Reference criteria for the identification of accident scenarios in the framework of land use planning

Land use planning (LUP) around industrial sites at risk of major accidents requires the application of sound approaches in the selection of credible accident scenarios. In fact, the ‘technical’ phase of LUP is based on the identification and assessment of relevant accident scenarios. An improper choice of scenarios may critically affect both the ‘technical’ phase of risk assessment and the following ‘policy’ phase concerning decision making on land-use restrictions and/or licensing. The present study introduces a procedure aimed at the systematic identification of reference accident scenarios to be used in the gathering of technical data on potential major accidents, which is a necessary step for LUP around Seveso sites. Possible accident scenarios are generated by an improved version of the MIMAH methodology (Methodology for the Identification of Major Accident Hazards). The accident scenarios are then assessed for LUP relevance considering severity, frequency and time scale criteria. The influence of prevention and mitigation barriers is also taken into account. Two applications are used to demonstrate the proposed procedure. In both case-studies, the proposed methodology proved successful in producing consistent sets of reference scenarios.     

Database for accidents and incidents in the fuel ethanol industry

The purpose of the present research is to collect information about accidents and incidents that have occurred at fuel ethanol facilities from 1998 to October 2014, and to keep complete unified records of them in a database. The developed database contains general information about the accident or incident, its sequence, mitigation measures, its causes and consequences for humans, environment and for the plant. Until now, this information is not available. The work consisted in gathering information from different documental sources and subsequent organization in a database. It complements the previous work made for biodiesel industry and fills the existing gap in the field of ethanol. Knowledge about this information enables us to manage plant risks, since the accidents that are more likely to occur and the main sources of risk can be easily identified. Also, it makes it possible to exchange information with interested third parties. Statistical analysis shows that accident frequency has an oscillatory behavior, rising in the last year. Fire is the most common type of accident, while equipment mechanical failure is the main cause of accident. Partial material loss has been identified as the most common consequence. Finally, some conclusions are obtained concerning to the importance of having an updated and complete accident and incident database.     

基于动态贝叶斯网络的石化装置火灾事故动态风险分析

为揭示石油炼化装置事故风险动态特性和事故情景演变路径,在对石化装置进行风险因素分析的基础上构建石化装置火灾事故故障树,基于贝叶斯网络非常规突发事故的演变过程,构建情景演变下的动态贝叶斯网络模型,在综合考虑应急措施的基础上,利用MATLAB软件和联合概率公式计算出各种事故场景的状态概率.以丙烯精馏装置火灾事故为例,结果表...     

基于粒子群算法的燃气管线泄漏疏散能力分析

为研究燃气管线泄漏事故人员疏散能力,统计分析近年国内燃气泄漏典型事故,得出第三方违章作业施工为燃气泄漏事故比例最高的直接原因及燃气泄漏事故伤亡人数发展趋势,在此基础上,引入粒子群PSO算法,以某施工引起的燃气管线泄漏事故为实例,研究领导者的领导能力和应急处置能力对员工之间信息交流及人员应急疏散能力的影响。分析实例显示现场领导者学习因子偏低,指挥能力差,直接影响事故现场的应急疏散自救行为,甚至改变疏散路径。并进一步分析模拟得出,学习因子提高后,现场领导者和员工的信息更新与交换效率大幅提升,应急疏散能力随之提高,进而提出实用性对策措施和建议,为提升燃气管线泄漏事故应急疏散能力提供技术参考。     

The functioning and status of the EC's major accident reporting system on industrial accidents

This paper describes the functioning and current status of the European Commission's Major Accident Reporting System (MARS), dedicated to collect in a consistent way data on major industrial accidents involving dangerous substances from the Member States of the European Union under the requirements of the `Seveso Directives', to analyse and statistically process them, and to distribute all non-confidential accidents data and analysis results to the Member States. This modern information exchange and analysis tool is made up of two connected parts: one for each local unit (i.e. for the Competent Authority of each Member State), and one central part for the European Commission. The local as well as the central parts of this network can serve both as data logging systems and, on different levels of complexity, as data analysis tools. The central database allows complex pattern analysis, identifying and analysing the succession of disruptive factors leading to an accident. On this basis, “lessons learned” can be formulated for the industry or regulatory bodies for further accident prevention. Results of various overall analyses of the contents of MARS are given. The availability of MARS data and analysis results is described.     

事故与熵──事故发生可能性计算的新方法

从熵增加的观点描述了事故的本质，剖析了人机系统的实质与特性，提出了风险熵与事故势的概念，给出了计算机风险熵与事故势的方法。结果表明，系统具有二重性。在系统运行期间，系统具有封闭体系的特性；在休整期间，系统具有开放体系的特性。事故是运行系统的必然发展趋势，是运行系统的固有属性，是一种自发过程。由于在系统熵增加的过程中信息及能量的交换，可以把事故定义为系统熵增加的结果。避免事故发生的原理是不断地向系统输入信息或负熵以抵消系统内部的熵增加。     

Research on the prediction model of hazardous chemical road transportation accidents

In recent years, hazardous chemicals road transport accidents have occurred frequently, causing huge casualties and property losses, and accident risk assessment has become the focus of researchers' research. To predict the risk probability value of hazardous chemical road transport accidents, first, we compiled data on road transportation accidents of hazardous chemicals in China in the past five years. And the nine nodes in the Bayesian network (BN) structure were defined in combination with relevant classification standards. The optimal Bayesian network structure for hazardous chemical road transport accidents was determined based on the K2 algorithm and the causalities between the nodes. Second, the node conditional probabilities were derived by parameter learning of the model using Netica, and the validity of the model was verified using the 5-fold cross-validation method. Last, the Bayesian network model of hazardous chemical road transport accidents is used to analyze accident examples, and the accident chain of “rear-end-leakage” is predicted, and the accident is most likely to be disposed of within 3–9 h. The study shows that the derived accident prediction model for hazardous chemical road transportation can reason reasonably about the evolution of accident scenarios and determine the probability values of accident risks under different parameter conditions.     

地下采矿安全信息管理系统开发与应用

地下矿床开采潜在着众多的事故隐患，因此，为了进行事故隐患预防和预测，进行矿山安全信息管理和事故分析就显得十分重要。针对金川矿区的地质、采矿条件，研究开发了集“安全信息管理与事故分析”于一体的计算机辅助系统。简要地介绍了该系统的功能、作用以及应用情况。     

Evaluation on consequences prediction of fire accident in emergency processes for oil-gas storage and transportation by scenario deduction

This paper takes the safety in emergency processes as the starting point, from the perspective of scenario deduction, to study the consequences of fire accidents for oil-gas storage and transportation. Through the statistical analysis of actual accident cases, 19 frequently occurring basic scenarios in emergency processes are summarized. The scenario evolution paths of fire accidents for oil-gas storage and transportation are given by analyzing the evolution law of the accident development. Fuzzy numbers are introduced to express experts' qualitative judgment on accident scenarios. The empirical probabilities of scenario nodes are obtained by defuzzification calculation, and the state probability of each scenario node is calculated by using the dynamic Bayesian network joint probability formula. Under the comprehensive consideration about the probability statistics of actual accident cases, the critical scenario nodes on the evolution path and their final scenario probabilities are jointly determined to realize the optimization of the scenario evolution path. By constructing the correlation between the optimized scenario evolution path and the accident consequences, an accident consequence prediction model is established. The occurrence probability of accident consequences is calculated by the defuzzification method and dynamic Bayesian network. The accuracy of the consequence prediction model is verified by the July 16 Dalian's Xingang Harbor oil pipeline explosion accident. The research results provide scientific basis for helping decision makers to make the effective emergency measures that are most conducive to the rapid elimination of accidents and reducing the severity of accident consequences.     

生产事故引发环境事件应急演练的典型问题剖析

当前基层组织的突发环境事件应急演练重点不明确,多数裹挟着厚重的生产事故救援内容,甚至偏离了环境应急演练主题,这对真实突发环境事件应对是不利的。基于最坏情景演练思想,剖析生产事故与环境事件的演练重点,厘清生产事故引发环境事件的处置流程和演练模式,并借助化工企业甲醇泄漏事故引发环境事件的桌面推演实例,廓清复杂环境事件应急演练的构设方法与实施步骤。结果表明:生产事故引发环境事件应急演练策划设计中,生产事故应急部分可有效集成为向环境应急提供信息的通道,提供关键处置结果作为环境应急主题演练的响应信息即可;生产事故引发环境事件应急演练组织实施中,重点凸显环境应急决策和部署情况,可根据演练场景需要,重点设置应急监测、污染控制、事故调查等应急功能（组）,以考查或展示环境综合应急能力。     

基于危险的事故场景及其形式化描述

事故场景的鉴别是复杂装备系统安全风险分析的基础,其完备性直接影响风险评估的有效性,因为任何事故场景的遗漏即意味着设计上可能存在潜在的事故隐患。提出从鉴别系统危险出发。建立危险与其原因(关联引发事件)、事件与系统要素以及系统各要素之间的映射关系,通过对这些关系的运算来获取事故场景的新方法并给出其形式化表述,以期在理论上确保事故场景鉴别的完备性。     

基于生物免疫的化工园区事故发生机理研究

基于生物免疫系统抵御疾病(抗原)的原理,从事故致因、事故演化过程和事故发展规律出发,分析化工园区事故发生机理。结果表明,安全生产免疫系统的免疫力持续低于抗原系统的抗原强度是化工园区事故发生的根本原因;化工园区事故演化过程包括潜伏期、萌芽期、暴露期和恢复期,各个时期的形成是安全生产系统的免疫力和抗原系统的抗原强度之间的差异决定的;化工园区事故发生具有周期性,每个事故发展周期内都包含安全生产免疫系统→免疫力过低的免疫因子→事故触发免疫因子和安全生产抗原系统→抗原强度过大的抗原因子→事故触发抗原因子的变化过程。     

基于知识图谱的建筑工程施工事故智能分析

为预防和减少建筑工程施工事故,应用人工智能领域知识图谱技术,对建筑工程施工事故进行分析。通过定义领域知识图谱概念体系结构,从建筑工程施工事故数据中提取关键知识要素,构建建筑工程施工事故知识图谱,将其储存在Neo4j图数据库中,并提出基于知识图谱的建筑工程施工事故分析流程,针对事故相关信息开展查询、统计分析以及关联路径分析等智能分析。研究结果表明：基于知识图谱技术,将建筑工程施工事故知识以可视化图形或表格等进行展示,将事故信息以知识形式结构化存储及表达,可有效提高事故分析工作效率,为事故预防以及安全管理提供决策支持。     

一种主动功能约束视域下的复杂系统事故预防模型

复杂系统事故发生模式具有多样性、不确定性的特点。传统的被动式、以失效因果分析为导向的事故预防模型虽然能够较为有效地防止或者减少同类事故的发生,但无法预防未发生过的新事故,因此并不适用于事故模式多样的复杂系统的事故预防。为了更加系统、全面地降低复杂系统的事故风险,需从更加主动的、前瞻性的视角分析如何使系统保持正常的功能。根据控制系统中的功能约束原理,并以功能分解与共振分析模型(ACAT/FRAM)为建模工具,提出一种主动功能约束视域下的复杂系统事故预防模型。该模型通过将复杂系统进行功能分解与抽象,以闭环控制关系对功能进行耦合关联,得到复杂系统要素的正常功能约束结构。基于该模型的事故预防机制在于保证系统各要素以及要素间的正常功能,据此可制定面向多种事故模式的事故预防措施。     

Why bad things happen to good people

Accidents in the process industries are extensively investigated to determine root causes, for lessons learned, and many times in search of the “guilty”. Accidents are seldom simple and most accidents have human elements that led to or facilitated the accident. Many times the people involved in these accidents, when considered individually on their merit, would be considered “good” people yet “bad things” (accidents) still occur.Human errors can be classified as individual, group, and organizational. Individual human errors have been addressed in a number of studies and papers. Many of these classify human errors and treat them probabilistically or cognitively. Less has been said regarding the individual psychological/sociological response/interaction mechanisms that might contribute to an industrial accident. These elements also contribute to a lack of situational awareness which often plays a large part in human error. Group and organizational interactions/dynamics can also contribute negatively to situational awareness and to the chain of events of an accident. Organization errors, which are typically latent, can also facilitate an accident and are many times people enabled for personal and business vested interests.This paper will discuss the effect of human error at the practical plant level in contributing to accidents in the process industries from individual, group, and organizational perspective. The discussion will include psychological/sociological response/interaction mechanisms that can contribute to situational awareness and human error. It will also discuss how complexity, veracity, and quantity of available information can affect the human decision-making process leading to mistakes.Accidents are seldom simple and most accidents have a number of elements that led to or facilitated the accident. When looking at individual elements probabilistically, multiplying probabilities together, it is hard to see how an accident could have occurred. A common refrain “That’s double jeopardy and we don’t have to consider that” is essentially a qualitative probabilistic analysis. Yet we have cases of triple, quadruple, n-jeopardy occurring to cause accidents. The paper will discuss the superimposition of causes and a similar concept of functional resonance in causing accidents.     

突发性环境污染事故的应急监测探讨

突发性环境污染事故应急预案方案中主要包括污染物的应急监测以及污染事故的处置方案。其中应急监测的工作在于明确造成环境污染的化学物品的种类、浓度、数量、已造成污染范围、已造成的破坏程度、事故未来发展事态等。通过应急监测所整理的信息数据,应急预案组织工作小组可以迅速的对突发性环境污染事故做出科学合理的决策。本文针对突发性环境污染事故应急监测工作方案进行梳理总结,指导组织管理人员如何快速的组织应急监测工作。     

A case study analysis to examine motorcycle crashes in Bogota,Colombia

IntroductionContributory factors to motorcycle crashes vary among populations depending on several aspects such as the users' profiles, the composition and density of traffic, and the infrastructure features. A better understanding of local motorcycle crashes can be reached in those places where a comprehensive analysis is performed. This paper presents the results obtained from a case study analysis of 400 police records of accidents involving motorcycles in Bogota.MethodTo achieve a deeper level of understanding of how these accidents occur, we propose a systemic approach that uses available crash data. The methodology is inspired by accident prototypical scenarios, a tool for analysis developed in France.ResultsWhen grouping cases we identified three categories: solo motorcycle accidents, motorcyclist and pedestrian accidents, and accidents involving a motorcycle and another vehicle. Within these categories we undertook in-depth analyses of 32 groups of accidents obtaining valuable information to better comprehend motorcyclists' road crashes in a local context. Recurrent contributory factors in the groups of accidents include: inexperienced motorcyclists, wide urban roads that incite speeding and risky overtaking maneuvers, flowing urban roads that encourage high speed and increased interaction between vehicles, and lack of infrastructure maintenance.Practical ApplicationsThe results obtained are a valuable asset to define measures that will be conveniently adapted to the group of accident on which we want to act. The methodology exposed in this paper is applicable to the study of road crashes that involve all types of actors, not only the motorcyclists, and in contexts different than those presented in Bogota.     

A conceptual offshore oil and gas process accident model

The purpose of this paper is to present and discuss an accident prevention model for offshore oil and gas processing environments. The accidents that are considered in this work relate specifically to hydrocarbon release scenarios and any escalating events that follow. Using reported industry data, the elements to prevent an accident scenario are identified and placed within a conceptual model to depict the accident progression. The proposed accident model elements are represented as safety barriers designed to prevent the accident scenario from developing. The accident model is intended to be a tool for highlighting vulnerabilities of oil and gas processing operations and to provide guidance on how to minimize their hazards. These vulnerabilities are discussed by applying the 1988 Piper Alpha and the 2005 BP Texas City disaster scenarios to the model.     

Development of a new chemical process-industry accident database to assist in past accident analysis

Past accident analysis (PAA) is one of the most potent and oft-used exercises for gaining insights into the reasons why accidents occur in chemical process industry (CPI) and the damage they cause. PAA provides invaluable ‘wisdom of hindsight’ with which strategies to prevent accidents or cushion the impact of inevitable accidents can be developed.A number of databases maintain record of past accidents in CPI. The most comprehensive of the existing databases include Major Hazard Incident Data Service (MHIDAS), Major Accident Reporting System (MARS), and Failure and Accidents Technical Information Systems (FACTS). But each of these databases have some limitations. For example MHIDAS can be accessed only after paying a substantial fee. Moreover, as detailed in the paper, it is not infallible and has some inaccuracies. Other databases, besides having similar problems, are seldom confined to accidents in chemical process industries but also cover accidents from other domains such as nuclear power plants, construction industry, and natural disasters. This makes them difficult to use for PAA relating to CPI. Operational injuries not related to loss of containment, are also often included. Moreover, the detailing of events doesn’t follow a consistent pattern or classification; a good deal of relevant information is either missing or is misclassified.The present work is an attempt to develop a comprehensive open-source database to assist PAA. To this end, information on about 8000 accidents, available in different open-source clearing houses has been brought into a new database named by us PUPAD (Pondicherry University Process-industry Accident Database). Multiple and overlapping accident records have been carefully eliminated and a search engine has been developed for retrieval of the records on the basis of appropriate classification. PUPAD doesn’t aim to replace or substitute the well established databases such as MHIDAS and MARS but, rather, aims to compliment them.     

基于文本挖掘和复杂网络的事故致因重要度评估方法——以房屋市政较大以上事故为例

为充分挖掘事故调查报告中的有效信息,明确安全管理工作的内容.首先,利用文本挖掘分析事故调查报告,采用最小词频阈值文档频改进信息增益评估函数对分词结果降噪,通过回溯特征项在报告中的具体表述,提取事故致因,再构建同义词词库.然后,引入复杂网络以改进TF-IDF,综合事故致因因素的关联特征评估其重要度.最后,以房屋市政较大及...