Resilience assessment of chemical industrial areas during Natech-related cascading multi-hazards

In chemical industrial areas, technological accidents triggered by natural events (Natech events) may escalate. Complex cascading multi-hazard scenarios with high uncertainties may be caused. Resilience is an essential property of a system to withstand and recover from disruptive events. The present study focuses on the change of the resilience level due to (possible) interactions between cascading hazards, chemical installations and safety barriers during the dynamic evolution of fire escalations triggered by a natural hazard (certain cascading multi-hazard scenarios). A quantitative resilience assessment method is developed to this end. The state transition of a system facing accidents in the context of resilience is explored. Moreover, the uncertainties accompanying an accident evolution are quantified using a Dynamic Bayesian Network, allowing a detailed analysis of the system performance in different time steps. System resilience is measured as a time-dependent function with respect to the change of system performance. The applicability of the proposed methodology is demonstrated by a case study, and the effects of different configurations of safety barriers on improving resilience are discussed. The results are valuable to support disaster prevention within chemical industrial areas.     

Handling and updating uncertain information in bow-tie analysis

Bow-tie analysis is a fairly new concept in risk assessment that can describe the relationships among different risk control parameters, such as causes, hazards and consequences to mitigate the likelihood of occurrence of unwanted events in an industrial system. It also facilitates the performance of quantitative risk analysis for an unwanted event providing a detailed investigation starting from basic causes to final consequences. The credibility of quantitative evaluation of the bow-tie is still a major concern since uncertainty, due to limited or missing data, often restricts the performance of analysis. The utilization of expert knowledge often provides an alternative for such a situation. However, it comes at the cost of possible uncertainties related to incompleteness (partial ignorance), imprecision (subjectivity), and lack of consensus (if multiple expert judgments are used). Further, if the bow-tie analysis is not flexible enough to incorporate new knowledge or evidence, it may undermine the purpose of risk assessment.Fuzzy set and evidence theory are capable of characterizing the uncertainty associated with expert knowledge. To minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence are equally important in addition to addressing the uncertainties in the knowledge. This paper proposes a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis. A case study comprising a bow-tie for a typical offshore process facility has also been developed to describe the utility of this methodology in an industrial environment.     

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.     

生产车间安全管理状况的区间数模糊综合评价方法研究

针对生产车间安全管理状况评价的多维多层次性和不确定性,运用区间数模糊综合评价方法对其进行综合评价.该方法基于层次分析和模糊综合评价的基本原理,对于单因素权重、综合评价权重、各指标评分和评价集中评价等级水平均采用区间数,以使评价更符合客观实际.研究了区间数层次分析综合排序权重的确定,建立了区间数模糊综合评价模型.在得出生产车间安全管理状况综合评价区间数得分之后,引入了区间数排序可能度和区间数符合度的概念,提出了由综合评价结果得分区间数确定评价水平等级的方法.通过实例分析,验证了该评价方法的可行性.     

基于系统理论事故模型与过程的危险性分析方法

传统危险性分析方法将事故视为开始事件诱发的一连串事件所造成的不幸后果,适于处理相对简单或由物理组件构成的系统,但无法胜 任较为复杂的社会技术系统,有必要研究和探索推广性更好、更为有效的系统安全分析手段。系统理论事故模型与过程（STAMP）将安全视为系 统组件间交互的一种涌现特性,并认为事故起因除了组件失效,组件间交互失常而违背安全约束也是重要诱因。主张在系统开发、设计和运行 中通过加强控制和强化有关安全约束来预防事故。基于此,先引入了STAMP的基本概念,并介绍了其分析步骤,然后,以贴近真实的导弹拦截系 统危险性分析案例,阐述了基于STAMP的分析过程。该分析方法可为开发较高安全性水平的社会技术系统提供技术支持。     

Technical,human, and organizational factors affecting failures of firefighting systems (FSs) of atmospheric storage tanks: Providing a risk assessment approach using Fuzzy Bayesian Network (FBN) and content validity indicators

Most risk assessment methods have problems such as uncertainty, static structure, and lack of validation. Also, in most of these studies, less attention has been paid to human, managerial, and organizational issues. Therefore, this study proposes a risk assessment method based on the Fuzzy Bayesian Network (FBN) to prevent failure of firefighting systems (FFSs) in the atmospheric Storage Tanks of a Petrochemical Industry. The first stage of the study is the development of a fault tree (FT) and investigation of basic events (BEs). In this study, content validity indices and brainstorming technique were used to validate the FT structure and reduce the uncertainties of Completeness, Modeling, and Parameter. After determining the probability of basic events (BEs) by the expert team opinions and fuzzy logic, events were transmitted to the Bayesian Network (BN) and then analyzed with deductive and inductive reasoning, followed by sensitivity analysis in the GeNIe software. Finally, results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties. Also, taking account of hidden factors of events, such as organizational and managerial factors, can help managers to prevent FFSs in tanks.     

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.     

Subjective theories of organizing and learning from events

The present paper outlines potential shortcomings of analyzing events in high hazard systems. We argue that the efficiency of organizational learning within high hazard systems is at least partially undermined by the subjective theories of organizing held by their members. These subjective theories basically reflect an “engineering” understanding of “how a system and its components perform”, and are assumed to involve (social-) psychological blind spots when applied to the analysis of events. More specifically, we argue that they neglect individual motives and goals that critically drive work performance and social interactions in high hazard systems. First, we focus on the process of identifying the causes of failed organizing within the course of an event analysis. Our analysis reveals a mismatch between the basic functional assumptions of the event analyst on the motives of social actors involved in an event and on the other hand, the perspective held by the social actors themselves. Second, we discuss the process of correcting failed social system performance after events. Thereby we draw on blind spots that emerge from the direct application of technical safety principles (i.e., standardization and redundancy) to the organization of social systems. Finally, we propose some future research strategies for developing event analysis methods which are aimed at improving an organization’s learning potential.     

Software for occupational health and safety risk analysis based on a fuzzy model

Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk.     

Designing a composite indicator for road safety

This study set out to develop a composite road safety indicator for benchmarking countries’ road safety performance, which would combine the main layers of the road safety pyramid which describes the complex nature of road safety activities, performance and outcomes. Four groups of basic safety indicators were considered, which refer to: policy performance (road safety programmes), final road safety outcomes (fatality rates, scope of traffic injury), intermediate outcomes (wearing rates of seat belts, crashworthiness and composition of vehicle fleet, alcohol-impaired driving), and background characteristics of countries (motorization level, population density). The analysis used the data collected for 27 European countries. Weights based on statistical models were used to combine the basic indicators into a composite one. Principal Component Analysis and Common Factor Analysis weighting were examined. The composite indicators, estimated by several methods, enabled us to rank and group the countries according to their safety performance.The analysis revealed that the countries’ ranking based on the composite indicators is not necessarily similar to the traditional ranking of countries based on fatality rates only. Furthermore, it was observed that the indicators belonging to the final outcomes and intermediate outcomes are not uniform in their behaviour. Indicators which were found to be more consistent and influential and termed a ‘core set of basic indicators’ are recommended for future uses. The general conclusion is that the design of a composite road safety indicator in which relevant information from the different components of the road safety pyramid has been captured and weighted is realistic and meaningful. Such an indicator gives a more enriched picture of road safety than a ranking based only on fatality rates, which is the common practice at present. Grouping countries in this process is promising and seems to be preferable to simply ranking countries.     

An integrated off-on line approach for increasing stability and effectiveness of automated controlled systems based on pump dependability—case study: Offshore industry

Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standard methodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshore industry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries are considered according to OREDA classification. The approach identifies the critical pump and their fault through which the major hazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is then performed for the worst pump which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection which ultimately enhance overall operational effectiveness.     

Component joint importance measures for maintenances in submarine blowout preventer system

In order to improve the performance and maintain the interconnection components of the subsea pipeline ram blowout preventer system, the idea of importance analysis can be used to solve this problem. This paper uses an extended joint integrated importance measure to effectively analyze the characteristics of component failures of the blowout preventer system. The interaction between two components is considered to improve system performance while the failed component is being repaired. In order to facilitate subsequent maintenance and repair work, the effects of changes in different parameters on the importance value are considered. Finally, the analysis of a numerical example of the submarine pipeline ram blowout preventer system is carried out to verify the proposed method.     

Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.     

Fuzzy fault tree analysis for fire and explosion of crude oil tanks

Crude oil tank fire and explosion (COTFE) is the most frequent type of accident in petroleum refineries, oil terminals or storage which often results in human fatality, environment pollution and economic loss. In this paper, with fault tree qualitative analysis technique, various potential causes of the COTFE are identified and a COTFE fault tree is constructed. Conventional fault tree quantitative analysis calculates the occurrence probability of the COTFE using exact probability data of the basic events. However, it is often very difficult to obtain corresponding precise data and information in advance due to insufficient data, changing environment or new components. Fuzzy set theory has been proven to be effective on such uncertain problems. Hence, this article investigates a hybrid approach of fuzzy set theory and fault tree analysis to quantify the COTFE fault tree in fuzzy environment and evaluate the COTFE occurrence probability. Further, importance analysis for the COTFE fault tree, including the Fussell–Vesely importance measure of basic events and the cut sets importance measure, is performed to help identifying the weak links of the crude oil tank system that will provide the most cost-effective mitigation. Also, a case study and analysis is provided to testify the proposed method.     

航运公司安全管理能力聚权分级模型

为了更好对航运公司安全管理工作摸底排查,采取针对性措施监管航运公司安全营运,需要对安全管理能力进行分类分级评价。基于表征航运公司安全管理能力的分级指标体系,建立安全管理能力分级评价模型。基于熵权和变异系数法的赋权方法,利用α系数检验两种客观赋权法的信度,提出聚合权重并建立安全管理能力的物元分级模型。利用多家航运公司数据确定分级指标的权重,对典型公司分级和评分。结果表明,提出的模型能合理反映各公司的安全管理能力,并有利于主管机关进行分类管理,采取针对性措施提高监管效率改善公司安全管理能力。     

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.     

An economic evaluation framework for membrane reactor modules in the presence of uncertainty: The case for process safety investment and risk reduction

A comprehensive Net Present Value (NPV) model has been developed to demonstrate the economic advantages of process safety and risk reduction investments on Pd/Au-based membrane reactors. In particular, the economic viability of Pd/Au-based membrane reactor modules incorporated into Integrated Gasification Combined Cycle (IGCC) plants is evaluated within the aforementioned framework by pro-actively following sound process safety design principles. Sources of irreducible uncertainty (market, technological, operational) as well as safety risk are explicitly recognized, such as the Pd/Au prices, membrane life-time and loss in the power plant capacity factor due to possible accidents. The effect of the above uncertainty drivers on the membrane module cost along with production disruption and associated revenue losses is elucidated using Monte-Carlo simulation techniques that enable the propagation of the above uncertain inputs through the NPV-model, and therefore, generate a more realistic distribution of the process system's value rather than a single-point/estimate that overlooks these uncertainties. Pre-investment on risk reducing measures, such as spare safety relief systems (cautionary redundancy) for membrane reactor modules operating at high pressures (e.g. 50 atm), is shown to be economically more attractive than cases where analogous safety measures are not implemented. Since accidents and possibly catastrophic events do happen in an uncertain world, additional investment on safety measures could ensure a safer and more profitable operation of the process system under consideration giving credence to the thesis that process safety investments may result in enhanced techno-economic performance in the presence of irreducible uncertainties.     

突发事件下城市关键基础设施应急策略研究

城市关键基础设施系统由于相互之间存在的各种关联关系而形成了一个相互依存的网络化复杂系统,在突发事件下,一个单一系统功能的失效或部分功能丧失会导致与其相关联的系统产生级联失效现象。针对关键基础设施系统间相互耦合的特性,建立了突发事件下多层系统之间的供需关系网络数学模型,提出当某单一系统的节点失效后,通过分析事故链,利用与之耦合系统的供需关联关系,进行紧急状态下的备用资源调度应急策略。研究表明,基于城市关键基础设施系统之间的供需关联关系来进行资源调度的应急决策能够有效地突破传统方法中以调用备用资源为主的单系统内部优化应急策略的局限性,更有效地优化整个网络资源以降低系统总体损失。     

基于企业职业伤害风险和违法处罚的分级监察模型研究

对企业实施分级监察的基础是企业监察级别的确定。分级监察是以“风险优先”为基本的原则风险管理思想。本文在对我国现有的安全生产法规政策和安监部门的部分执法文书以及企业违法处罚情况进行分析总结的基础上,建立了企业违法处罚情况的量化模型,并以企业职业伤害风险和企业违法处罚结果为影响因素,建立了二元分级监察模型。运用所建立的模型对辽宁省某市的159家调研企业的监察级别进行了划分,并对分级结果进行了简要分析。     

Economic assessment of inherently safe membrane reactor technology options integrated into IGCC power plants

Pd/alloy-based (Pd/Cu, Pd/Au) membrane reactors embedded into Integrated Gasification Combined Cycle (IGCC) plants (IGCC-MR) enable the storage and/or use of the energy value of H₂ to produce electricity while the CO₂ enriched retentate exit stream becomes particularly suitable for high pressure CO₂ capture-sequestration. There is undoubtedly a lack of operating experience associated with IGCC-MR plants, and therefore, sound process intensification principles/practices should be followed not only to enhance process system performance but also to ensure process safety and economic feasibility of an IGCC-MR plant. Motivated by the above considerations, a comprehensive process economic assessment framework for an inherently safe membrane Pd/alloy-based reactor integrated into an IGCC plant is proposed. In particular, a detailed Net Present Value (NPV) model has been developed to evaluate the economic viability of an IGCC-MR plant where the membrane reactor module design conforms to basic inherent safety principles. Sources of irreducible uncertainty (market, regulatory and technological) are explicitly recognized such as the power plant capacity factor, Pd price, membrane life time and CO₂-taxes due to future regulatory action/policies. The effect of the above uncertainty drivers on the project's/plant's value is studied through Monte Carlo methods resulting in detailed NPV-distribution and process economic outcome profiles. The simulation results derived suggest that in the presence of (operational, economic and regulatory) uncertainties, inherently safe membrane reactor technology options integrated into IGCC plants could become economically viable. In particular, comparatively more attractive NPV distribution profiles are obtained when concrete safety risk-reducing measures are taken into account through pre-investment in process safety (equipment).