Ageing management and monitoring of critical equipment at Seveso sites: An ontological approach

A safe “ageing” of Seveso establishments is a challenge for both operators and regulators. To this scope, Seveso III Directive required to integrate the equipment integrity issue into the safety management system for the major accident prevention; at the same time, the Italian Authority adopted a short-cut method for a quick ageing evaluation, which awards the application of the best techniques to control integrity and prevent deterioration-related failures. In this paper, the use of the ontology has been proposed to support decision-making about the implementation of technical solutions to control equipment ageing and comply the requirements of the Seveso legislation. To contrast deterioration mechanisms, the rapid development of data intensive smart sensors should be exploited and, in this frame, the automated on-line direct monitoring of equipment conditions, based on innovative low-cost sensors, is a novelty and promising solution. The developed ontology-based system points towards the adoption, when possible, of on-line monitoring. This solution provides much more data than traditional measurements and it is essential for the operators to understand how to merge concurrent information and data and to adequately control equipment deterioration. The ontology-based approach appears a viable solution even for this purpose. To demonstrate its potentiality, a real use-case has been used, where the model has been tested in finding the best technical solutions to improve the ageing management of an atmospheric distillation unit of a refinery in order to comply with safety requirements. A further use-case is given to show how the model can be used to react, after real-time damage signals, to restore safety conditions by means of an adequate decision-making.     

A framework addressing a safe ageing management in complex industrial sites: The Italian experience in «Seveso» establishments

In Europe, the Directive 2012/18/EU (Seveso III) strengthens the obligation to adopt a program assuring the integrity of critical equipment at major hazard establishments, by taking into account actual deterioration mechanisms (internal and external corrosion, erosion, thermal and mechanical fatigue, etc.). The program must cover all phases of the lifecycle and ensure a safe ageing of equipment, particularly when these are reaching the final stage of life. The effectiveness of the integrity program must be carefully assessed during the audits planned by the establishment's operator as well as by inspectors on behalf of the Competent Authorities. The adoption of a Risk Based Inspection scheme provides a valuable help to face this matter. The operator is, anyway, required a considerable effort to face at least three issues related to: (i) the understanding of concurring physical and chemical phenomena; (ii) the management of information associated with each individual component and its history, (iii) the appropriate measurement, including acquisition and management of data. There is a considerable difficulty in understanding these issues during Seveso inspections and external audits, because time and resources are often limited. For this reason, models and methods supporting the definition of the ageing status and trend in industrial sites are needed. This paper analyses the main factors affecting ageing. A framework for “ageing” assessment in complex industrial sites, including “Seveso” establishments, is proposed; then, its validation, by means of data collected during a testing phase carried out in Italy, is also given.     

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...     

Risk assessment of safety level in university laboratories using questionnaire and Bayesian network

Accidents in university laboratories not only create a great threat to students’ safety but bring significant negative social impact. This paper investigates the university laboratory safety in China using questionnaire and Bayesian network (BN) analysis. Sixteen influencing factors for building the Bayesian net were firstly identified. A questionnaire was distributed to graduate students at 60 universities in China to acquire the probability of safe/unsafe conditions for sixteen influencing factors, based on which the conditional probability of four key factors (human, equipment and material, environment, and management) was calculated using the fuzzy triangular theory and expert judgment. The determined conditional probability was used to develop a Bayesian network model for the risk analysis of university laboratory safety and identification of the main reasons behind the accidents. Questionnaire results showed that management problems are prominent due to insufficient safety education training and weak management level of management personnel. The calculated unsafe state probability was found to be 65.2%. In the BN analysis, the human factor was found to play the most important role, followed by equipment and material factor. Sensitive and inferential analysis showed that the most sensitive factors are personnel incorrect operation, illegal operation, and experiment equipment failure. Based on the analysis, countermeasures were proposed to improve the safe management and operation of university laboratories.     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

基于贝叶斯网络模型的船舶搁浅事故分析

根据海上交通安全事故统计数据显示,船舶搁浅事故是主要的海上交通安全事故之一。为了研究船舶搁浅事故的发生机理,收集了我国东部海域部分海事局辖区的船舶搁浅事故样本。首先从人为因素、环境因素和船舶因素三方面分析导致船舶搁浅事故的原因,确定网络节点。然后找出每起搁浅事故的事故链,并建立船舶搁浅事故贝叶斯网络模型。再对建立的贝叶斯网络模型进行仿真,选取21起船舶搁浅事故对建立的模型进行验证,确定模型的有效性。最后,利用HUGIN软件找出船舶搁浅事故各影响因素的致因概率,得到导致船舶搁浅事故的致因链。在人为因素方面,瞭望不当和不熟悉航道情况占据的比例最高;在船舶因素方面,舵机设备故障对船舶搁浅事故影响最大;在环境因素方面,风/浪/流对船舶搁浅事故影响最大。     

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.     

基于贝叶斯网络的养老院火灾风险评估方法研究

为预防养老院火灾事故,结合事故树法(FTA)和贝叶斯网络法(BN),建立了一套养老院火灾风险定量评估模型。首先,采用事故树法建立潜在的养老院火灾事故场景;其次,考虑到养老院火灾事故场景中不确定因素的影响,将事故树模型转化为贝叶斯网络模型,并结合有人员伤亡的养老院火灾事故发生发展实际优化模型;最后,以某市养老院为例,结合调研、文献及统计数据确定先验概率及条件概率,并用GENIE 2.0软件实现贝叶斯图形化,分析验证该模型逻辑可行性。结果表明:通过该模型和方法,不仅可以预测养老院火灾事故中各场景发生发展概率,还能对各风险因素敏感度和最大致因链进行分析,提高了风险因素辨识和评价的准确性,可以为养老院火灾风险分析和防控提供参考。     

基于三角模糊数的机械伤害事故风险分析

为研究机械伤害事故风险因素的影响程度,更好地对机械系统进行安全管理,实现机械设备安全运行和生产,以某企业清理沥青修整机作业时发生的机械伤害事故为例对其进行风险评估,根据机械伤害事故的特点并结合《机械工厂安全性评价标准》构建了机械伤害风险评价指标体系,采用三角模糊数和网络分析法计算导致事故的各个因素和子因素的权重。结果表明,危险操作倾向、机器安全防护、身心状态是导致事故发生的直接因素,并据此提出了相应的风险预防措施,为机械伤害事故风险决策提供了有力依据。     

Analysis of factors that influence hazardous material transportation accidents based on Bayesian networks: A case study in China

In this study, we applied Bayesian networks to prioritize the factors that influence hazardous material (Hazmat) transportation accidents. The Bayesian network structure was built based on expert knowledge using Dempster-Shafer evidence theory, and the structure was modified based on a test for conditional independence. We collected and analyzed 94 cases of Chinese Hazmat transportation accidents to compute the posterior probability of each factor using the expectation-maximization learning algorithm. We found that the three most influential factors in Hazmat transportation accidents were human factors, the transport vehicle and facilities, and packing and loading of the Hazmat. These findings provide an empirically supported theoretical basis for Hazmat transportation corporations to take corrective and preventative measures to reduce the risk of accidents.     

基于贝叶斯网络的煤矿事故人因推理

煤矿事故的不可重现性决定了事故原因的调查具有很强的不确定性,如何通过事故发生后的相关信息提高事故深层次原因调查的准确性是非常重要的。将HFACS与贝叶斯网络相结合,以煤矿事故HFACS分析结果为样本,通过卡方检验和让步比分析建立人因的贝叶斯网络因果图,进一步利用最大似然估计算法确定了煤矿事故人因的贝叶斯网络参数。最后,以双柳煤业顶板事故的调查信息为证据推理导致煤矿事故发生的深层次原因,提高事故原因调查的准确性,从而验证模型的有效性。     

公路施工安全事故的影响因素重要度评价实证研究

针对公路施工过程中施工事故频发、监管重点难以把握的现状,建立公路施工安全事故影响因素重要度评价模型。选取2002—2007年发生的43起公路施工安全事故为样本数据,基于对公路施工安全事故的分析,认为公路施工安全事故的发生,受到施工人员、施工器材、环境风险和管理4个方面的共同影响,通过拆分、合并、剔除3个过程筛选出11种引发公路施工安全事故的影响因素;应用灰色关联度分析,进行影响因素的重要度评价,结果将11个影响因素划分为4个重要度水平。根据公路施工安全事故影响因素的重要度评价结果,制定预控措施以使公路施工事故的灾害损失减少到最低。     

基于贝叶斯网络的化工园区地震次生灾害情景分析

为了研究化工园区内发生地震灾害后的事故演化过程,利用事故链模型对地震次生灾害演化过程进行分析,并将其转化为贝叶斯网络,确定各节点的变量与状态取值范围;通过相关文献及专家经验判断分析,获得贝叶斯网络中各节点的条件概率;依据贝叶斯网络的推理策略,比较不同地震烈度下,各化工事故发生的后验概率值,并探讨应急救援的及时性对地震次生灾害发生概率的影响,从关键要素遏制化工事故的发生,采取针对性的应对措施,尽可能的降低化工事故,有效的降低人员伤亡及财产损失。     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为（Unsafe Human Behaviors,UHBs）对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析。构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,将不同等级高后果区划分为不同等级人口敏感区;利用专家经验评判法得到不同等级人口敏感区基本事件的先验概率和中间事件的条件概率表;运用贝叶斯网络双向推理算法求解模糊Bow-tie模型。结果表明:随着地区人口敏感等级的提高,输气管道泄漏燃爆事故发生的概率随之增大,发现导致输气管道失效泄漏事故发生的最主要原因为施工破坏,失效原因与EGIG分析的结果基本相符,验证该方法在高后果区输气管道泄漏燃爆事故分析上的可行性,可为输气管道高后果区的安全管理提供决策依据。     

基于贝叶斯网络的页岩气集输管道失效概率计算方法研究

页岩气集输管道运行压力和出砂量在生产过程中衰减显著，这导致管道失效概率不断变化，针对这一问题，采用贝叶斯网络方法，建立了页岩气集输管道失效概率动态计算模型。首先，分析页岩气气质特征、管道运行工况及失效原因，利用逻辑门的连接关系，建立了页岩气集输管道失效故障树；其次，基于贝叶斯网络与失效故障树的结构映射关系，将失效故障树转化成贝叶斯网络结构；然后，通过贝叶斯网络的参数学习，实现模型求解；最后，进行了实例应用。研究结果表明:该模型不仅可有效计算页岩气集输管道的失效概率，还能确定影响管道失效的关键风险因素，并且可通过调整节点的状态及概率分布，实现页岩气集输管道失效概率的更新。     

Study of Major Accidents Involving Chemical Reactive Substances: Analysis and Lessons Learned

The objective of this paper is to present the results of the analysis performed on a selection of accidents included in the MARS database. This is a database of past accidents that occurred in Europe maintained by the European Commission, in order to help the Member States to meet the requirements of the Seveso and Seveso II directives. The study is focused on those accidents that involve reactions between chemical substances, whether wanted or unwanted, that generated a hazardous situation by loss of control of such reactions. Runaway reactions are known to be especially dangerous, given that many times they are unexpected, or their possible consequences underestimated, so sometimes chemical industries are not ready to cope with the effects of loss of control of reactive processes. The aim of the analysis is to obtain lessons learned from past accidents in order to prevent similar situations in the future, or to reduce their consequences. Understanding the causes of past accidents, including equipment failures, deviations in the expected course of a reaction, or deficiencies in process operations performed, can help to a better understanding of similar processes. Industries working with potentially dangerous chemicals should consider introducing lessons learned into their safety management systems.     

基于模糊层次分析法的矿井安全综合评价

为定量地综合评价煤矿安全状况,结合目前煤矿灾害事故的特点,根据影响煤矿安全的因素,建立了包括环境、技术、人员、管理等4个单元、17项指标的多因素多级指标评价体系。采用模糊层次分析法(FAHP)和模糊综合评价模型相结合的方法对煤矿安全进行综合评价。首先是通过模糊层次分析法确定了各评价指标的权重,其结果显示:安全管理是影响煤矿安全的首要因素,其次是人员素质、技术与装备保障,而矿井自然安全条件排序为最后。理论联系实际,应用模糊综合评价方法对某矿的安全现状进行综合分析,得出其安全状况为"良好",同时也证明将模糊层次分析法应用于安全评价的可行性。     

贝叶斯网络在CFIT风险评价中的应用

针对事故树分析法(FTA)在风险评价中的局限性,在可控飞行撞地(CFIT)事故树的基础上,建立贝叶斯网络(BN).运用推理运算对贝叶斯网络进行定量分析,通过分析计算数据,寻找主要事故致因,并提出对应的改进措施.再将改进措施引入到贝叶斯网络中,评价相关措施的有效性.结果表明,改进措施后,高度设置错误的后验概率最大,将成为预防CFIT的工作重点.最后指出贝叶斯网络方法是对传统的基于故障树分析的风险评价方法的有益改进.     

煤矿安全管理能力理论框架研究

运用文献分析和综合归纳等研究方法,对煤矿安全管理能力进行研究。通过研究得出:煤矿安全管理能力本质是一种累积专有知识的集合,是煤矿对由安全生产体系进行协调控制的过程中,诸要素相互作用形成的蕴含在煤矿内部的一种企业管理能力。具备知识属性的"人、设备、环境、制度"成为煤矿安全管理能力的构成要素,而"人的不安全行为"、"设备不安全状态"、"环境不安全条件"和"制度不安全条件"对构成要素产生不良影响,成为煤矿安全管理能力的影响因素。煤矿安全管理能力的构成要素与影响因素之间存在一种此消彼长的互动关系——构成要素越强则影响因素越弱,导致煤矿安全事故发生概率越低;构成要素越弱则影响因素越强,导致煤矿安全事故发生概率越高。     

水平定向钻穿越施工的失效可能性研究

水平定向钻穿越施工是管道穿越工程的一种主要施工形式,在施工中由于地质条件、设备使用和穿越工艺选择等原因使其存在风险,因此有必要对其失效可能性进行研究。建立了包含“人、机、料、法、环”五方面的水平定向钻施工失效可能性指标评价体系,对于特征影响因素,如扩径比、管土摩擦系数等,运用回拖过程的力学分析得出其分布规律,用模糊化的方法将底层指标分值转化为先验概率,再代入贝叶斯网络进行概率推理,最终确定其失效可能性。以某管道工程采取水平定向钻穿越河流为例,得出其失效可能性等级为“较高”,最后提出了相应的控制措施。运用贝叶斯网络研究水平定向钻穿越施工的失效可能性具有重要的工程应用价值和现实意义。