化 ,已经远远超出了人脑的记忆和分析能力。面对道路交通的海量数据 ,传统运用的DBMS和OLTP技术 ,已无法发现隐藏在数据背后的关系、规则和发展趋势等新的内容、知识和信息。因此 ,建立基于DMKD的智能道路交通安全决策支持系统是相关部门急需解决的重大课题。笔者重点介绍了数据挖掘、知识发现的概念 ,提出了基于DW +OLAP +DMKD的道路交通安全决策支持系统 ,通过道路交通系统的要素分析 ,介绍了一种面向属性的粗糙集方法提取规则 ,并阐述了一种递进式规则评价提炼过程。     

Lagging or leading? Exploring the temporal relationship among lagging indicators in mining establishments 2006–2017

Problem: Safety management literature generally categorizes key performance indicators (KPIs) as either leading or lagging. Traditional lagging indicators are measures related to negative safety incidents, such as injuries, while leading indicators are used to predict (and therefore can be used to prevent) the likelihood of future negative safety incidents. Recent theory suggests that traditional lagging indicators also possess characteristics of leading indicators, and vice versa, however empirical evidence is limited. Method: The current research investigated the temporal relationships among establishment-level injuries, near misses, and fatal events using injury and employment data from a sample of 24,910 mining establishments over a 12-year period. Results: While controlling for employee hours worked, establishment-level reported injuries and near misses were associated with of future fatal events across the sample of mines and over the time period studied. Fatal events were also associated with increases in future reported near misses, providing evidence of a cyclic relationship between them. Discussion: These findings challenge the strict categorization of injuries, near misses, and fatal events as lagging indicators. Practical applications: Understanding the KPIs that should be used to manage organizational safety, and how they can be used, is of critical practical importance. The results of the current study suggest that, depending on several considerations, metrics tied to negative safety incidents may be used to anticipate, and possibly prevent, future negative safety events.     

Low rate releases of hazardous light gases under semi-confined geometry: A consequence based approach and case-study application

As evidenced by accident statistics, an important factor when considering the safe operation of process plants is the effective mitigation of the effects of gaseous flammable releases, either by a prevention, or a protection approach. A detailed historical analysis was performed considering accidental scenarios associated with the use and management of light gases, starting from raw data selected from FACTS database and analysed by a causal multi-layer method. Results revealed that the major part of the accidental releases involving methane, hydrogen, ethene, ammonia can be attributed to organizational or process/plant immediate causes. As expected, the most frequent scenarios following the release are fire and explosion. We focus our attention on the development of a short-cut method allowing preliminary evaluation of the maximum gaseous build-up under semi-confined conditions, limiting the effects of the fire/explosion scenario to a tolerable level. The limitations of the model that is applied to selected case-studies and require further experimental validation are critically discussed. The results of the application of the model, which can boast of being safe but not disproportionately conservative, can be set as a maximum threshold in proper designing technical measures aiming at limiting the effects to a tolerable level by protection methods, e.g. isolation, venting, suppression and containment.     

PDE accident model from a safety information perspective and its application to Zhangjiakou fire and explosion accident

Accident models can provide theoretical frameworks for determining the causes and mechanisms of accidents, and thus are theoretical bases for accident analysis and prevention. The role of safety information in accident causation is profound. Thus, safety information is an important and essential perspective for developing accident models. This study presents a new accident model developed from a safety information perspective, called the Prediction—Decision—Execution (PDE) accident model. Because the PDE accident model is an emerging accident model that was proposed in 2018, its analysis logic and viability remain to be discussed. Thus, the main contributions of this study include two aspects: (i) detailed explanation of the analysis logic of the PDE accident model, and (ii) case-study examination of the Zhangjiakou fire and explosion accident, a serious accident that occurred in China in 2018, to demonstrate the viability of the PDE accident model. Results show that this is a safety-information-driven accident model that can provide a new and effective methodology for accident analysis and prevention, and safety management.     

Accident consequence calculation of ammonia dispersion in factory area

With the widespread use of ammonia in the process industry, more and more accidents were caused by ammonia leakage and dispersion. The dispersion of ammonia is determined by its physical properties, release source conditions and atmospheric environment. Full-scale numerical simulation based on CFD theory was carried out to study the dispersion law of ammonia in a food factory. It was found that ammonia concentrated on the symmetric plane and showed an upward movement near the source. Moreover, the effect of pressure on the dispersion of ammonia was explored showing that the concentration of ammonia near the source increased with the increase of pressure, while the dispersion of ammonia far from the source is mainly influenced by wind field. Last but not the least, the dangerous area completely covers the obstacle region according to the harmful concentration, but the lethal concentration range and explosion range both only existed near the release source. Correspondingly, the concentration of ammonia in the region far from the symmetric plane can be regarded as a safe area. When the accident happens, one should stay away from the release source and evacuate towards the sides in a timely manner. We hope that this work can provide an effective method in predicting the impact of ammonia dispersion and can arouse concerns over the public safety.     

On the application of the window of opportunity and complex network to risk analysis of process plants operations during a pandemic

To quantify the pandemic specific impact with respect to the risk related to the chemical industry, a novel risk analysis method is proposed. The method includes three parts. Firstly, the two types of “window of opportunity” (WO) theory is proposed to divide an accident life cycle into two parts. Then, a qualitative risk analysis is conducted based on WO theory to determine possible risk factors, evolution paths and consequences. The third part is a quantitative risk analysis based on a complex network model, integrating two types of WO. The Fuzzy set theory is introduced to calculate the failure probabilities of risk factors and the concept of risk entropy is used to represent the uncertainty. Then the Dijkstra algorithm is used to calculate the shortest path and the corresponding probability of the accident. The proposed method is applied to the SCR denitrition liquid ammonia storage and transportation system. The results show that it is a comprehensive method of quantitative risk analysis and it is applicable to risk analysis during the pandemic.     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

新时期加强和改进大学生安全教育的实践与探索

针对高校在大学生安全教育方面重视不够,内容观点陈旧,教育手段单一等主要问题及其产生的原因,通过分析并找出解决问题的方法;树立以人为本、珍爱生命的理念,遵循安全第一,预防为主的原则,采取多种措施,切实开展安全教育,普及安全知识与防范技能,培养学生健全的法律意识、安全意识,提高自我保护和安全防范能力;制订相关的法律法规与规章制度,完善安全教育的领导体制与运行机制,切实做好高校大学生安全教育工作。