Operational risk assessment: A case of the Bhopal disaster

Accidental releases of hazardous chemicals from process facilities can cause catastrophic consequences. The Bhopal disaster resulting from a combination of inherently unsafe designs and poorly managed operations is a well-known case. Effective risk modeling approaches that provide early warnings are helpful to prevent and control such rare but catastrophic events. Probability estimation of these events is a constant challenge due to the scarcity of directly relevant data. Therefore, precursor-based methods that adopt the Bayesian theorem to update prior judgments on event probabilities using empirical data have been proposed. The updated probabilities are then integrated with consequences of varying severity to produce the risk profile.This paper proposes an operational risk assessment framework, in which a precursor-based Bayesian network approach is used for probability estimation, and loss functions are applied for consequence assessment. The estimated risk profile can be updated continuously given real-time operational data. As process facilities operate, this method integrates a failure-updating mechanism with potential consequences to generate a real-time operational risk profile. The real time risk profile is valuable in activating accident prevention and control strategies. The approach is applied to the Bhopal accident to demonstrate its applicability and effectiveness.     

Risk assessment of rare events

Rare events often result in large impacts and are hard to predict. Risk analysis of such events is a challenging task because there are few directly relevant data to form a basis for probabilistic risk assessment. Due to the scarcity of data, the probability estimation of a rare event often uses precursor data. Precursor-based methods have been widely used in probability estimation of rare events. However, few attempts have been made to estimate consequences of rare events using their precursors. This paper proposes a holistic precursor-based risk assessment framework for rare events. The Hierarchical Bayesian Approach (HBA) using hyper-priors to represent prior parameters is applied to probability estimation in the proposed framework. Accident precursor data are utilized from an information theory perspective to seek the most informative precursor upon which the consequence of a rare event is estimated. Combining the estimated probability and consequence gives a reasonable assessment of risk. The assessed risk is updated as new information becomes available to produce a dynamic risk profile. The applicability of the methodology is tested through a case study of an offshore blowout accident. The proposed framework provides a rational way to develop the dynamic risk profile of a rare event for its prevention and control.     

A new approach for facility siting using mapping risks on a plant grid area and optimization

The present work is focused on developing a methodology to find the optimal placement of a hazardous process unit and other facilities using optimization theory while considering a risk map in the plant area. Incidents can have possible consequences resulting from flammable gas releases, which can be evaluated by using consequence modeling programs. The probability of each incident can be derived from initial leak hole size estimation through event tree analysis. In this methodology the plant area was divided into square grids and risk scores were estimated for each grid. The overall cost is a function of the probable cost of property damage due to fires or explosions and the interconnection cost including piping, cable, and management. The proposed approach uses a mixed integer linear optimization programming (MILP) that identifies attractive locations by minimizing the overall cost. A case study is presented for a hexane–heptane separation facility that considers the meteorological data for the given area in order to show the applicability of the proposed methodology. Results from this study will be useful in assisting the selection of locations for facilities and for risk management.     

基于贝叶斯网络的危化品爆炸事故电力系统风险评估模型*

为提高危化品爆炸事故电力应急预警的准确性,建立基于贝叶斯网络的危化品爆炸事故电力系统风险评估模型。基于危化品爆炸事故电力应急典型情景分析,建立综合考虑突发事件、承灾载体和应急管理等风险因素的贝叶斯网络结构。应用概率刻画风险因素信息的不确定性及其相互影响,定量分析事件后果。结合一般条件和典型情景等的应用实例,分析评价方法和风险因素对风险等级的影响。结果表明:该模型能够在危化品爆炸事故发生后,评价电力应急预警等级;能够在危化品爆炸事故发生前,分析典型情景的风险和风险因素的影响,为应急准备提供支持;“最大概率法”较“概率加权求和法”得出的事件等级可能较低。     

Risk-based route evaluation against country-specific criteria of risk tolerability for hazmat transportation through Indian State Highways

Risk-based route evaluation is necessary for decision making by authorities for regulating hazardous materials (hazmats) transport vehicles. The paper highlights risk estimation and its representation for three highway study routes in western India using frequency analysis through logic diagrams and scenario based detailed consequence analysis of accidental releases considering 26 hazmats from UN Classes-2, 3, 6 and 8 categories. The 3 routes have been evaluated based on several layers of analysis namely hazmat-wise, route-segment-wise, route-wise and overall assessment including presentation of normalized risk figures. The results show that compared to the risk on city route segment, individual risks on other two routes are higher and extend beyond ALARP (As Low As Reasonably Practicable) region when assessed against HSE, UK risk criteria, whereas, societal risks on all three routes are within the ALARP except some part in the higher fatality area. But, considering the general mortality rates in India and sustained economic growth, the authors proposed widening of the ALARP region for individual risk tolerability of transportation activity of essential commodities that benefits society to a large extent in this developing economy. However, specific risk reduction measures have also been suggested to improve upon the risk picture in the study area.     

A new simple methodology for evaluation of explosion risk in underground coal mines

The key objective of this paper is the presentation of a new risk assessment tool for underground coal mines based on a simplified semi-quantitative estimation and assessment method.In order to determine the risk of explosion of any work process or activity in underground coal mines it is necessary to assess the risk. The proposed method is based on a Risk Index obtained as a product of three factors: frequency of each individual scenario P_ucm, associated severity consequences C_ucm and exposure time to explosive atmospheres E_ucm. The influence of exposure time is usually not taken into account up to now. Moreover, the exposure to explosive atmospheres may affect factors of hazardous event probability as much as its consequences. There are many definitions of exposure to explosive atmospheres but in the case of underground coal mines the exposure is defined as frequency risk of firedamp and coal dust. The risk estimation and risk assessment are based on the developed of a risk matrix.The proposed methodology allows not only the estimation of the explosion risk but also gives an approach to decide if the proposal investment is well-justified or not in order to improve safety.     

A new look at release event frequencies

Within the context of a quantitative risk analysis (QRA), the two main constituents used to describe petrochemical risks are, and have always been, consequence and probability. The consequences of hazardous material accidents are easy to apprehend – if a hazard is realized it can injure people or cause fatalities, damage equipment or other assets, or cause environmental damage. Frequencies for these consequences, on the other hand, are not as easy to understand. Process safety professionals develop event frequencies by evaluating historical data and calculating incident rates, which represent, in the QRA context, how often a release of a hazardous material has occurred. Incident rates are further modified by probabilities for various hole sizes, release orientations, weather conditions, ignition timing, and other factors, to arrive at unique event probabilities that are applied in the QRA. This paper describes the development of incident rates from historical database information for various equipment types, as well as defining a methodology for assigning hole size probabilities from the same data, such that a hole size distribution can be assigned within each QRA study. The combination of total incident rates and a hole size distribution relationship can then serve as a foundation within the frequency side of many QRA studies.     

Rare event risk analysis – application to iceberg collision

To design an engineering system, testing in extreme conditions is at least recommended if not required. There are ambiguities about how to define an extreme state and how to consider it in the design of a system or its operation. The probability estimation of such an event is challenging due to data scarcity, especially in many engineering domains, e.g. offshore development. In this study, available techniques for analyzing the probability of extreme events are examined for their suitability in engineering applications, and a framework is proposed for rare event risk analysis. The framework is comprised of three phases. In the first phase, the outlier based extreme value theory is implemented to estimate the rare event probability. The maximum likelihood criterion is used to estimate the extreme distribution parameters. In the second phase, the rare event is considered as a heavy tail event, and the tail index is estimated through the Hill and the SmooHill estimator. In the third phase, The uncertainty analysis is conducted, and the risk is computed. The proposed methodology is tested for extreme iceberg risk assessment on large offshore structures in the Flemish Pass basin. For this specific case, the estimated design extreme iceberg speed was 4.31 km/h, with an occurrence probability of 3.61E-06.     

Experimental analysis of 31 risk estimation tools applied to safety of machinery

This article studies differences in the results of using different risk estimation tools in the same hazardous situations involving dangerous machinery. We investigated how (a) types of risk estimation parameters and methods of constructing tools, (b) the number of levels of each parameter, and (c) the number of risk levels influence the results. Consequently, 31 risk estimation tools were compared by using them to estimate risk levels associated with 20 hazardous situations. Risk estimation appears to be tool-dependent, as different tools give different results with identical hazardous situations. The scope of the tool, its use, and construction could explain these differences. This article also proposes a series of rules for constructing tools to alleviate many problems associated with the variability of risk estimations.     

FMEA在乙烯罐区风险分析中的应用研究

详细介绍国际上先进的风险管理方法故障类型和影响分析(FMEA)的评价理论和分析方法。为了能够在系统使用阶段进行故障类型和影响分析(FMEA),并缩减其工作量,对故障源分析过程进行改进,并对乙烯罐区进行FMEA风险评价。对乙烯罐区安全操作中的各种不期望发生事件,潜在的故障类型、故障因素、后果严重度、发生概率及风险等级进行逐个分析,并根据评价结果制定相应的风险削减措施。研究表明,FMEA不仅能保证系统运行过程的可靠性,而且通过研究导致不期望发生事件(事故)的故障源(故障类型),从源头消除故障隐患。     

Route evaluation for hazmat transportation based on total risk - A case of Indian State Highways

Risk-based hazmat transportation route evaluation involves risk calculations taking into consideration the probability of collision related accident occurrence and detailed consequence analysis of various event scenarios. Probabilistic hazmat transportation risk assessment mainly depends on three important factors i.e. accident rate, Average Daily Traffic and population density besides route length which has a definite bearing on it. An effort has been made to estimate the route segment specific (location-specific) accident rate instead of aggregate National or State average values in order to bring specificity into the issue of decision making to avoid routes with higher accident rates. Instead of using default accident rate for different highway types developed with the US data, which are not well-comparable when used in Indian situations; the author used site-specific truck accident data. Subsequently, Loss of Containment (LOC) probabilities and spillage probabilities for different route segments have been computed and compared. Finally, route segment-wise total risk is estimated which is a convenient measure of the average number of persons likely to be exposed from all the possible consequence event scenarios resulting from releases of different hazmats being transported along the studied routes. The present study highlights the route evaluation carried out based on total risk computation, without going through detailed event based consequence analysis on two State Highway routes and one major urban road passing through important industrial corridors of Surat District in western India, to enable routing decisions by local authorities and also for planning emergency mitigation purposes.     

基于粗糙集理论的危险货物运输风险分析

为解决不确定环境中危险货物运输风险分析问题,针对风险数值分析等方法无法识别构成风险的主要因素和次要因素,无法获得因素重要度,以及不能揭示风险因素与风险之间的因果关系等问题,提出基于粗糙集理论的危险货物运输风险分析方法。首先将原始样本进行属性约简和规则约简,获得各个属性的重要度,识别影响危险货物运输安全的主要因素和次要因素;然后,通过对原始样本进行实例推理,推导出危险货物运输事故规律;最后通过算例验证模型和算法的有效性。结果表明,道路的平纵曲线半径是影响危险货物运输安全的最重要因素,其次是驾驶员因素和运输车辆因素。     

What you don’t manage will leak: A tribute to Trevor Kletz

This paper expands on a simple concept shared with us over three decades ago by Trevor Kletz: what you don’t have can’t leak. Despite many efforts at eliminating hazards through inherently safer process methodologies, as encouraged by Kletz and others, the reality is that the use of hazardous materials and processes is still quite common. Therefore, we consider those processes that still handle hazardous materials – the cases where what you do not manage will leak and may cause a fire, explosion or toxic release. Our intended audience is quite broad. As Kletz has noted over the years, it is not just the people running a process who are responsible for its safety, but also those who make decisions on its design, operation, maintenance, staffing, etc. We hope that this paper contributes to an understanding of why we continue to have hazardous materials leak, potentially leading to accidents that cause fatalities, serious injuries, property damage, and environmental harm.We expand on the fundamental equation for risk, a function of both the frequency and the consequence of a possible event, by considering the effects of poor operational discipline on risk, and ultimately, on the possible leak or release of the hazardous material. Continued safe operation involving hazardous materials depends on and is sustained by the operational discipline of everyone involved in the design of processes and their continuing operation and maintenance. What we do not manage will leak and therein lays the fundamental challenge that Kletz continues to emphasize today.     

A fuzzy model for assessing risk of occupational safety in the processing industry

Managing occupational safety in any kind of industry, especially in processing, is very important and complex. This paper develops a new method for occupational risk assessment in the presence of uncertainties. Uncertain values of hazardous factors and consequence frequencies are described with linguistic expressions defined by a safety management team. They are modeled with fuzzy sets. Consequence severities depend on current hazardous factors, and their values are calculated with the proposed procedure. The proposed model is tested with real-life data from fruit processing firms in Central Serbia.     

A Fuzzy Model for Assessing Risk of Occupational Safety in the Processing Industry

Abstract

Managing occupational safety in any kind of industry, especially in processing, is very important and complex. This paper develops a new method for occupational risk assessment in the presence of uncertainties. Uncertain values of hazardous factors and consequence frequencies are described with linguistic expressions defined by a safety management team. They are modeled with fuzzy sets. Consequence severities depend on current hazardous factors, and their values are calculated with the proposed procedure. The proposed model is tested with real-life data from fruit processing firms in Central Serbia.     

Development of machine learning based prediction models for hazardous properties of chemical mixtures

Lower flammability limit (LFL), upper flammability limit (UFL), auto-ignition temperature (AIT) and flash point (FP) are crucial hazardous properties for fire and explosion hazards assessment and consequence analysis. In this study, a comprehensive prediction model set was constructed by using expanded chemical mixture databases of chemical mixture hazardous properties. Machine learning based gradient boosting quantitative structure-property relationship (GB-QSPR) method is implemented for the first time to improve the model performance and prediction accuracy. The result shows that all developed models have significantly higher accuracy than other regular QSPR models, with the 5-fold cross-validation RMSE of LFL, UFL, AIT, and FP models being 1.06, 1.14, 1.08, and 1.17, respectively. All developed QSPR models can be used to estimate reliable chemical mixture hazardous properties and provide useful guidance in chemical mixture hazard assessment and consequence analysis.     

RAPID-N: Rapid natech risk assessment and mapping framework

Natech accidents at industrial plants are an emerging risk with possibly serious consequences. For the mitigation of natech risk, authorities need to identify natech prone areas in a systematic manner. In order to facilitate probabilistic natech risk mapping, a unified methodology was developed that is based on the estimation of on-site natural hazard parameters, determination of damage probabilities of plant units, and assessment of probability and severity of possibly triggered natech events. The methodology was implemented as an on-line, extensible risk assessment and mapping software framework called RAPID-N, which allows rapid local and regional natech risk assessment and mapping with minimal data input. RAPID-N features an innovative data estimation framework to complete missing input data, such as on-site natural hazard parameters and plant unit characteristics. The framework is also used for damage assessment and natech consequence analysis, and allows easy modification of input parameters, dynamic generation of consequence models according to data availability, and extension of models by adding new equations or substituting existing ones with alternatives. Results are presented as summary reports and interactive risk maps, which can be used for land-use and emergency planning purposes by using scenario hazards, or for rapid natech consequence assessment following actual disasters. As proof of concept, the framework provides a custom implementation of the U.S. EPA's RMP Guidance for Offsite Consequence Analysis methodology to perform natech consequence analysis and includes comprehensive data for earthquakes. It is readily extendible to other natural hazards and more comprehensive risk assessment methods.     

Modelling of BP Texas City refinery accident using dynamic risk assessment approach

Process industries involve handling of hazardous substances which on release may potentially cause catastrophic consequences in terms of assets lost, human fatalities or injuries and loss of public confidence of the company. In spite of using endless end-of-the-pipe safety systems, tragic accidents such as BP Texas City refinery still occur. One of the main reasons of such rare but catastrophic events is lack of effective monitoring and modelling approaches that provide early warnings and help to prevent such event. To develop a predictive model one has to rely on past occurrence data, as such events are rare, enough data are usually not available to better understand and model such behavior. In such situations, it is advisable to use near misses and incident data to predict system performance and estimate accident likelihood. This paper is an attempt to demonstrate testing and validation of one such approach, dynamic risk assessment, using data from the BP Texas City refinery incident.Dynamic risk assessment is a novel approach which integrates Bayesian failure updating mechanism with the consequence assessment. The implementation of this methodology to the BP Texas City incident proves that the approach has the ability to learn from near misses, incident, past accidents and predict event occurrence likelihood in the next time interval.     

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。     

Shelter-in-place risk assessment for high-pressure natural gas wells with hydrogen sulphide and its application in emergency management

This paper provides a risk assessment method of sheltering in-place for high-pressure natural gas wells with hydrogen sulphide. In this paper, the shelter-in-place risk is estimated by integrating the health consequences of an individual taking one kind of emergency response to the emergency orders of sheltering in place from the emergency decision makers and the probability of the corresponding emergency response action. The probability of the corresponding emergency response action in the proposed method is estimated through the accident probability analysis and the probability analysis of taking a certain response action. The health consequence estimation is based on air exchange rate test of the shelter buildings as well as accident consequence calculation. The evaluation of shelter-in-place risks based on “as low as reasonably practicable (ALARP)” guidelines was employed to provide suggestions for emergency management under both normal conditions and off normal conditions. A case study of risk assessment of sheltering in the local residential houses in Xuanhan County of Sichuan Province, China was taken as an example to illustrate the proposed risk assessment process of shelter-in-place and its application in the decision-making process for emergency management.