Handling data uncertainties in event tree analysis

Event tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.     

Cost-based fire risk assessment in natural gas industry by means of fuzzy FTA and ETA

Fire is the most prevalent accident in natural gas facilities. In order to assess the risk of fire in a gas processing plant, a fault tree analysis (FTA) and event tree analysis (ETA) has been developed in this paper. By utilizing FTA and ETA, the paths leading to an outcome event would be visually demonstrated. The framework was applied to a case study of processing plant in South Pars gas complex. All major underlying causes of fire accident in a gas processing facility determined through a process hazard analysis (PHA). Fuzzy logic has been employed to derive likelihood of basic events in FTA from uncertain opinion of experts. The outcome events in event tree has been simulated by computer model to evaluate their severity. In the proposed methodology the calculated risk has the unit of cost per year which allows the decision makers to discern the benefit of their investment in safety measures and risk mitigation.     

石油化工储存装置定量风险评价方法研究

提出通过基础失效概率数据库、事故树分析、事件树分析3种方式来确定重大事故的发生概率.阐述了外界气象条件和人员分布情况对风险的影响和确定方法,给出了利用区域网格方式计算装置在平面某点的个人风险叠加模型和社会风险计算方法.最后,研制开发了石油化工储存装置定量风险评价软件,利用该软件计算了某化工厂4个储存装置所产生的个人风险...     

Methodology for computer aided fuzzy fault tree analysis

Probabilistic risk assessment (PRA) is a comprehensive, structured and logical analysis method aimed at identifying and assessing risks of complex process systems. PRA uses fault tree analysis (FTA) as a tool to identify basic causes leading to an undesired event, to represent logical dependency of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event.To conduct a quantitative fault tree analysis, one needs a fault tree along with failure data of the basic events (components). Sometimes it is difficult to have an exact estimation of the failure rate of individual components or the probability of occurrence of undesired events due to a lack of sufficient data. Further, due to imprecision in basic failure data, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising out of subjectivity of the data.This paper presents a methodology for a fuzzy based computer-aided fault tree analysis tool. The methodology is developed using a systematic approach of fault tree development, minimal cut sets determination and probability analysis. Further, it uses static and dynamic structuring and modeling, fuzzy based probability analysis and sensitivity analysis.This paper also illustrates with a case study the use of a fuzzy weighted index and cutsets importance measure in sensitivity analysis (for system probabilistic risk analysis) and design modification.     

Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis

Failure of oil and gas transmission pipelines was analyzed by fault tree analysis in this paper. According to failure modes of pipeline: leakage and rupture, a fault tree of the pipeline was constructed. Fifty-five minimal cut sets of the fault tree had been achieved by qualitative analysis, while the failure probability of top event and the important analyses of basic events were evaluated by quantitative analysis. In conventional fault tree analysis, probabilities of the basic events were treated as precise values, which could not reflect real situation of system because of ambiguity and imprecision of some basic events. In order to overcome this disadvantage, a new method was proposed which combined expert elicitation with fuzzy set theories to evaluate probability of the events. As an example, failure probability of pipeline installation was assessed by using the proposed method, achieving its fuzzy failure probability of 6.4603×10⁻³. The method given in this article is effective to treat fuzzy events of FTA.     

Mapping safety culture attributes with integrity management program to achieve assessment goals: A framework for oil and gas pipelines industry

Introduction: The safety of oil and gas pipelines is an increasing concern for the public, government regulators, and the industry. A safety management system cannot be efficient without having an effective integrity management program (IMP) and a strong safety culture. IMP is a formal document (policies, planning, scheduling, and technical processes) while safety culture is a measure of views, beliefs, and traditions about safety. For regulatory authorities and O&G companies, assessing the effectiveness of both the IMP and safety culture through regulatory audits is a daunting task with indistinct findings. Method: An integrated framework based on regulatory audits is developed to assess the maturity of safety culture based on IMP efficacy through risk-based approach by using failure mode and effect analysis (FMEA). The framework focuses on three distinct aspects, the probability of failure occurrence in case of the non-compliance of regulatory and program requirements, severity of non-compliance, and effectiveness of the corrective actions. Results: Program requirements and performance indicators are translated into assessment questions which are grouped into 18 IMP components. Subsequently, these components are linked with four safety culture attributes. Sensitivity analysis revealed that four IMP components, i.e., organizational roles and responsibilities, policy and commitment, risk assessment, and training and competency, significantly affect the safety culture maturity level. Conclusions: Individual assessment of IMP and safety culture in O&G sector consumes extensive time and efforts in the auditing process. The framework facilitates the process by pursuing common criteria between IMP and safety culture. The O&G companies and regulator can prioritize the improvement plans and guidelines using the framework's findings. Practicalapplications:The integrated framework developed in this research will improve the existing assessment mechanism in O&G companies. The framework has been effectively implemented on a case of 17 upstream O&G pipeline-operating companies in the province of British Columbia, Canada.     

Incident tree model and incident tree analysis method for quantified risk assessment: An in-depth accident study in traffic operation

Fault tree analysis (FTA) is a logically structured process that can help identify potential causes of system failure before the failures actually occur. However, FTA often suffers from a lack of enough probabilistic basic events to check the consistency of the logic relationship among all events through linkage with gates. Sometimes, even logic relationship among all events is difficult to determine, and failures in system operation may have been experienced rarely or not at all. In order to address the limitations, this paper proposes a novel incident tree methodology that characterizes the information flow in a system instead of logical relationship, and the amount of information of a fuzzy incident instead of probability of an event. From probability statistics to fuzzy information quantities of basic incidents and accident, we propose an incident tree model and incident tree analysis (ITA) method for identification of uncertain, random, complex, possible and variable characteristic of accident occurrence in quantified risk assessment. In our research, a much detailed example for demonstrating how to create an incident tree model has been conducted by an in-depth analysis of traffic accident causation. The case study of vehicle-leaving-roadway accident with ITA illustrates that the proposed methodology may not only capture the essential information transformations of accident that occur in system operation, but also determine the various combinations of hardware faults, software failures and human errors that could result in the occurrence of specified undesired incident at the system level even accident.     

城市管道系统风险分析及闭环管理研究

为了探索构建城市管道系统安全及可靠性风险管理体系,基于FMECA,FTA&ETA及FRACAS等技术,建立涵盖故障模式辨识、影响及危害度分析、纠正措施执行等内容,且遵循闭环管理原则的科学、完整的风险闭环管理模式。针对城市管道安全及可靠性研究存在的局限性,引入FCE改进的FMECA和模糊灰关联FTA等定量计算方法,克服统计信息匮乏、数据模糊等瓶颈。研究结果表明:基于改进“3F”一体化技术的系统风险闭环管理体系契合城市管道风险管控需求,为多态、多要素耦合、不确定性复杂系统整体风险分析研究提供新思路。     

Safety assessment of natural gas storage tank using similarity aggregation method based fuzzy fault tree analysis (SAM-FFTA) approach

Fault tree analysis (FTA) is an important method to analyze the failure causes of engineering systems and evaluate their safety and reliability. In practical application, the probabilities of bottom events in FTA are usually estimated according to the opinions of experts or engineers because it is difficult to obtain sufficient probability data of bottom events in fault tree. However, in many cases, there are many experts with different opinions or different forms of opinions. How to reasonably aggregate expert opinions is a challenge for the engineering application of fault tree method. In this study, a fuzzy fault tree analysis approach based on similarity aggregation method (SAM-FFTA) has been proposed. This method combines SAM with fuzzy set theory and can handled comprehensively diverse forms of opinions of different experts to obtain the probabilities of bottom events in fault tree. Finally, for verifying the applicability and flexibility of the proposed method, a natural gas spherical storage tank with a volume of 10,000 m³ was analyzed, and the importance of each bottom event was determined. The results show that flame, lightning spark, electrostatic spark, impact spark, mechanical breakdown and deformation/breakage have the most significant influence on the explosion of the natural gas spherical storage tank.     

基于FMECA与模糊FTA的余热锅炉安全分析

为了保证余热锅炉安全运行,预防爆炸事故发生,利用FMECA方法和模糊FTA方法,研究余热锅炉事故致因。通过对余热锅炉潜在危险因素的分析辨别,探讨设备故障类型、原因及相应处理方法,引入模糊FTA对余热锅炉爆炸事故定性和定量分析,进而构建了基于FMECA与模糊FTA的余热锅炉安全分析框架,并计算得出事故发生的模糊概率以及对基本事件的敏感性分析。研究表明,余热锅炉系统的可靠度大约为96.92%,未按规定排污,报警器失灵,安全阀压力连接管堵塞及除氧器不合格事件对顶事件发生概率的影响最大,从而为该系统的安全决策提供支持。     

基于模糊Bow-tie模型的油轮靠港装卸作业溢油风险分析

为了全面分析油轮靠港装卸作业溢油事故风险,在风险定量分析中引入了模糊Bow-tie模型,基于事故树方法分析油轮靠港装卸作业发生溢油事故的原因,采用事件树方法分析溢油事故可能导致的后果,利用模糊集理论与专家评价相结合的方法分析油轮靠港装卸作业溢油的模糊可能值,采用层次分析法确定作业溢油后果因素的权重值,采用矩阵乘法计算溢油后果风险值。分析结果表明:油轮靠港装卸作业过程中一旦发生溢油,发生火灾+污染、爆炸+污染的概率较高。基于以上风险分析提出了油轮靠港装卸作业风险的防控措施,可为油轮靠港装卸作业安全风险管理提供参考。     

A new pre-assessment model for failure-probability-based-planning by neural network

At present, the prediction of failure probability is based on the operation period for laid pipelines, and the method is complicated and time-consuming. If the failure probability can be predicted in the planning stage, the risk assessment system of gas pipeline will be greatly improved. In this paper, the pre-laying assessment model is established to minimize risk of leakage due to piping layout. Firstly, Fault Tree Analysis (FTA) modeling is carried out for urban natural gas pipeline network. According to expert evaluation, 84 failure factors, which can be determined in the planning stage, are selected as the input variables of the training network. Then the FTA model is used to calculate the theoretical failure probability value, and the failure probability prediction model is determined through repeated trial calculation based on BP (Back Propagation Neural Network) and RBF (Radial Basis Function), for obtaining the optimal network parameter combination. Finally, two prediction models are used to calculate the same example. By comparing our pre-assessment model with the theoretical prediction consequences of the fault tree, the results show that the error of RBF prediction model can be close to 3%, which proves the validity and correctness of the method.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.     

Developing safety indicators for preventing offshore oil and gas deepwater drilling blowouts

An important question with respect to the Macondo blowout is whether the accident is a symptom of systemic safety problems in the deepwater drilling industry. An answer to such a question is hard to obtain unless the risk level of the oil and gas (O&G) industry is monitored and evaluated over time. This article presents information and indicators from the Risk Level Project (RNNP) in the Norwegian O&G industry related to safety climate, barriers and undesired incidents, and discusses the relevance for deepwater drilling. The main focus of the major hazard indicators in RNNP is on production installations, whereas only a limited number of incident indicators and barrier indicators are related to mobile drilling units. The number of kicks is an important indicator for the whole drilling industry, because it is an incident with the potential to cause a blowout. Currently, the development and monitoring of safety indicators in the O&G industry seems to be limited to a short list of “accepted” indicators, but there is a need for more extensive monitoring and understanding. This article suggests areas of extensions of the indicators in RNNP for drilling based on experience from the Macondo blowout. The areas are related to schedule and cost, well planning, operational aspects, well incidents, operators’ well response, operational aspects and status of safety critical equipment. Indicators are suggested for some of the areas. For other areas, more research is needed to identify the indicators and their relevance and validity.     

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。     

Consequence risk analysis using operating procedure event trees and dynamic simulation

Faults due to human errors cost the petrochemical industry billions of dollars every year and can have adverse environmental consequences. Unquantified human error probabilities exist during process state transitions performed each day by process operators using standard operating procedures. Managing the risks associated with operating procedures is an essential part of managing the overall safety risk. Additional operator training and safety education cannot eliminate all such faults due to human errors; therefore, we propose an operating procedure event tree (OPET) like analysis with branches and events specifically designed to perform risk analysis on operating procedures. The OPET method adapts event trees to analyze the risk due to human error while performing operating procedures. We consider human error scenarios during the procedure and determine the likely consequences by applying dynamic simulation. The modified event tree provides an estimate of the error frequencies.Operating procedure steps were developed, and potential operator faults were determined for two typical equipment switching procedures found in chemical plant operations. Then, dynamic simulation using Aspen HYSYS software was applied to determine the overpressure related consequences of each fault. Finally, the error frequencies resulting from those scenarios were analyzed using operating procedure event trees. We found that a typical ethylene plant gas header would overpressure with 0.6% frequency per manual dryer switch. Since dryer switches occur from every few days up to once per shift, these results suggest that dryer switching should be automated to ensure safe and environmentally friendly operation. Process dryer switching performed manually by operators opening and closing gate valves can be automated with control valves and a distributed control system. A sample distillation column was found to overpressure with 0.85% frequency per manual reflux pump switch.     

因果分析与系统安全性风险评价方法

综合了故障树分析和事件树分析的方法,提出因果分析的框架,研究了基于因果分析建立事故脚本的方法。在此基础上,还对因果分析的概率风险评价方法进行研究,并利用该评价方法,对电机过热的安全性问题进行分析,给出了分析计算的结果     

基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*

为分析海底管道运行中存在的泄漏风险,提出1种基于毕达哥拉斯模糊数与贝叶斯网络的风险评估模型。首先,通过毕达哥拉斯模糊数转换专家定性评价,拓展专家意见模糊范围;然后,结合主客观组合赋权法,利用毕达哥拉斯梯形爱因斯坦混合几何算子（PTFEHG）实现专家意见的聚合;最后,通过贝叶斯网络的推理与敏感性分析,计算海底管道泄漏风险的失效概率,并辨识关键风险因素。研究结果表明:该方法可以结合专家意见对海底管道泄漏风险进行定量分析,并识别导致泄漏事故的关键风险因素,对海底管道安全管理具有指导意义。     

A bayesian network-based safety assessment method for solid propellant granule-casting molding process

The safety of the solid propellant molding process is vital for the stable production of high-quality propellants. Failure events caused by abnormal parameters in the molding process may have catastrophic consequences. In this paper, a Bayesian network (BN) model is proposed to assess the safety of the solid propellant granule-casting molding process. Fault tree analysis (FTA) is developed to construct a causal link between process variables and process failures. Subsequently, expert experience and fuzzy set theory (FST) are used to obtain failure probabilities of the basic events (BEs). Based on the mapping rules, FTA provides BN with reliable prior knowledge and a network structure with interpretability. Finally, when new evidence is obtained, the probability is updated with the diagnostic reasoning capability of BN. The results of the sensitivity analysis and diagnostic inference were combined to identify key parameters in the granule-casting molding process, including curing temperature, vacuum degree, extrusion, calendering roll distance, length setting value, holding time, and polish time. The results of this paper can provide effective supporting information for managers to conduct process safety analysis.