Fuzzy logic for piping risk assessment (pfLOPA)

This paper explores the application of the fuzzy logic for risk assessment of major hazards connected with transportation of flammable substances in long pipelines. As a basis for risk assessment, the framework of the fuzzy Layer of Protection Analysis (fLOPA) was used. fLOPA presents a new approach to risk assessment based on two assumptions: 1. different effects of the layer of protection functions on particular elements of the risks (frequency and severity of consequence), and 2. the application of fuzzy logic system (FLS) composed of three elements: fuzzification, inference process and defuzzification. A further calculation follows LOPA methodology with the use of fuzzy logic system where fuzzy risk matrix is used for risk assessment. A typical case study comprising section of a long pipeline failure is performed and a comparison between the classical LOPA approach and fuzzy approach is made.     

基于模糊保护层的池火灾事故风险分析

为计算引发池火灾事故的风险值,提高事故风险的量化水平,判断现有风险控制措施是否满足风险容忍度的要求,为制定减缓风险措施提供依据,给出了新的池火灾风险评估模型。基于传统的保护层分析模型(LOPA),结合模糊集合理论,引入模糊风险矩阵进行风险评估,构建适用于引发池火灾事故的模糊保护层(fL OPA)风险分析模型。该模型的特点是将模糊逻辑和保护层分析结合,减少了传统保护层分析方法计算过程中的不确定性因素,引入严重度减少指数(SRI)概念,使严重度计算、风险评估更加准确。运用该模型对原油储罐泄漏池火灾事故风险进行分析,给出风险决策方案,判断现有保护措施是否能控制风险在可容忍范围内,实例验证了模型的可行性。     

Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis

Vast amounts of oil & gas (O&G) are consumed around the world everyday that are mainly transported and distributed through pipelines. Only in Canada, the total length of O&G pipelines is approximately 100,000 km, which is the third largest in the world. Integrity of these pipelines is of primary interest to O&G companies, consultants, governmental agencies, consumers and other stakeholder due to adverse consequences and heavy financial losses in case of system failure. Fault tree analysis (FTA) and event tree analysis (ETA) are two graphical techniques used to perform risk analysis, where FTA represents causes (likelihood) and ETA represents consequences of a failure event. ‘Bow-tie’ is an approach that integrates a fault tree (on the left side) and an event tree (on the right side) to represent causes, threat (hazards) and consequences in a common platform. Traditional ‘bow-tie’ approach is not able to characterize model uncertainty that arises due to assumption of independence among different risk events. In this paper, in order to deal with vagueness of the data, the fuzzy logic is employed to derive fuzzy probabilities (likelihood) of basic events in fault tree and to estimate fuzzy probabilities (likelihood) of output event consequences. The study also explores how interdependencies among various factors might influence analysis results and introduces fuzzy utility value (FUV) to perform risk assessment for natural gas pipelines using triple bottom line (TBL) sustainability criteria, namely, social, environmental and economical consequences. The present study aims to help owners of transmission and distribution pipeline companies in risk management and decision-making to consider multi-dimensional consequences that may arise from pipeline failures. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process. A simple example is used to demonstrate the proposed approach.     

Application of fuzzy logic to explosion risk assessment

Safety and health of workers potentially being at risk from explosive atmospheres are regulated by separate regulations (ANSI/AIHA in USA and ATEX in the European Union). The ANSI/AIHA does not require risk assessment whereas it is compulsory for ATEX. There is no standard method to do that assessment. For that purpose we have applied the explosion Layer of Protection Analysis (ExLOPA), which enables semi-quantitative risk assessment for process plants where explosive atmospheres occur. The ExLOPA is based on the original work of CCPS for LOPA taking into account an explosion accident scenario at workplace. That includes typical variables appropriate for workplace explosion like occurrence of the explosive atmosphere, the presence of effective ignition sources, activity of the explosion prevention and mitigation independent protection layers as well as the severity of consequences. All those variables are expressed in the form of qualitative linguistic categories and relations between them are presented using expert based engineering knowledge, expressed in the form of appropriate set of rules. In this way the category of explosion risk may be estimated by the semi-quantitative analysis. However, this simplified method is connected with essential uncertainties providing over or under estimation of the explosion risk and may not provide real output data.In order to overcome this problem and receive more detailed quantitative results, the fuzzy logic system was applied. In the first stage called fuzzification, all linguistic categories of the variables are mapped by fuzzy sets. In the second stage, the number of relation between all variables of analysis are determined by the enumerative combinatorics and the set of the 810 fuzzy rules “IF-THEN” is received. Each rule enables determination of the fuzzy risk level for a particular accident scenario. In the last stage, called defuzzification, the crisp value of final risk is obtained using a centroid method. The final result of the risk presents a contribution of each risk category represented by the fuzzy sets (A, TA, TNA and NA) and is therefore more precise and readable than the traditional approach producing one category of risk only. Fuzzy logic gives a possibility of better insights into hazards and safety phenomena for each explosion risk scenario. It is not possible to receive such conclusions from the traditional ExLOPA calculation results. However it requires the application of computer-aided analyses which may be partially in conflict with a simplicity of ExLOPA.The practical example provides a comparison between the traditional results obtained by ExLOPA and by fuzzy ExLOPA methods.     

AFRA – Heuristic expert system to assess the atmospheric risk of sulphide waste dumps

In 2006, an unprecedented atmospheric confined space accident took place in a sampling shed at the Sullivan Mine in Kimberley, British Columbia. This accident suggests that a risk assessment should be carried out on a regular basis at mine reclamation sites for many years after closure. In this paper, an Atmospheric Fuzzy Risk Assessment (AFRA) tool is described that can assess atmospheric risk given heuristic and measured data at such sites. It can also serve to transfer knowledge about atmospheric hazards in an enclosed structure. The system uses fuzzy logic to input and output information and to perform weighted inferencing. The paper describes the developmental process as well as system verification and validation based on a number of known test and reference waste dumps. AFRA is a heuristic expert system based on fuzzy logic and the first tool that was developed to assess the atmospheric risk of mine waste dumps. The atmospheric risk is estimated by fuzzy Mamdani system given the values of four major elements of risk comprising of: gas generation, gas emission, gas confinement, and human exposure. The ability of AFRA to adapt its risk assessment to different climate conditions is explained. There are many physical, chemical, and environmental factors which fluctuate over time affecting oxygen-depletion in waste dumps. AFRA can help mining engineers and mine managers recognize this type of danger when conducting a confined space inventory at a reclamation site.     

Fuzzy logic-based approach for identifying the risk importance of human error

In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by “human error”. There are uncertainties in the traditional human error risk assessment (e.g. HECA) due to the uncertainties and imprecisions in Human Error Probability (HEP), Error-Effect Probability (EEP) and Error Consequence Severity (ECS). While fuzzy logic can deal with uncertainty and imprecision. It is an efficient tool for solving problems where knowledge uncertainty may occur. The purpose of this paper is to develop a new Fuzzy Human Error Risk Assessment Methodology (FHERAM) for determining Human Error Risk Importance (HERI) as a function of HEP, EEP and ECS. The modeling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs (i.e. HEP, EEP, and ECS) and outputs (i.e. HERI) of a risk assessment system in the form of IF–THEN rules. It is implemented on fuzzy logic toolbox of MATLAB using Mamdani techniques. A case example is presented to demonstrate the proposed approach. Results show that the method is more realistic than the traditional ones, and it is practicable and valuable.     

安全屏障在蒸气云爆炸中的控制效果研究

为了研究安全屏障在蒸气云爆炸事故中的控制效果,运用蝴蝶结法、TNT当量法建立研究模式,计算安全屏障作用下的事故概率、分析事故后果,并结合风险矩阵从概率和后果方面评价其风险程度。以事故概率、风险程度为指标,表征、分析安全屏障的控制效果,并对较高、高风险提出控制措施。将该模式应用于实例分析,结果表明该企业的安全屏障可以降低事故的发生概率。但是由于后果严重度的影响,其风险程度仍处于较高水平,需要进一步加强安全措施。     

A fuzzy logic and probabilistic hybrid approach to quantify the uncertainty in layer of protection analysis

Layer of protection analysis (LOPA) is a widely used semi-quantitative risk assessment method. It provides a simplified and less precise method to assess the effectiveness of protection layers and the residual risk of an incident scenario. The outcome failure frequency and consequence of that residual risk are intended to be conservative by prudently selecting input data, given that design specification and component manufacturer's data are often overly optimistic. There are many influencing factors, including design deficiencies, lack of layer independence, availability, human factors, wear by testing and maintenance shortcomings, which are not quantified and are dependent on type of process and location. This makes the risk in LOPA usually overestimated. Therefore, to make decisions for a cost-effective system, different sources and types of uncertainty in the LOPA model need to be identified and quantified. In this study, a fuzzy logic and probabilistic hybrid approach was developed to determine the mean and to quantify the uncertainty of frequency of an initiating event and the probabilities of failure on demand (PFD) of independent protection layers (IPLs). It is based on the available data and expert judgment. The method was applied to a distillation system with a capacity to distill 40 tons of flammable n-hexane. The outcome risk of the new method has been proven to be more precise compared to results from the conventional LOPA approach.     

油气储运设施事故风险指数模糊逻辑评估方法

油气储运设施风险是其事故发生概率和事故后果的综合度量,而事故概率和后果的定量评估结果往往是具有不确定性的数据,以确定性风险评估准则为基础的传统风险矩阵法和风险值法显然难以评估油气储运设施风险。为此提出开展油气储运设施事故风险的模糊逻辑推理法,首先,对风险矩阵的概率语言等级和损失语言等级的边界进行定量划分;然后,建立油气储运设施风险矩阵模糊集和模糊逻辑推理规则;最后,通过风险模糊推理运算和模糊风险解模糊化以确定油气储运设施的风险水平。实例应用与分析表明,利用推荐方法可得到较为详尽的风险数据信息,不但风险指数更加清晰,而且其所属风险等级类别也更加明确,评估结果能更好地指导油气储运设施的风险管理。     

Developing a new fuzzy inference system for pipeline risk assessment

The problem of less and/or even lack of information and uncertainty in modeling and decision making plays a key role in many engineering problems; so that, it results in designers and engineers could not reach to sure solutions for the problems under consideration. In this paper, an application of the fuzzy logic for modeling the uncertainty involved in the problem of pipeline risk assessment is developed. For achieving the aim, relative risk score (RRS) methodology, one of the most popular techniques in pipeline risk assessment, is integrated with fuzzy logic. The proposed model is performed on fuzzy logic toolbox of MATLAB^® using Mamdani algorithm based on experts' knowledge. A typical case study is implemented and a comparison between the classical risk assessment approach and the proposed model is made. The results demonstrate that the proposed model provides more accurate, precise, sure results; so that, it can be taken into account as an intelligent risk assessment tool in different engineering problems.     

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.     

Uncertainty representation and propagation in quantified risk assessment using fuzzy sets

It is generally acknowledged that there are substantial uncertainties present in any analysis of risk. This paper provides a brief overview of the current techniques used for uncertainty analyses, and highlights their inappropriateness for practical use in the complete risk assessment process. The concept of fuzzy sets as a means for quantifying uncertainty is introduced and a case study demonstrates the application of this method to a simple consequence analysis where parameter uncertainty is considered. The results of this fuzzy analysis are compared with those of a more traditional probabilistic approach using a Monte Carlo simulation. This comparison demonstrates that the novel approach of fuzzy sets is a more appropriate technique due to its non-statistical nature and that the amount of computation required is substantially reduced compared to the traditional probabilistic approach. The versatility of fuzzy set theory suggests that this approach could also be used to quantify other types of uncertainty present in the risk assessment process, including model uncertainty and expert opinion.     

基于三角模糊理论的尾矿库风险评价研究

根据尾矿库的特点和我国现行的尾矿库安全生产监督管理法律法规及标准规范的要求,构建了尾矿库风险评价指标体系。综合考虑评价指标对风险发生可能性及后果严重程度的不同影响来确定指标权重,同时考虑到权重确定和指标赋值中的模糊性和不确定性等问题,选用三角模糊理论建立了尾矿库风险评价模型,并以本溪某尾矿库为例进行说明。理论分析和实例计算表明,该方法对尾矿库风险评价有很好的适用性。     

基于模糊数学的石油化工装置HAZOP风险分析技术研究

对传统的HAZOP分析中偏差原因发生可能性进行量化。对于有统计数据的,根据行业数据、公司经验及企业事故建立HAZOP风险分析统计数据库;对于没有统计数据的HAZOP分析偏差原因发生概率,通过专家主观评判,用模糊数理论将专家自然语言转换为模糊数,采用左右模糊排序法将模糊数转换为模糊失效概率值。研究了偏差后果严重程度的划分标准,并根据偏差原因概率和偏差后果严重程度确定风险等级,利用风险矩阵得出偏差风险的大小。从而把HAZOP分析方法从定性改进为半定量的分析方法。据此对石油化工装置进行了HAZOP风险分析。     

SPA–fuzzy method based real-time risk assessment for major hazard installations storing flammable gas

For monitoring and control of major hazard installations storing flammable gas, the risk based warning/early-warning is very important. A set-pair analysis (SPA) based fuzzy assessment method (SPA–fuzzy) is proposed for the real-time risk assessment in this paper. Based on principle of SPA and fuzzy logic theory, the likelihood of accident occurrence and the consequence of the accident can be assessed, and the risk value or risk degree can be evaluated. The method takes advantage of the data acquired from the real-time safety monitoring system, so that the varying of the risk can be revealed during an accident developing. The risk assessment simulation of VCE accident caused by gas leaked from LPG tank is performed. It is shown that SPA–fuzzy method has the same risk value as that assessed by normal fuzzy method.     

Fuzzy-AHP在LNG接收站风险辨识中的应用

笔者以液化天然气(LNG)接受站的生产工艺、设备、作业环境的特点为背景,提出一种基于模糊层次分析方法(Fuzzy-Analytic Hierarchy Process)的风险评估方法。首先,根据LNG接收站风险事故多层次、多因素及不确定的特点,结合本行业的安全标准,确立了LNG接受站的风险因素和评价指标,建立接受站的安全评价体系;随后,运用Fuzzy-AHP方法确定权重矢量和模糊评价矩阵,并通过模糊运算求出决策矢量,实现对风险因素的排序以达到风险辨识目的;最后,对国内某LNG站进行了实例计算。计算表明该接收站的硬件设施完善,但应加强风险管理,制定相应的措施应对因气候条件、储罐区管理不当及船舶安全保护不到位等引发的事故。结果表明基于LNG站的Fuzzy-AHP风险辨识模型的安全性综合评价是有效的。     

基于三角模糊数的HAZOP分析在石油化工装置中的应用

工艺危害分析强调运用系统的方法对危害进行辨识、分析,并采取必要的措施消除和减少危害。HAZOP分析能对工艺过程非常系统、全面的进行分析,但传统的HAZOP分析在量化风险时,对于偏差原因发生的可能性评价存在较大的主观性。本文对于没有统计资料的HAZOP分析偏差原因发生可能性,采用专家打分法,利用三角模糊数来表示其模糊发生概率。对于有统计资料的偏差原因,直接表示成三角模糊数。这种方法能够很好的表示HAZOP分析偏差发生概率。介绍了基于三角模糊数的HAZOP分析步骤,并在石油化工装置中进行了应用。这对HAZOP分析技术在石油化工装置中的推广具有重要意义。     

Fuzzy risk modeling of process operations in the oil and gas refineries

Operating several assets has resulted in more complexity and so occurrence of some major accidents in the refining industries. The process operations risk factors including failure frequency and the consequence components like employees' safety and environment impacts, operation downtime, direct and indirect cost of operations and maintenance, and mean time to repair should be considered in the analysis of these major accidents in any refinery. Considering all of these factors, the risk based maintenance (RBM) as a proper risk assessment methodology minimizes the risk resulting from asset failures. But, one of the main engineering problems in risk modeling of the complex industries like refineries is uncertainty due to the lack of information. This paper proposes a model for the risk of the process operations in the oil and gas refineries. The fuzzy logic system (FLS) was proposed for risk modeling. The merit of using fuzzy model is to overcome the uncertainty of the RBM components. This approach also can be accounted as a benchmark for future failures. A unified risk number would be obtained to show how the criticality of units is. The case study of a gas plant in an oil refinery is performed to illustrate the application of the proposed model and a comparison between the results of both traditional RBM and fuzzy method is made.For the case study, 26 asset failures were identified. The fuzzy risk results show that 3 failures have semi-critical level and other 23 failures are non-critical. In both traditional and fuzzy RBM methods, some condenser failures had the highest risk number and some pumps were prioritized to have the lowest risk level. The unit with unified risk number less than 40 is in the non-critical conditions. Proposed methodology is also applicable to other industries dealing with process operations risks.     

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.     

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。