ARAMIS project: a comprehensive methodology for the identification of reference accident scenarios in process industries

In the frame of the Accidental Risk Assessment Methodology for Industries (ARAMIS) project, this paper aims at presenting the work carried out in the part of the project devoted to the definition of accident scenarios. This topic is a key-point in risk assessment and serves as basis for the whole risk quantification.

The first result of the work is the building of a methodology for the identification of major accident hazards (MIMAH), which is carried out with the development of generic fault and event trees based on a typology of equipment and substances. The term “major accidents” must be understood as the worst accidents likely to occur on the equipment, assuming that no safety systems are installed.

A second methodology, called methodology for the identification of reference accident scenarios (MIRAS) takes into account the influence of safety systems on both the frequencies and possible consequences of accidents. This methodology leads to identify more realistic accident scenarios. The reference accident scenarios are chosen with the help of a tool called “risk matrix”, crossing the frequency and the consequences of accidents.

This paper presents both methodologies and an application on an ethylene oxide storage.     

Identification and classification of dynamic event tree scenarios via possibilistic clustering: Application to a steam generator tube rupture event

This paper illustrates a method to identify and classify scenarios generated in a dynamic event tree (DET) analysis. Identification and classification are carried out by means of an evolutionary possibilistic fuzzy C-means clustering algorithm which takes into account not only the final system states but also the timing of the events and the process evolution. An application is considered with regards to the scenarios generated following a steam generator tube rupture in a nuclear power plant. The scenarios are generated by the accident dynamic simulator (ADS), coupled to a RELAP code that simulates the thermo-hydraulic behavior of the plant and to an operators’ crew model, which simulates their cognitive and procedures-guided responses.A set of 60 scenarios has been generated by the ADS DET tool. The classification approach has grouped the 60 scenarios into 4 classes of dominant scenarios, one of which was not anticipated a priori but was “discovered” by the classifier. The proposed approach may be considered as a first effort towards the application of identification and classification approaches to scenarios post-processing for real-scale dynamic safety assessments.     

Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches

Safety analysis in gas process facilities is necessary to prevent unwanted events that may cause catastrophic accidents. Accident scenario analysis with probability updating is the key to dynamic safety analysis. Although conventional failure assessment techniques such as fault tree (FT) have been used effectively for this purpose, they suffer severe limitations of static structure and uncertainty handling, which are of great significance in process safety analysis. Bayesian network (BN) is an alternative technique with ample potential for application in safety analysis. BNs have a strong similarity to FTs in many respects; however, the distinct advantages making them more suitable than FTs are their ability in explicitly representing the dependencies of events, updating probabilities, and coping with uncertainties. The objective of this paper is to demonstrate the application of BNs in safety analysis of process systems. The first part of the paper shows those modeling aspects that are common between FT and BN, giving preference to BN due to its ability to update probabilities. The second part is devoted to various modeling features of BN, helping to incorporate multi-state variables, dependent failures, functional uncertainty, and expert opinion which are frequently encountered in safety analysis, but cannot be considered by FT. The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.     

Aviation safety and maintenance under major organizational changes, investigating non-existing accidents

The objective of this paper is to discuss the following questions: Do concurrent organizational changes have a direct impact on aviation maintenance and safety, if so, how can this be measured? These questions were part of the investigation carried out by the Accident Investigation Board, Norway (AIBN). The AIBN investigated whether Norwegian aviation safety had been affected due to major organizational changes between 2000 and 2004. The main concern was the reduction in safety margins and its consequences.This paper presents a summary of the techniques used and explains how they were applied in three airlines and by two offshore helicopter operators. The paper also discusses the development of safety related indicators in the aviation industry. In addition, there is a summary of the lessons learned and safety recommendations. The Norwegian Ministry of Transport has required all players in the aviation industry to follow up the findings and recommendations of the AIBN study.     

Critical factors and paths influencing construction workers’ safety risk tolerances

While workers’ safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers’ safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers’ safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers’ safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers’ unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research.     

A probabilistic quantitative risk assessment model for the long-term work zone crashes

Work zones especially long-term work zones increase traffic conflicts and cause safety problems. Proper casualty risk assessment for a work zone is of importance for both traffic safety engineers and travelers. This paper develops a novel probabilistic quantitative risk assessment (QRA) model to evaluate the casualty risk combining frequency and consequence of all accident scenarios triggered by long-term work zone crashes. The casualty risk is measured by the individual risk and societal risk. The individual risk can be interpreted as the frequency of a driver/passenger being killed or injured, and the societal risk describes the relation between frequency and the number of casualties. The proposed probabilistic QRA model consists of the estimation of work zone crash frequency, an event tree and consequence estimation models. There are seven intermediate events – age (A), crash unit (CU), vehicle type (VT), alcohol (AL), light condition (LC), crash type (CT) and severity (S) – in the event tree. Since the estimated value of probability for some intermediate event may have large uncertainty, the uncertainty can thus be characterized by a random variable. The consequence estimation model takes into account the combination effects of speed and emergency medical service response time (ERT) on the consequence of work zone crash. Finally, a numerical example based on the Southeast Michigan work zone crash data is carried out. The numerical results show that there will be a 62% decrease of individual fatality risk and 44% reduction of individual injury risk if the mean travel speed is slowed down by 20%. In addition, there will be a 5% reduction of individual fatality risk and 0.05% reduction of individual injury risk if ERT is reduced by 20%. In other words, slowing down speed is more effective than reducing ERT in the casualty risk mitigation.     

The ENEA criticality accident dosimetry system: a contribution to the 2002 international intercomparison at the SILENE reactor

The present paper summarises the activity carried out at the ENEA Radiation Protection Institute for updating the methodologies employed for the evaluation of the neutron and photon dose to the exposed workers in case of a criticality accident, in the framework of the 'International Intercomparison of Criticality Accident Dosimetry Systems' (Silène reactor, IRSN-CEA-Valduc June 2002). The evaluation of the neutron spectra and the neutron dosimetric quantities relies on activation detectors and on unfolding algorithms. Thermoluminescent detectors are employed for the gamma dose measurement. The work is aimed at accurately characterising the measurement system and, at the same time, testing the algorithms. Useful spectral information were included, based on Monte Carlo simulations, to take into account the potential accident scenarios of practical interest. All along this exercise intercomparison a particular attention was devoted to the 'traceability' of all the experimental and computational parameters and therefore, aimed at an easy treatment by the user.     

Intelligent infrastructure-based queue-end warning system for avoiding rear impacts

Accident avoidance is a very important part of enhancing road safety. The development of a queue-end warning system for highway work zones which automatically predicts queue-end location and alerts drivers so that rear-end collisions can be avoided has been described. In the absence of the widespread use of in-vehicle collision warning devices, dynamic messages about queue-end, displayed on portable variable message sign (PVMS) boards, are necessary for improving road safety. Although queues at selected locations along the road can be detected by the simple use of sensors, the changing nature of queue length would require numerous sensors to find the end of traffic queue. The reported queue-end warning system is based on a combination of sensors for detecting traffic and an artificial neural network (ANN) model-based algorithm for predicting queue-end location and issuing warning messages displayed on PVMS. Following the characterisation of work zones in terms of functional areas and geometrics, a microsimulator was calibrated and validated. Simulations were carried out next with traffic sensors and queue counter looped-in and the resulting data were used for training and validation of ANN models for queue length prediction. An automated information system was synthesised that integrates traffic sensors, ANN models, PVMS and potential links with other media. Selected results of ANN models illustrate their application in the queue-end warning system     

Safety risk assessment and management—the ESA approach

The European Space Agency ESA aims at minimizing the safety risks of their space flight projects. Hazard and risk reduction is supported by hazard analysis and probabilistic risk assessment. In hazard analysis hazardous conditions and accident scenarios are identified. Risk assessment is the probabilistic evaluation of accident scenarios and is the basis for risk management. The risk assessment method involves the determination and propagation of event probability. Expert judgement is used in a structured way. In risk management the risk assessment results are used to prioritize and optimize risk reduction efforts and to support risk acceptance evaluations.     

Environmental vulnerability assessment in the vicinity of an industrial site in the frame of ARAMIS European project

This work has been carried out in the framework of the ARAMIS project, which aims at developing a comprehensive procedure for assessing the risk level associated to an industrial site with respect to the surrounding environment. To this end, an index is defined which consists of the contribution of three terms, expressing the severity of the scenario consequences, the efficiency of the safety management and the vulnerability of the surrounding environment. The present work focuses on this last aspect concerning the determination of the vulnerability, of the area in the vicinity of an industrial site, of human, environmental (or natural) and material stakes. The applied methodology consists in identifying and quantifying the targets by the means of a geographical information system (GIS) and in assessing the contribution of each target on the basis of a multicriteria decision approach (Saaty method). The result is an operational tool allowing competent authorities, industrialists and risk experts to assess the vulnerability of the area surrounding an industrial site.     

PET包装材料中聚酯低聚物的研究进展

目的 综述PET包装材料中聚酯低聚物的研究现状,包括筛查识别、迁移检测、风险评估及政策法规。方法 PET包装材料中聚酯低聚物的筛查识别主要采用液相色谱-高分辨率质谱技术进行,结合靶向筛查和非靶向筛查手段。聚酯低聚物的迁移检测主要是测定不同条件聚酯低聚物从PET包装材料向食品模拟物的迁移。结果 部分研究开展了真实食品中低聚物的含量测定,并采用合适的方法对食品样品进行前处理。聚酯低聚物的风险评估通常是将食品/食品模拟物中的迁移量和法规中的迁移限量进行比较。对法规中未列出的低聚物,通常采用毒理学关注阈值(TTC)方法结合Cramer决策树进行风险评估。由于实验数据的缺乏,针对PET内聚酯低聚物的法规还十分有限。结论 随着PET包装材料的广泛使用,特别是新型PET包装材料的出现,有必要对PET中聚酯低聚物的潜在风险进行深入研究,以确保食品安全。应注重高分辨率质谱在聚酯低聚物筛查及迁移检测中发挥的作用,为后续风险评估提供重要数据支持。     

Use of Cognitive Work Analysis for exploration of safety management in the operation of motorcycles and scooters

The risk of accident, injury and death is disproportionately higher for motorcycle riders than for motorists. In this paper, we investigate strategies of safety management associated with operation of powered two-wheel vehicles (motorcycles and scooters). Accident prevention is most often driven by an epidemiological approach that investigates the risk factors associated with accidents. By focusing on risk factors, these types of studies fail to examine the strengths of the system in any depth. In this paper we employ an ethnographic approach structured by reference to the framework of Cognitive Work Analysis, to identify how riders of powered two-wheel vehicles manage their own safety and the safety of others. We anticipate that this research will open up a rich, relatively untapped, area for exploration of safety interventions.     

高通量筛查和安全评估结合评价乳制品包装安全风险

目的 以乳制品包装为研究对象,建立一套科学评价食品接触材料安全风险的方法,全面评价食品接触材料在接触食品过程中带来的食品安全风险。方法 采用非靶向高通量筛查检测技术全面筛查食品模拟物中的重金属和有机物,根据权威数据库和物质毒理学资料进行危害评估,参考欧盟和美国膳食暴露量计算方法进行暴露评估,结合评估结果计算风险系数,最终表征食品接触材料的安全风险。结果 抽取了市面上的塑料、金属、涂料及复合包装等不同材质的乳制品包装进行检测,检出铜、铬、锰和锡等元素,以及有意添加物（如单体、溶剂、抗氧剂、光引发剂、爽滑剂、增塑剂等）、非有意添加物质（如抗氧剂降解产物、寡聚物等）。采用暴露评估和危害评估方法分别表征检出物的膳食暴露和健康指导值,安全风险评估风险系数分布在0.007%～9.4%之间,安全风险较低。结论 建立的食品接触材料安全评价方法是一种有效评价食品接触材料安全风险的方法,该方法具有一定的通用性,企业、行业和政府部门等可用于识别食品接触材料的安全风险,为减少和排除安全风险提供科学依据。     

The german precursor study—methodology and insights

Probabilistic Safety Assessment (PSA) yields a systematic and quantitative prediction of possible accident scenarios at technical installations on the basis of data gained from the past experience on similar technical installations. Precursor studies are performed in order to make operational experience, as far as possible, available for support of PSAs. An Accident Sequence Precursor in a Nuclear Power Plant (NPP) is defined as an observed event scenario which could result, in coincidence with additional postulated events, in a potential severe core damage accident. In this paper, the methodology and the insights of the plant-specific German Precursor Study are explained in detail. As the results have demonstrated, the Precursor methodology is applicable for ranking of the safety significance of the observed events and for trending the plant risk level (described by the frequency of potential severe core damage accidents) versus operating time.     

Combining task analysis and fault tree analysis for accident and incident analysis: A case study from Bulgaria

Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident – the flooding of the plant's basement – was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.     

Numerical investigation of structural crash response of thin-walled structures on soft soil

Accident statistics show that although the certification of aircraft structures is based on crash scenarios on hard or rigid surfaces, in reality most of the crash cases occur on soft soil or water. Therefore a structure which is designed for hard surfaces may not be safe enough for a possible crash scenario on water or soft soil. Finite element method (FEM) has been used in several numerical investigations and promising results were obtained. However, since soil is a granular medium this work aims at numerical modeling of the experimentally observed soil behavior using particle-based numerical technique. In this work numerical simulations of the crash tests on idealized cones and hemispheres were used to validate the models and compare FEM-based models with particle-based models. The results of numerical simulations were compared with quasi-static and dynamic test results conducted on coarse sand sample at the Deutsches Zentrum fur Luft- und Raumfahrt e.V (DLR). After obtaining a stable and accurate particle-based numerical model for the soft soil the crash performance of deformable metallic energy absorbers on soft soil ground was investigated and compared with test data and numerical investigations of rigid ground impacts.     

基于FTA模型的荔枝冷藏运输环节风险分析

目的解决荔枝冷藏运输环节中安全风险识别及定性分析的难题。方法基于因素空间及故障树分析模型(FTA),分析荔枝冷链运输环节的安全事件集、空间结构(工位)集和简约因素集,建立荔枝冷藏运输环节风险因素关系矩阵,通过矩阵运算获取不同空间结构下荔枝运输安全事故发生的基本事件。结果根据运算求解结果,构建荔枝运输环节的故障树模型,获取了运输环节故障树的最小割集。荔枝冷藏运输事故最小割集数为13个,并分析了各个基本事件的结构重要度。结论通过研究最小割集及事件的结构重要度,进行荔枝冷链运输环节的安全分析,并提出了促进现场安全管理的对策及建议。     

Plant functional modelling as a basis for assessing the impact of management on plant safety

A major objective of the present work is to provide means for representing a chemical process plant as a socio-technical system, so as to allow hazard identification at a high level in order to identify major targets for safety development. The main phases of the methodology are: (1) preparation of a plant functional model where a set of plant functions describes coherently hardware, software, operations, work organization and other safety related aspects. The basic principle is that any aspect of the plant can be represented by an object based upon an Intent and associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. (2) Plant level hazard identification based on keywords/checklists and the functional model. (3) Development of incident scenarios and selection of hazardous situation with different safety characteristics. (4) Evaluation of the impact of management on plant safety through interviews. (5) Identification of safety critical ways of action in the management system, i.e. identification of possible error- and violation-producing conditions.     

Symptom based diagnostic system for nuclear power plant operations using artificial neural networks

Nuclear power plant experiences a number of transients during its operations. These transients may be due to equipment failure, malfunctioning of process systems and unavailability of safety systems. In such a situation, the plant may result into an abnormal state which is undesired. In case of an undesired plant condition generally known as an initiating event (IE), the operator has to carry out diagnostic and corrective actions. The operator's response may be too late to mitigate or minimize the negative consequences in such scenarios. The objective of this work is to develop an operator support system based on artificial neural networks that will assist the operator to identify the IEs at the earliest stages of their developments. These abnormal plant conditions must be diagnosed and identified through the process instrument readings. A symptom based diagnostic system has been developed to investigate the IEs. The event identification is carried out by using resilient back propagation neural network algorithm. Whenever an event is detected, the system will display the necessary operator actions in addition to the type of IE. The system will also show the graphical trend of relevant parameters. The developed system is able to identify the eight IEs of Narora Atomic Power Station. This paper describes the features of the diagnostic system taking one of the IEs as a case study.     

A "worst case" methodology for obtaining a rough but rapid indication of the societal risk from a major accident hazard installation

This paper describes a methodology developed to provide a rough but rapid indication of the magnitude of the societal risks at and in the vicinity of a major accident hazard installation. It is intended to be used by the UK Health & Safety Executive (HSE) as a first screening tool when examining safety reports submitted under The Control of Major Accident Hazards (COMAH) Regulations 1999. These are the Regulations which implement in the UK the major aspects of Council Directive 96/82/EC, the "Seveso II" Directive. Within the methodology a new weighted risk integral parameter is defined, suitable for comparison with criteria, and its value calculated. The paper includes examples to illustrate the use of the methodology.