Risk measures constituting a risk metrics which enables improved decision making: Value-at-Risk

In this work, a novel approach is proposed for expressing the risks of process plants consisting of a large number of scenarios, in the form of a risk metrics of leading indicators to prevent potential high profile industry accidents. The methodology includes: 1) risk estimation of a portfolio by CPQRA (or QRA), 2) monetization of the tangible risks with the inclusion of the lost time of production, 3) estimation of the maximum portfolio loss using Value-at-Risk approach, 4) inclusion of intangible risks using FN-curve and, 5) generation of F$-curve of tangible risks. The proposed methodology can particularly help in understanding the stakes at risk by performing the overall cost-benefit analysis, for identifying the most risky scenarios and identifying critical equipments to enable better risk-informed decision making in order to adopt appropriate risk mitigation measures. This work establishes the groundwork for developing measures for understanding and comparing the large number of risk values derived from QRA studies for large portfolios. It will aid in less subjective decision making as it enables the decision maker to choose the most preferred portfolio option among alternatives. Decisions made with the accurate understanding of the consequences of risks can significantly reduce potential work-related fatalities, property losses and save millions of dollars.     

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.     

An extension to Fuzzy Fault Tree Analysis (FFTA) application in petrochemical process industry

Fault Tree Analysis (FTA) is an established technique in risk management associated with identified hazards specific to focused fields. It is a comprehensive, structured and logical analysis method aimed at identifying and assessing hazards of complex systems. To conduct a quantitative FTA, it is essential to have sufficient data. By considering the fact that sufficient data is not always available, the FTA method can be adopted into the problems under fuzzy environment, so called as Fuzzy Fault Tree Analysis (FFTA). This research extends FFTA methodology to petrochemical process industry in which fire, explosion and toxic gas releases are recognized as potential hazards. Specifically, the case study focuses on Deethanizer failure in petrochemical plant operations to demonstrate the proposed methodology. Consequently, the study has provided theoretical and practical values to challenge with operational data shortage in risk assessment.     

定量风险评价技术在管道城市穿越段的应用

介绍了管道高后果区定量风险评价的方法和风险可接收标准.将定量风险评价技术在我国某长输原油管道城市穿越段的应用表明,定量风险评价方法适用于人口密集的管道高后果区,能对管道高后果区的风险管理、决策提供重要的参考.     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

An engineer-based methodology to perform Explosion Risk Analyses

Explosion Risk Analyses (ERA) are usually performed as part of the Quantitative Risk Assessment (QRA). The combination of frequencies and associated consequences allow to get a risk picture of the facility and provides decision support to the risk owner. The outcomes of this study allow also to provide, after adequate interpretation, Design Explosion Loads (DEL) to engineering disciplines (e.g. structures, piping and equipment) according to a given Risk Acceptance Criterion (RAC). For most of the offshore applications, the consequence part of the ERA is done with Computational Fluids Dynamics (CFD) to properly handle congestion and confinement effects as simple models cannot. With the increase of computational power, thanks to Moore's Law, there is an increasing trend to perform more and more CFD simulations with the expectation to improve confidence in results while taking more and more probabilistic variables into account. In the early 2000s, it was 10's of simulations, in the 2010s, it was 100's and now it is common to reach 1000's. However, one should remark that there is still a lot of uncertainties behind these studies since the geometry maturity is generally not enough especially at the early stage of detailed engineering when the preliminary Design Explosion Loads (pDEL) should be provided to disciplines. Anticipated congestion is normally put in the model, but it usually put a bias at the beginning of the consequence modelling part. In the risk-based approach, the frequency part is also of major importance. One need to keep in mind that consequence refinement should be done in close relation with the frequency refinement to ensure consistency in the approach. The practical methodology presented in this paper was developed to provide reliable inputs to engineering disciplines, taking into consideration uncertainties and potential spread of results while using a reasonable number of CFD scenarios. Finally, the safety engineers are still the key contributor in the performance of the ERA, and hence brain-based design is kept in the loop while minimizing computer-based design.     

Failure Mode and Effect Analysis using an integrated approach of clustering and MCDM under pythagorean fuzzy environment

Failure Mode and Effect Analysis (FMEA) is an effective risk analysis and failure avoidance approach in the design, process, services, and system. With all its benefits, FMEA has three limitations: failure mode risk assessment and prioritization, complex FMEA worksheets, and difficult application of FMEA tables. This paper seeks to overcome the shortcomings of FMEA using an integrated approach based on a developed Pythagorean fuzzy (PF) k-means clustering algorithm and a popular MCDM method called PF-VIKOR. In the first step, Pythagorean fuzzy numbers (PFNs) were used to collect Severity (S), Occurrence (O), and Detection (D) factors for failure modes to incorporate uncertainty and fuzziness into subjective judgments. Afterward, failure modes were clustered by developing a novel k-means clustering algorithm that accepts PFNs as input. Finally, the PF-VIKOR approach was used to analyze the ordering of cluster risks. The proposed approach was implemented in the dehydration unit of an Iranian gas refinery and the results were compared with the traditional FMEA. The findings showed the flexibility and applicability of the proposed approach in addressing real-world problems. This research provides two key contributions: (1) designing a PFN-based k-means clustering algorithm that tackles FMEA limitations and (2) using the PF-VIKOR method for prioritizing and evaluating failure mode clusters.     

Uncertainties in QRA: Analysis of losses of containment from piping and implications on risk prevention and mitigation

Quantitative Risk Assessment (QRA) is commonly used in the chemical industry to support decision-making. Common practices are based on standard methods, such as fault tree, event tree, etc.; in this frame, risk is a function of frequency of events (probability) and associated consequences (negative outcomes), but relevant uncertainties often are not properly taken into account in the derived results. This paper presents the application of an extended risk analysis of loss of containments for a case-study with the following aims: firstly, the uncertainties related to the results of the analysis, which derive from assumption in the application of the standard models, are qualitatively assessed; secondly the application allows evaluating the impact of the uncertainties on the trustworthiness of the results and, finally, commenting about their use in the risk prevention and mitigation.     

Optimizing the design of storage facilities through the application of ISD and QRA

Four strategies can be used to achieve safety in chemical processes: inherent, passive, active and procedural. However, the strategy that offers the best results is the inherent safety approach, especially if it is applied during the initial stages of a project. Inherently Safer Design (ISD) permanently eliminates or reduces hazards, and thus avoids or diminishes the consequences of incidents. ISD can be applied using four strategies: substitution, minimization, moderation and simplification. In this paper, we propose a methodology that combines ISD strategies with Quantitative Risk Assessment (QRA) to optimize the design of storage installations. As 17% of major accidents in the chemical industry occur during the storage process and cause significant losses, it is essential to improve safety in such installations. The proposed method applies QRA to estimate the risk associated with a specific design. The design can then be compared to others to determine which is inherently safer. The risk analysis may incorporate complex phenomena such as the domino effect and possible impacts on vulnerable material and human elements. The methodology was applied to the San Juanico tragedy that occurred in Mexico in 1984.     

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.     

油气长输管道定量风险评价

管道风险评价普遍采用以Kent打分法为代表的定性方法,笔者提出了一种新方法,即定量风险评价(QRA),采用基于管道失效历史数据库和已有成熟的数值模型,进行管道失效概率分析和失效后果分析,并以此方法在某输气管道上进行了验证,最后得到管段的绝对风险和人口密集段的个人风险,并进行了风险预测。研究表明,QRA受人员主观判断影响较小,计算方法科学合理,结果量化,对进行检测与维护维修资源的分配具有很好的指导意义。     

低概率重大事故风险与定量风险评价

论述应用定量风险评价(QRA)对评价、控制低概率重大事故风险的重要意义.介绍了低概率重大风险范畴与主要来源,QRA技术的主要用途与基本方法,研发与使用QRA计算重大风险的主要技术程序.提出了在应用QRA评价重大风险时应注意的几个主要技术问题.     

Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

A new methodology for quantitative risk assessment (QRA) integrated with dynamic simulation and accident simulation is proposed. The objective of this study is to discover inherent risks that are undetectable by conventional risk analysis methods based on steady-state conditions. The target process is the reactor section in the heavy oil desulfurization (HOD) process, which is likely to pose vast potential risks due to the high operating conditions of pressure and temperature. First, a dynamic simulation of a shut-down procedure was performed to observe the behavior of process variables using Aspen HYSYS V10, which is a commercially available process software. Based on the results of the dynamic simulation, several blind spots indicating a higher operating pressure than that in the steady-state simulation were identified. To assess the risks of the detected blind spots, a QRA was performed using the commercial software of SAFETI V8.22, which performs risk calculation based on consequence and frequency data. As a result of applying the proposed method to the HOD process, the risk assessment outcome was identified as intolerably risky unlike that of steady-state conditions, thereby indicating that dynamic simulations can serve as a method to spot inherent risks that are undetectable in steady-state conditions. In addition, mitigation procedures that reduce the risk of the process to a tolerable level are performed, thereby enabling a safer and more reliable process.     

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.     

Fuzzy Application Procedure (FAP) for the risk assessment of occupational accidents

This paper concerns a procedure to quantify the risk of occupational accidents based on Fuzzy Logic approach, named Fuzzy Application Procedure (FAP). FAP was developed as a support tool, after the method based on fuzzy logic was developed and validated. The methodology and FAP support tool were found to be able to quantitatively assess the risk of occupational accidents for different industrial and site activities and to identify the most efficient intervention measures that can be taken to reduce risks. The application of FAP to two Italian industrial plant allowed the validation of the procedure. It can be seen how FAP should be considered easy to use for any type of company, with the only requirement of having a sufficient and homogeneous number of accidents recorded, so as to be able to correctly tune the reference parameters of the fuzzy methodology.     

区域自然灾害综合风险模糊随机评价方法

从自然灾害危险性、社会经济易损性和区域设防等多种角度建立了区域自然灾害综合风险评价指标体系。针对典型自然灾害综合风险评价影响因素具有随机性、模糊性和数据资料不精确等多种不确定性,利用蒙特卡洛方法模拟三角模糊数,把三角模糊数及其函数之间的运算简化为普通的实数之间的运算,从而建立区域自然灾害综合风险模糊随机评价模型。研究表明,在评价结果一致的前提下以置信区间形式表示的综合风险评价结果比其他常规方法,提供的信息更加丰富,充分反映了受多种不确定性因素综合影响的区域自然灾害综合风险评价的客观实际情况,研究结果可为区域防御自然灾害与提升综合抗灾能力提供决策依据。     

Estimation of the impact probability in domino effects due to the projection of fragments

Despite the remarkable severity of domino effects in activities at major hazard, a complete methodology analysing such events has not been developed and integrated within Quantitative Risk Analysis (QRA). Such a deficiency appears to be particularly remarkable for domino effects triggered by the projection of fragments. The aim of the present work is therefore to propose a systematic procedure for the quantification of domino effects due to fragments projection within QRA. To achieve this objective, the deterministic approach for the estimation of the realistic trajectory of fragments is entirely reviewed. In order to incorporate such a reviewed approach within the standard QRA, a probabilistic model for the impact probability of the fragments is developed by applying a Monte-Carlo method to the trajectory equations. The validation of the proposed framework is carried out by using the data related to an accident occurred in 1993 in the oil refinery of Milazzo (Italy).     

Inherent risk assessment—A new concept to evaluate risk in preliminary design stage

Quantitative Risk Assessment (QRA) has been a very popular and useful methodology which is widely accepted by the industry over the past few decades. QRA is typically carried out at a stage where complete plant has been designed and sited. At that time, the opportunity to include inherent safety design features is limited and may incur higher cost. This paper proposes a new concept to evaluate risk inherent to a process owing to the chemical it uses and the process conditions. The risk assessment tool is integrated with process design simulator (HYSYS) to provide necessary process data as early as the initial design stages, where modifications based on inherent safety principles can still be incorporated to enhance the process safety of the plant. The risk assessment tool consists of two components which calculate the probability and the consequences relating to possible risk due to major accidents. A case study on the potential explosion due to the release of flammable material demonstrates that the tool is capable to identify potential high risk of process streams. Further improvement of the process design is possible by applying inherent safety principles to make the process under consideration inherently safer. Since this tool is fully integrated with HYSYS, re-evaluation of the inherent risk takes very little time and effort. The new tool addresses the lack of systematic methodology and technology, which is one of the barriers to designing inherently safer plants.     

Embedding the human factor in road tunnel risk analysis

The paper is focusing on road tunnel safety and builds upon the Directive 2004/54/EC launched by the European Commission; the latter sets basic requirements and suggests the implementation of risk assessment in several tunnel cases apart from technical measures imposed on the basis of tunnel structural and operational characteristics. Since the EU Directive does not indicate the method for performing risk assessment, a wide range of methods have been proposed, most of them based on quantitative risk assessment (QRA). Although the majority of current road tunnel QRAs assess physical aspects of the tunnel system and consider several hazards concerning the transportation of dangerous goods through a tunnel, they do not take into account, sufficiently, several organizational and human-related factors that can greatly affect the overall safety level of these critical infrastructures. To cope with this limitation this paper proposes a fuzzy logic system based on CREAM method for human reliability analysis (Hollnagel, 1998) in order to provide more sophisticated estimations of the tunnel operator's performance in safety critical situations. It is deduced that a human reliability analysis component to analyze operator performance, like the fuzzy system proposed here, is important for risk analysts. Consideration of organizational and human factors will enhance risk analysts’ studies and highlight the uncertainty related to human performance variability.     

Risk perception by offshore workers on UK oil and gas platforms

This paper reports the first investigation of risk perception by workers on offshore oil and gas installations on the UK Continental Shelf, following changes in offshore safety legislation in the wake of the Piper Alpha disaster in 1988. The Offshore Safety Case regulations (Health and Safety Executive, 1992, A Guide to the Offshore Installations (Safety Case) Regulations) put the onus on the operator to identify the major hazards and to reduce the risks to As Low As is Reasonably Practicable (ALARP). The regulations specifically state that Quantitative Risk Assessments (QRA) must be used when preparing the Safety Case. However, people do not use QRA when making everyday judgements about risk; they make subjective judgements known as risk perceptions, which are influenced by a number of different factors. This study was designed to complement the extensive QRA calculations that have already been carried out in the development of Safety Cases. The aim was to measure subjective risk perception in offshore personnel and examine how this relates to the more objective risk data available, namely accident records and QRA calculations. This paper describes the Offshore Risk Perception Questionnaire developed to collect the data and reports on UK offshore workers' perceptions of the risks associated with major and minor hazards, work tasks and other activities aboard production platforms.