基于演化博弈的危化品安全监管情景推演研究

针对危化品安全生产监管问题,基于演化博弈理论构建危化品安全监管演化博弈模型,并将危化品事故发生率引入模型,对比分析危化品企业与地方政府监管部门行为策略的演化稳定均衡。在此基础上进行情景推演模拟仿真,研究表明:危化品事故发生率,对危化品企业和地方政府监管部门的策略选择有显著影响,当危化品事故发生概率低于某一临界值时,危化品企业和监管部门都会疏忽安全投入和监管;地方政府承受危化品事故经济损失和信誉损失增大时,危化品安全监管系统演化呈现出周期性波动;引入上级政府惩罚机制情景下,当上级政府惩罚力度高于危化品企业未投入安全生产受到的处罚和地方政府安全监管成本时,其最终都选择安全投入和严格监管策略。研究结论为政府监管危化品安全生产提供新的思路和对策建议。     

危化品事故情景推演网络构建及关键节点分析*

为有效应对危化品事故发生与演变时存在的动态性及不确定性问题,基于事故演变过程中的关键情景状态及对应孕灾环境、应急活动和处置目标等要素,引入动态贝叶斯网络方法,构建危化品事故情景推演网络,并结合复杂网络知识,对孕灾环境和应急活动2类事故影响因素节点进行敏感性和重要度分析。结果表明:情景推演网络计算的情景节点概率符合事故发生的实际情况,能够对危化品事故在不同孕灾环境和应急救援下的演变路径进行推演,并且分析得到燃烧物、消防力量、火场环境和建筑密度等关键影响因素节点,研究结果可为事故处理提供应急辅助决策支持。     

Quantitative risk assessment model of hazardous chemicals leakage and application

The hazardous chemical accidents remain a matter of major concern. However, there is a dearth of practical measures about the emergency management of hazardous chemicals leakage. Therefore, in order to provide more accurate management plan, quantitative risk assessment has become a critical issue in chemical industry. The main aim of this study is to quantify the risk of hazardous chemicals leakage, and take precautions against the accidents. In this study, a Fire-Explosion-Poisoning Quantitative Probability Model (FEPQPM) has been established. The paper introduced the probability analysis methods to analyze derivative accidents caused by hazardous chemicals leakage, established quantitative risk assessment models, and made acceptable risk level analysis. This model has been applied to quantitatively assess an enterprise’s storage tank at Changshou Chemical Industrial Distripark (CID) in Chongqing, China. Evaluation results are in line with the actual situation of the CID. It is shown that the probability of poisoning is very large, causing more economic loss than the other two types of accidents, and death toll of leakage accident increases over time, resulting in greater economic losses. The risk level of leakage accident involving poisoning is unacceptable.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

A New Safety Risk Index for Use in Petrochemical Planning

Risk analysis is being used to evaluate and manage the potential of unwanted events in the chemical processing industry. The risk in this study is the risk posed by chemical plant accidents and it is presented in a simple quantitative form. A safety risk index is formulated that represents the maximum number of people that might be affected if an accident occurred that caused the release of all the plant inventory of a chemical. The index has four terms: frequency of accidents; hazardous effect of the chemical; inventory of the chemical released; size of the plant. The overall unit of the index is expressed as the number of people affected per year from the plant operation and is formed in a particularly simple manner so as to be suitable for the comparison of safety risk within a model for planning the development of the petrochemical industry.     

Improved models of failure time for atmospheric tanks under the coupling effect of multiple pool fires

Fire accidents of chemical installations may cause domino effects in atmospheric tank farms, where a large amount of hazardous substances are stored or processed. Pool fire is a major form of fire accidents, and the thermal radiation from pool fire is the primary hazard of domino accidents. The coupling of multiple pool fires is a realistic and important accident phenomenon that enhances the propagation of domino accidents. However, previous research has mostly focused on the escalation of domino accidents induced by a single pool fire. To overcome the drawback, in this study, the failure of a storage tank under the coupling effect of multiple pool fires was studied in view of spatial and temporal synergistic process. The historical accident statistics indicated that the accident scenario of two-pool fires accounted for 30.6% in pool fires. The domino accident scenario involving three tanks is analyzed, and the typical layout of tanks is isosceles right triangle based on Chinese standard “GB50341-2014”. The thermal response and damage of a target tank heated by pool fires were numerically investigated. The volume of 500 m³, 3000 m³, 5000 m³ and 10000 m³ were selected. Flame temperature was obtained by FDS, and then was input onto the finite element model. The temperature field and stress field of target tanks were simulated by ABAQUS. The results showed that the temperature rise rate of the target tanks under multiple pool fires was higher than that under a single pool fire. The failure time of the tank under the coupling effect of multiple fires was lower than that under the superposition of multiple fires without the first stage. The stress and yield strength were compared to judge the failure of the target tank. The model of failure time for the tank under the coupling effect of pool fires was established. Through the verification, the deviation of this model is 4.02%, which is better than the deviation of 15.76% with Cozzani's model.     

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.     

Risk analysis of deepwater drilling operations using Bayesian network

Deepwater drilling is one of the high-risk operations in the oil and gas sector due to large uncertainties and extreme operating conditions. In the last few decades Managed Pressure Drilling Operations (MPD) and Underbalanced Drilling (UBD) have become increasingly used as alternatives to conventional drilling operations such as Overbalanced Drilling (OVD) technology. These newer techniques provide several advantages however the blowout risk during these operations is still not fully understood. Blowout is regarded as one of the most catastrophic events in offshore drilling operations; therefore implementation and maintenance of safety measures is essential to maintain risk below the acceptance criteria. This study is aimed at applying the Bayesian Network (BN) to conduct a dynamic safety analysis of deepwater MPD and UBD operations. It investigates different risk factors associated with MPD and UBD technologies, which could lead to a blowout accident. Blowout accident scenarios are investigated and the BNs are developed for MPD and UBD technologies in order to predict the probability of blowout occurrence. The main objective of this paper is to understand MPD and UBD technologies, to identify hazardous events during MPD and UBD operations, to perform failure analysis (modelling) of blowout events and to evaluate plus compare risk. Importance factor analysis in drilling operations is performed to assess contribution of each root cause to the potential accident; the results show that UBD has a higher occurrence probability of kick and blowout compared to MPD technology. The Rotating Control Devices (RCD) failure in MPD technology and increase in flow-through annulus in UBD technology are the most critical situations for kick and blowout.     

Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

Among the various techniques used for safety analysis of process systems, bow-tie (BT) analysis is becoming a popular technique as it represents an accident scenario from causes to effects. However, the BT application in the dynamic safety analysis is limited due to the static nature of its components, i.e. fault tree and event tree. It is therefore difficult in BT to take accident precursors into account to update the probability of events and the consequent risk. Also, BT is unable to represent conditional dependency. Event dependency is common among primary events and safety barriers. The current paper illustrates how Bayesian network (BN) helps to overcome these limitations. It has also been shown that BN can be used in dynamic safety analysis of a wide range of accident scenarios due to its flexible structure. This paper also introduces the application of probability adapting in dynamic safety analysis rather than probability updating. A case study from the U.S. Chemical Safety Board has been used to illustrate the application of both BT and BN techniques, with a comparison of the results from each technique.     

Real-time risk assessment of explosion on offshore platform using Bayesian network and CFD

Combustion or explosion accident resulting from accidental hydrocarbon release poses a severe threat to the offshore platform's operational safety. Much attention has been paid to the risk of an accident occurring over a long period, while the real-time risk that escalates from a primary accident to a serious one was ignored. In this study, a real-time risk assessment model is presented for risk analysis of release accidents, which may escalate into a combustion or explosion. The proposed model takes advantage of Fault Tree-Event Tree (FT-ET) to describe the accident scenario, and Bayesian network (BN) to obtain the initial probability of each consequence and describe the dependencies among safety barriers. Besides, Computational Fluid Dynamics (CFD) is applied to handle the relationship between gas dispersion and time-dependent risk. Ignition probability model that considering potential ignition sources, gas cloud, and time series are also integrated into this framework to explain the likelihood of accident evolution. A case of release accidents on a production platform is used to test the availability and effectiveness of the proposed methodology, which can be adopted for facilities layout optimization and ignition sources control.     

模糊概率事件的故障树分析

许多职业事故的基本致因事件多属于模糊事件,其概率很难确定。本文以煤矿典型危害——内因火灾为例,探讨了模糊概率下的故障树分析问题。煤矿内因火灾故障树虽具有确定的结构形式,其基本致因事件的概率却无法统计。经过长期的生产实践,煤矿中一大批防火专家可以用自然语言较准确地描述基本事件发生的可能性,这就为故障树分析提供了有效信息。文中以模糊数学为基础,引入Delphi方法,征集并整理了25位专家对龙凤矿内因火灾致因的意见,确定了基本事件的模糊概率及其临界重要度排序,提出了行之有效的防治内因火灾措施。     

Risk analysis of LPG transport by road and rail

Historical data concerning more than 130 LPG rail and road transport accidents were critically examined, identifying the scenarios, following their evolution into the final accidental events, and determining their theoretical probabilities of occurrence. In principle, rail accidents are rather hazardous, the most probable scenario being a major release followed by an UVCE. However, in order to discriminate among road and rail transport, the relevant number of trips and accident rates should be taken into account. In fact, the application, concerning the transport of 5700 ton/year of LPG in Italy along one rail and two different road itineraries, showed that the risk for rail transport was more than one order of magnitude lower than that for those on the roads. The population density along the route and the accident rate, rather than the length of the route, appear the most important factors for discriminating between different itineraries.     

Application of CFD model in an LPG tank explosion accident

In this research, a 3D tank farm model of a petrochemical plant was built in order to analyze an LPG tank explosion accident. Furthermore, the Computational Fluid Dynamic (CFD) algorithm was also applied to reconstruct the scenario of the accident. With its 3D dynamic abilities, the CFD simulation results can be used to facilitate the understanding of the spatial and transient distribution of different hazardous physical variables, which cannot be observed from the traditional methods.After the maximum physical variables of overpressure, pressure-impulse, and thermal radiation temperature were calculated, the results were adopted to estimate the corresponding 3D individual risk value. With the aid of the CFD simulation and the analysis method of maximum physical variable, the researchers can use the simulation results to scrutinize the possible causes and consequences of a chemical accident.     

突发事故概率估算研究

以预防、降低和消除化工行业中密封容器爆炸事故为目标,从引发事故的成因分析入手,运用事故树分析,求其最小割集和最小径集。在此基础上,引入相对重要度,确定控制事故发生的关键因子,并讨论了管理因素对突发性事故概率的影响,为企业的安全管理提供了科学依据。     

危险化学品公路运输事故新特点及对策研究

统计分析了2008年1月～2010年5月我国发生的485起危险化学品公路运输事故。从事故发生的原因、事故涉及的化学品、事故造成的危害、事故发生的月份分布及年份变化等几个方面,分析了近年来危险化学品公路运输事故的新特点及变化规律。经统计分析,道路交通事故是引发危险化学品运输事故的主要原因之一;侧翻是危险化学品车辆最容易发生的道路交通事故;而随着我国高速公路的迅猛发展,追尾造成的危险化学品运输事故数量呈上升趋势;危险化学品公路运输过程中易燃液体事故起数最多,爆炸品和毒性物质事故造成的人员伤亡最严重;春节前后取代夏季,成为近两年危险化学品运输事故高发期。针对这些特点,对我国危险化学品公路运输安全管理与监控提出了建议。     

Promoting inherent safety

By inherent safety is meant that a hazard is eliminated rather than being managed by various add-on equipment and procedures. Practices of inherent safety have been developed in the chemical industry, and include for instance the substitution of hazardous substances by less hazardous ones. Inherently safer design strives to eliminate the possibility of major adverse events even when the probabilities of these events are small or cannot be meaningfully estimated. Considerations of security can be more easily incorporated into this approach than into most other branches of risk and safety analysis. Therefore, inherent safety has a great potential as a meeting-ground for the much-needed coordination of safety and security work. Its philosophical underpinnings are outlined, and proposals are made for more efficient promotion of its principles.     

危险化学品事故多米诺效应历史数据研究评述

系统整理分析近十五年来国内外利用历史数据进行危险化学品事故多米诺效应研究的相关文献,介绍该领域研究的主要数据来源、主要研究方法,对主要研究内容进行交叉比对,整理挖掘包括危险化学品多米诺事故场景下的易发物质、高发区域/过程、主要事故致因、高频事故序列、致死概率5项事故内在规律并对规律的运用进行初步探讨。提出在后续研究中可以从改进采样时间区间设计和进行细分事故场景研究作为该领域的完善方向。     

Advanced multi-perspective computer simulation as a tool for reliable consequence analysis

Major accidents involving hazardous materials are a crucial issue for the chemical and process industries. Many accidental events taken place in the past showed that dangerous substances may pose a severe threat for people and property. Aiming at loss prevention, a series of actions have been instituted through international regulations concerning hazardous installations safety preparedness. These actions involve efficient land-use planning, safety studies execution, as well as emergency response planning drawing up. A key factor for the substantial consideration of the above is the effective prediction of possible accident forms and their consequences, for the estimation of which, a number of empirical models have been developed so far. However, (semi-)empirical models present certain deficiencies and obey to certain assumptions, thus leading to results of reduced accuracy. Another approach that could be used for this purpose and it is discussed in this work, is the utilization of advanced computational fluid dynamics (CFD) techniques in certain accident forms modeling. In particular, composite CFD-based models were developed for the simulation of several characteristic accident forms involving isothermal and non-isothermal heavy gas dispersion, confined and unconfined explosion in environment of complex geometry, as well as flammable cloud fire. The simulation cases were referred to real-scale trials allowing us to conclude about the validity of the quantitative results. Comparisons of the computational predictions with the experimental observations showed that obtained results were in good agreement with the experimental ones, whereas the evaluation of statistical performance measures proved the simulations to be statistically valid.     

基于Apriori算法的易燃易爆危险化学品储运火灾爆炸事故关键致险因素的挖掘

导致易燃易爆危险化学品储运火灾爆炸事故的因素繁多、关系复杂,挖掘关键致险因素是减少管理成本、提高防控效率的关键。研究了200例事故等级为较大事故以上的易燃易爆危险化学品储运火灾爆炸事故的原因,采用事故树分析法建立易燃易爆危险化学品储运火灾爆炸事故树,并运用频度统计法遴选出致险因素;在此基础上,建立基于Apriori算法的关联规则模型进行数据挖掘,共得到14个关键致险因素。通过对关键致险因素与易燃易爆危险化学品储运火灾爆炸事故之间关联规则的分析表明,关键致险因素与事故之间存在强关联规则,单一关键致险因素或其组合的存在必将导致事故的发生,为实现危险化学品储运精准化安全管理提供参考。