工业设施易受攻击性评价方法研究

9.11事件以来,恐怖袭击的威胁引起各国政府、媒体和公众的广泛关注,恐怖袭击的风险研究成为安全科学的新课题.工业设施,特别是化学物质和能量聚集的工业设施,由于潜在的失控后果的严重性,遭恐怖袭击的威胁更大.本文基于恐怖袭击目标选择与工业设施某些固有特征的相关性,从攻击者的角度分析工业设施固有特征中影响其目标效用的诸因素,建立工业设施易受攻击性评价方法.     

基于机器学习的恐怖袭击事件后果预测方法研究

恐怖袭击事件通常会造成严重的人员伤亡、财产损失和社会影响,针对在不同场景下发生恐怖袭击所造成的后果进行预测是目前应对恐怖袭击事件急需解决的问题之一。利用多源数据,首先基于随机森林算法对恐怖袭击事件是否造成死伤进行分类预测,进而基于岭回归算法预测事件造成的具体死伤人数。研究结果表明:随机森林在测试集上对有死伤事件的召回率达到0.85,岭回归预测死亡和受伤人数的平均绝对误差分别小于1人和2人。研究结果可为反恐资源配置优化、预防恐怖袭击事件和减少其造成的损害提供辅助决策支持。     

基于博弈论的地铁车站恐怖袭击风险定量研究

近年来发生的几起地铁重大恐怖袭击事件引起了各国政府、媒体和公众的广泛关注.地铁车站恐怖袭击可以看作博弈双方即袭击者和防御者之间的零和博弈.本文以某地铁线路上的22个车站为例,应用目标损失概率模型定量分析了恐怖袭击风险,通过防御资源变化得到了不同的目标损失概率.研究结果可以为地铁车站防御资源优化配置、防恐反恐预案编制等提供量化依据.     

论城市公共安全的风险管理

从城市公共安全风险管理系统的研究出发,结合城市公共安全管理的特点,从城市工业危险源、公共场所、公共设施、公共卫生、自然灾害、生态环境、恐怖袭击等存在的风险,探讨其风险的特点;提出风险管理的步骤和原则;强调我国已进入风险社会和加强城市公共安全风险管理的重要性;指出了我国城市公共安全风险管理存在的问题,简单介绍了美国、日本、英国、俄罗斯等国家风险管理的经验;就我国城市公共安全风险管理现状,提出具体对策并构建了城市公共安全风险管理的基本框架。重点阐述了城市公共安全管理的内涵、现状、存在问题和应对措施并指出建立完善的城市公共安全管理体系是做好城市公共安全风险管理的有效办法。     

An approach to solve the facility layout problem based on the worst-case scenario

A new approach to determine the optimal distribution of process facilities is presented in this paper. The formulation considers a set of facilities already installed in a given land and a new set of facilities to be accommodated within the same land. In addition, it is considered that a set of facilities either installed or to be laid out presents the possibility of toxic release. Based on previous analysis, the worst-case scenario implies calm wind and stable atmospheric condition. Since these conditions tend to exist during several days of the year, the proposed model is formulated assuming these deterministic values for wind and atmospheric conditions. The final model is formulated as a disjunctive model that is converted into a mixed-integer non-linear program (MINLP) via the convex-hull method. The model is then solved with local and global optimizers in the GAMS package. Using the current approach based on minimum distances for a particular case study results in a distribution with a very high risk whereas the optimal results using this proposed approach indicate large separations between releasing facilities and the inhabited facilities due to the high toxicity of the released material. More elaboration will be aggregated into the developed model to include prevention and mitigation systems to produce more compact but optimal and safe layouts.     

A new approach for resource allocation for black spot treatment (case study: The road network of Iran)

Introduction: Currently, spatial and temporal distribution of safety resources in Iran is entirely based on expert opinions, regardless of network priorities. Considering the lack of resources for implementing safety treatments, prioritizing unsafe points is an important and complicated issue where the effectiveness of each safety treatment option should be thoroughly investigated. The political, social, and environmental aspects should also be taken into consideration, including social and political pressures and officials talks on less important topics. Obviously, this inappropriate resource allocation poses a serious challenge to the expected goals. In this study, a methodology based on economic and social issues is proposed to optimize the annual budget allocation for eliminating or reducing the risk of accident-prone points. In this methodology, the spatial and temporal distribution of budget is determined using a mathematical model aimed to maximize the benefits of reducing the accidents after deducting the costs of implementing the safety countermeasures. The outputs of this model include the safety countermeasure alternatives and a five-year time schedule for implementing them, or the alternative of no action with regard to budget, social, and judicial constraints. In order to evaluate the proposed method, it is applied to the road network of Iran and the results are compared with those of the conventional method that is currently used for resource allocation in this country. The results show that the proposed method leads to 15% higher benefits compared to the conventional method. Moreover, this method makes 641 safe points, which is about 17% more than the safe points resulted from the existing method. Therefore, the proposed method brings about a safer network as a result of the optimal allocation of available resources.     

以南疆为例的区域暴恐袭击风险评估

为探寻暴恐袭击高风险区域,推进公共安全精细化管理,以南疆地区为例,采用网格化社会经济数据、遥感数据和兴趣点(POI)数据等多源地理空间数据,从暴恐分子出现可能性、暴恐袭击目标选择偏好和暴恐袭击后果3个方面建立暴恐袭击风险评估指标体系,根据层次分析法(AHP)-Entropy、聚类分区等确定地理空间指标权重,最终得到南疆地区30″×30″(约1 km×1 km)细粒度的暴恐袭击风险的空间分布情况。结果表明:南疆地区的暴恐袭击高风险以上网格主要位于喀什、和田及阿克苏地区的部分市区和县城,与暴恐袭击历史事件的分布较一致,证明风险评估指标体系的合理性和可行性。     

Inverse calculation approaches for source determination in hazardous chemical releases

Source determination is vital in decision making and emergency planning involving hazardous chemical releases. This work was concentrated on inverse calculation approaches for source determination as well as current trends and future perspectives. In this paper, these different approaches are reviewed by dividing them into two categories: probability modeling methods and optimization modeling methods. The traits of these approaches are comparatively analyzed. Then it is shown how these approaches behave when applied to practical cases, and their feasibility, applicability, stability, and limitation in determining the location and strength are presented. It is argued that when experimenting with potential terrorist attacks involving hazardous chemical releases, observation points should be around the main line of the downwind direction when the source is known; while the uniform distribution of observation points is an efficient solution for unknown incidents. Probability modeling methods are demonstrated to be insufficient during emergency responses due to their lacking of enough prior information of unknown parameters, while optimization modeling methods are efficient and become a new trend in source determination. Findings reflect an urgent need for the development of high-accuracy detectors and further research of data transmission techniques in order to ensure the validity of these approaches.     

基于数据挖掘的施工危险识别注意投入与分配研究*

为分析施工情境中危险识别注意资源动态投入分配规律,基于动态时间规整算法,挖掘危险识别注视轨迹序列,以表征注意资源投入分配变化,并采用k-means聚类、注视熵、Needleman-Wunsch全局序列对齐算法和统计等方法,深入挖掘注意资源在危险目标中投入和分配等时空变化规律。研究结果表明:当事人危险识别各阶段注意资源呈现从显著目标到高危目标的投入变化趋势,危险识别注意资源分配随情境复杂因素呈现零散、均匀的空间特征,分配无序程度提高。     

Emergency resources demand prediction using case-based reasoning

The demand prediction on emergency resources is the premise and basis of optimal allocation of emergency resources. Nowadays, there are only few researches on this aspect in China and abroad. For this reason, the paper aims at the characteristics of emergency resource demand prediction and presents a method for emergency resource demand prediction using case-based reasoning (CBR), which is also a method based on risk analysis. This prediction method cannot only provide a basis for emergency resource reserve and allocation in future, but also provide a method and model support for the emergency resources allocation decision-making system to be constructed in future.     

Combating interference by unauthorised persons

Under the new threat situation it is necessary to impede and if necessary detect ingress by unauthorised persons into the relevant establishment. It may be necessary to take additional measures to protect installations or parts thereof that are especially hazardous or at risk from terrorist attacks from interference by unauthorised persons.

It is the duty of the state to take precautionary and preventive measures to impede or prevent external terrorist attacks or entry by force into establishments. The necessary resources for this purpose must be made available even in times of limited budgets.

Since total protection can never be guaranteed, external emergency measures have a particularly important role to play. The competent authorities in this sector must receive the necessary information from the operators and must take the measures within their sphere of responsibility without delay.

Much of the information necessary for assessment of the risk situation by the operators and the authorities is already available under the provisions on the safety report and the external alarm and emergency plans according to European Seveso II Directive (96/82/EC).

It is recommended that a restriction of disclosure of information on the grounds of public safety should only be permitted for establishments/installations which are to be regarded as security-relevant on the basis of the hazard and the risk analysis.

The outline of the systematic approach of a security analysis like it is proposed in Germany is described separately.     

Preparing for major terrorist attacks against chemical clusters: Intelligently planning protection measures w.r.t. domino effects

Chemical industrial areas or so-called chemical clusters consist of hundreds, and sometimes thousands, of chemical installations situated next to each other. Such areas can thus be seen as the summation of a large number of structures exhibiting danger to a certain degree for initiating or continuing accident domino effects or knock-on effects. In this article, an approach to investigate in a systemic way the vulnerability of each installation within the larger chemical cluster context, is developed. Our suggested method results in a prioritization of chemical installations with respect to their vulnerability for domino effects. The method can be used for intelligently designed protection of chemical industrial areas against terrorist attacks.     

City hazardous gas monitoring network

In our today's societies, many dangerous chemicals are produced and transported. Due to the vast use of chemicals, more chemical accidents are taking place with huge losses. In this study a city hazardous gas monitoring network was designed to detect the dispersion of toxic and combustible gases in the primary stages. The network could cover hazardous chemical facilities, important hazardous chemical routes, warehouses and special locations which may be the targets of terrorist attacks. The network is consisted of several local networks and a central control panel complex. Each local network has a local control panel in the center and many detectors and sounders around it at distances less than 3000 m that communicate with the local control panels wirelessly. In each location there are two types of gas detectors, toxic and combustible, and a sounder which are equipped with a wireless, radio frequency modem allowing the units to communicate readings and other information on a real-time basis with a remotely located local control panel. High sensitive Photo Ionization Detectors, PIDs, are used to provide fast and low-level on-site screening for chemicals contamination. Combustible gas detectors are the second choice to sense the combustible gas and verify the readings of PIDs in this regard. The central panel consists of several connected control panels work uniquely helping a computer set and the appropriate software and communicate with local control panels via telephone lines. All of the network components are shown on the monitor of central panel with special symbols by geographical information system program. The system is fully addressable so that the high level detection of a detector produces a blinking color double-circle around its symbol in GIS plan. In case of high level gas detection, a team of experts who are fully equipped with different portable detectors depart to the site to test the field to identify the chemicals. All readings of detectors are saved in a data bank and then analyzed to find any chemicals spills and leakages. The network was simulated by a special program so that the components of local networks and the central panel are shown in separate windows. By clicking on one detector on environmental window the formerly designed responses will be activated in central panel window.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

Methodology for Natech coupling risk assessment using correlative multi-criteria decision-making method

When a natural disaster occurs, it may damage multiple industrial facilities in a certain area at the same time, and the resulting Natech events may have an impact on the surrounding industrial facilities, generating coupling risk. In this study, the assessment of Natech events coupling risk is conducted using the method of correlated multi-criteria decision-making, and the knowledge of fuzzy measures is introduced to solve the uncertainty problem in Natech coupling risk. Natech Coupling Risk Index is constructed to involve physical and functional facilities. The concept of equivalent population is proposed to compare the risks generated by physical facilities and functional facilities. And economic indicators are added to calculate the comprehensive risk value. The purpose of this contribution is to enable local government managers to use their expertise and resources and the existing risk assessment of the plants themselves and rely on the scoring of experts limitedly to quickly and easily identify potential high Natech risk areas. In the calculation process of coupling risk, the government can also take the lead to promote information communication between different plants and other industrial subjects. The proposed method was applied in a realistic chemical industry area in Guangzhou, China and in a hypothetical town. The result shows that the physical risk may be transferred to the population and economy through the coupling between industrial facilities and the functional link between functional facilities and population and economy.     

大型公共场所多源疏散的控制流模型研究

以现有的单源最快流控制算法为基础,考虑人员在大型公共场所中的实际分布状况,遵循最大限度利用各出口的原则,提出针对多源疏散的全局最优化算法。根据此算法可以得出各疏散源点经过各出口的疏散人员数量以及人员的行走路径、从源点出发和完成疏散的时刻。将算法应用于某百货公司的案例研究表明,在多源疏散的情况下,各源点依次按照单源最快流控制算法进行独立疏散,能够保证每个源点的最优疏散,但整体的疏散效率并非最优;而应用全局最优化算法进行疏散,可以充分利用疏散过程中不同出口的疏散时间差,取得减少整体疏散时间、提高疏散效率的效果。     

大型游乐设施风险评估与分级方法研究

大型游乐设施的运行是一个动态管理过程,不仅涉及设备本身,而且与人、环境等因素密切相关。针对这个特点,提出大型游乐设施风险矩阵(RMM)的风险分级方法。提出了将事故树与模糊数学相结合的模糊事故树法(FFTA);采用3σ模糊表征法计算大型游乐设施各类风险事故的概率;再采用信息熵法来评价大型游乐设施的风险后果;最后利用风险矩阵法来确定大型游乐设施的风险等级,并通过实例验证了该分级模型有效。     

Frequency data and modification factors used in QRA studies

The source data for QRA’s is important to assure meaningful risk assessment results, particularly when the result is to be compared against quantitative risk acceptance criteria. The author’s company is one of the largest global QRA providers and we have concluded that the UK HSE Hydrocarbon Release Database (HCRD) provides the basis for the best leak frequency data as it offers complete leak data collection in a systematic manner, against a known population of equipment and facilities in the UK sector of the North Sea for which there is an accurate parts count estimate. The LEAK program is described. It screens HCRD to remove leak events not associated with full operations inventories and flows (e.g. when isolated for maintenance) and further uses a distribution function that permits frequencies for any arbitrary hole size range to be determined (e.g. 25 mm leaks, 50 mm leaks, full-bore ruptures). An important factor is that leak frequency data is not stationary, offshore operators have improved their control of leak events and the HCRD shows a declining leak rate over time.DNV often uses frequency modification techniques, termed MOR - Modification of Risk. This paper reviews 4 methods developed by the company internationally. These are the Manager Method, the API 581 method, a barrier based method, and a proprietary management system based method. These all permit localization of UK North Sea data to apply to other facilities (onshore or offshore) and with different management systems and mechanical integrity programs.Overall, localized data using MOR is considered more accurate than direct use of UK North Sea data, however validation is an issue. There are no direct comparisons that compare leak statistics over a sufficiently long period with static management systems and integrity programs. Thus MOR techniques remain judgment based approaches, but transparent in methodology and assumptions. The barrier based modification technique is the most directly verifiable of the four MOR methods presented.     

Risk management of terrorist attacks in the transport of hazardous materials using dynamic geoevents

This paper focuses attention on emergency management associated with a terrorist attack in the transport of hazardous materials in urban areas. The case study is in an urban area, a potential target for terrorist attacks due to its high vulnerability. Since it is not possible to predict where and when an attack will occur, the risk associated with terrorism is complex. It is only possible to identify the critical points for potential actions where counter measure must be applied. In the case of incidents which evolve relatively slowly, mitigation actions can be applied. The use of dynamic geoevents permits the immediate location of the event on a georeferenced map and the possibility of having a dynamic evolution of the scenario and of the number of people involved. The dynamic scenario has been created using the output of a consequence simulation code and a GIS software. Some assumptions were necessary but, since the aim of the paper is to define the procedure for the construction of the dynamic geoevent, these can be considered acceptable. The method will be further implemented in future.     

Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines.