Mathematical methods for application of experimental adiabatic data – An update and extension

The paper represents some results of comparative analysis of the methods used for processing and interpreting data of adiabatic calorimetry as well as applying it to practical situations. Specifically two approaches are compared – approximate method based on evaluation of simplified kinetics and a more comprehensive, simulation-based method that utilizes the evaluation of more detailed kinetic models.The analysis is focused on two important types of data processing – correction of experimental results on thermal inertia (phi-factor correction) and estimation of adiabatic time to maximum rate (TMR).The most widely cited method for phi-factor correction is considered and its improvement is proposed to enable more precise prediction of the adiabatic time scale. A procedure for phi-factor correction of pressure response is also proposed. The limitations of this enhanced Fisher's method are discussed by comparison with simulation-based method. All the illustrative materials are based on real examples.As an example of application, the simplified method will be used to predict TMR and its limitations will be discussed.     

Learning from incidents – A method for assessing the effectiveness of the learning cycle

This paper describes a method for assessing the effectiveness in the steps of the learning cycle: the 1st loop with reporting – analysis – decision – implementation – follow-up, and the 2nd loop on an aggregated basis. For each step, the dimensions considered the most relevant for the learning process (scope, quality, timing and information distribution) and for each dimension the most relevant aspects (e.g. completeness and detail) were defined. A method for a semi-quantitative assessment of the effectiveness of the learning cycle was developed using these dimensions and aspects and scales for rating. The method will give clear indications of areas for improvement when applied. The results of the method can also be used for correlation with other safety parameters, e.g. results from safety audits and safety climate inquiries. The method is intended to be used on a sample of the broad range of incidents normally seen in process industry companies. The method was tested on a two-year incident reporting material from six companies from various types of process industries. It was found that the method and the tools worked very well in practice. The results gave interesting insights into the effectiveness of learning from the incidents.     

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.     

Optimization of HSE in maintenance activities by integration of continuous improvement cycle and fuzzy multivariate approach: A gas refinery

Gas refineries have been continuously focusing on Health, Safety and Environment programs to improve maintenance activities. Several researches have studied on this area with different analysis methods. This study presents an integrated approach for optimization of factors contributing to the implementation of Health, Safety and Environment (HSE) in maintenance activities. HSE managers in each sector answered standard questionnaire whit respect to HES. The methodology is based on fuzzy data envelopment analysis (FDEA) and Deming's continuous improvement cycle. Also, this method is used to rank the relevant performance efficiencies in certain and uncertain conditions of each HSE sectors whit considering HSE in maintenance activities. It corresponds and integrates its registered HSE-MS with OHSAS 18001:2007 and ISO 14001:2004 to evaluate multiple inputs and outputs of over 36 subsidiary HSE divisions with parallel mission and objectives simultaneously. Also, it determines efficient target indices and could assure continuous improvement in the organization. This is the first study that introduces an integrated approach to improve HSE management programs in a gas refinery by a robust and continuous improvement approach.     

Conceptual compression discussion on a multi-linear (FTA) and systematic (FRAM) method in an offshore operation’s accident modeling

Risk assessment can be classified into two broad categories: traditional and modern. This paper is aimed at contrasting the functional resonance analysis method (FRAM) as a modern approach with the fault tree analysis (FTA) as a traditional method, regarding assessing the risks of a complex system. Applied methodology by which the risk assessment is carried out, is presented in each approach. Also, FRAM network is executed with regard to nonlinear interaction of human and organizational levels to assess the safety of technological systems. The methodology is implemented for lifting structures deep offshore. The main finding of this paper is that the combined application of FTA and FRAM during risk assessment, could provide complementary perspectives and may contribute to a more comprehensive understanding of an incident. Finally, it is shown that coupling a FRAM network with a suitable quantitative method will result in a plausible outcome for a predefined accident scenario.     

考虑非独立保护层影响的LOPA改进策略研究

针对LOPA在识别保护层方面的局限性,通过考虑非独立保护层的影响,将非独立保护层分为不满足有效性与不满足独立性2类进行分析,针对不同类型的非独立保护层分别应用引入削减系数以及与故障树分析（FTA）集成的方法对传统LOPA进行改进,并结合具体案例验证其适用性。研究结果表明:改进方法的计算结果较传统方法计算结果降低了1个数量级,避免了传统方法过于保守的评价结果;通过对传统方法的改进,克服了LOPA在识别保护层方面以及场景频率计算方面的局限性,有助于拓展其使用范围。     

Integrating major accidents hazard into occupational risk assessment: An index approach

Major Accident Hazard (MAH) and Occupational Safety and Health (OSH) are two separated topics in both industrial practice and legislation; recently, interest is increasing toward an integrated risk assessment mainly forced by the tendency to a more efficient safety management system. The present study proposes a semi-quantitative approach to integrate MAH in OSH risk assessment. The two risk types are characterized by opposite features: the OSH analysis is usually task-based and focused on job profiles, while the MAH analysis is space-based and focused on plant characteristics. The basic idea of the proposed approach is to merge spatial information and job profile features in order to improve OSH assessment; thus, a risk index derived by the recent standard ISO 12100 (2010) has been adapted. In detail, the proposed index combines exposure times of each worker at each plant unit – derived from the OSH analysis – with damage areas derived from MAH analysis allowing a quantitative assessment of the MAH risk level for each individual job profile. The model has been tested in a large petrochemical plant; several hypotheses have been developed in order to validate the model. Results have showed the potentiality of the proposed approach in providing a common and coherent representation of both MAH and OSH risks, according to job profiles and plant units.     

Worker-fatigue contributing to workplace incidents in New Zealand Forestry

ProblemReports of incidents in dangerous work environments can be analysed to identify common hazards, in turn aiding in the prevention of future accidents. Whilst studies exist that do this, most focus on causes that involve physical risks. In this paper we propose an alternative approach, and illustrate causes of forestry incidents from the perspective of worker-failure and fatigue. Method This paper outlines the analysis of eight years’ worth of New Zealand forestry incident data, with a focus on the cause of, and time that, incidents occur. Results This has resulted in two main findings. First, 70% of incidents can be attributed, at least in part, to worker-failures. Second, 78% of worker-failure based causes show indications of fatigue. This indicates that a significant number of forestry incidents are caused by worker-fatigue. Finally, this dataset showed inconsistencies in data quality, similar to those that exist in other datasets. This did not affect our analysis. However, these types of errors have the potential to affect the data quality in the national reporting system. Impact on industry The results from this study will be used in a larger project on detecting fatigue in forestry workers for injury and incident prevention. It is also our hope that other researchers may find these results of interest for further fatigue prevention research in hazardous industries.     

SESAR safety decision-making: Lessons from environmental,nuclear and defense modeling

SESAR, the ‘Single European Sky Air traffic Research’ program, envisages radical changes for European Air Traffic Management (ATM). It integrates and implements new technologies and information processing. This paper examines the safety decision-making in the implementation of SESAR projects. SESAR poses new safety problems because it adopts new paradigms for ATM safety – what lessons are there from environmental, nuclear and defense modeling? These disciplines have also had to confront the limitations of modeling the rates of rare and damaging – even catastrophic – events. A major conceptual change in SESAR is that of automated separation assurance systems. Some existing responsibilities transfer from the controller – either to the pilot or to computer systems – in a progressively phased approach. The major problem for SESAR safety validation is that mixed equipage/operations within a common airspace potentially generate new and different safety issues regarding the validation of safety predictions. A potential way forward uses high-fidelity Human In The Loop Simulations (HITLS) to generate confidence in the resilience of the ATM system. The focus changes from proving safety, i.e. through traditional kinds of validation processes, to extensive resilience testing using these simulations. The aim would be to test how resilient the system is to seeded errors, penetration testing, and crash/stress testing. This would be a high cost process because of the large investments required and the need for long sequences of testing. However, these demanding processes can provide ‘justified belief’ to the decision-maker that the changed ATM system is acceptably safe.     

Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network

Among the various techniques used for safety analysis of process systems, bow-tie (BT) analysis is becoming a popular technique as it represents an accident scenario from causes to effects. However, the BT application in the dynamic safety analysis is limited due to the static nature of its components, i.e. fault tree and event tree. It is therefore difficult in BT to take accident precursors into account to update the probability of events and the consequent risk. Also, BT is unable to represent conditional dependency. Event dependency is common among primary events and safety barriers. The current paper illustrates how Bayesian network (BN) helps to overcome these limitations. It has also been shown that BN can be used in dynamic safety analysis of a wide range of accident scenarios due to its flexible structure. This paper also introduces the application of probability adapting in dynamic safety analysis rather than probability updating. A case study from the U.S. Chemical Safety Board has been used to illustrate the application of both BT and BN techniques, with a comparison of the results from each technique.     

Totalitarian loss of responsibility in an explosives production plant

One of the largest accidents of communist era in former Czechoslovakia occurred in an explosion production plant in Semtín 26 years ago. Original analysis of the accident concentrated on technical causes and did not look for root causes. Additional root cause analysis showed that the plant’s safety management had been decaying and that other layers of causes had lain under the root causes. According to deeper analysis in this article, the event represents an accident that shows the decay of safety management after decades of dispersed ownership in a totalitarian society. We attempt to understand the mechanisms which led the plant into such a state. Their substantial aspects are identified and a model of the development of managers’ attitude to safety is constructed. The analysis points at the replacement of ideal managers’ behavior in safety management by distorted behavior which is here termed the totalitarian loss of responsibility. Presumably, more accidents with similar backgrounds can be identified in totalitarian surroundings. The analysis shows that the Chernobyl disaster can be considered one of them. Tools that helped deepen the analysis are based on the STAMP model and on the archetypes of safety. The analysis integrates various ideas and models into a single procedure based on the original representation of assumptions about the structure of safety management.     

What can be learned from incidents in chemistry labs

Students of chemistry should achieve certain safety competencies. Among other things they should be able to learn from undesirable events that happen during their work. In order to facilitate this we decided to analyze, together with our students, the specific causes of a few undesirable events which have happened in our school laboratories. We applied an approach based on root cause analysis and on the classification of four levels of safety assurance. Our examples showed the effectiveness of this approach, leading us at once not only to the identification of errors committed by students, but to those of teachers as well. This enabled us to compile a set of recommendations for the possible prevention of such incidents. Above all, our analysis strongly reinforced the conviction that this approach – learning from actual incidents – is more than just a cause analysis technique. It is a pattern of behavior, a cultural pattern. A technique may be analyzed and taught, but the most effective way to pass on a behavioral pattern is to set an example. The best way to show students how to learn from their own errors is for teachers to demonstrate how they have learned from their own experiences. Work in chemistry labs provides ample opportunities for this.     

Risk management of cost consequences in natural gas transmission and distribution infrastructures

A critical aspect of risk management in energy systems is minimizing pipeline incidents that can potentially affect life, property and economic well-being. Risk measures and scenarios are developed in this paper in order to better understand how consequences of pipeline failures are linked to causes and other incident characteristics. An important risk measure for decision-makers in this field is the association between incident cause and cost consequences. Data from the Office of Pipeline Safety (OPS) on natural gas transmission and distribution pipeline incidents are used to analyze the association between various characteristics of the incidents and product loss cost and property damage cost. The data for natural gas transmission incidents are for the period 2002 through May 2009 and include 959 incidents. In the case of natural gas distribution incidents the data include 823 incidents that took place during the period 2004 through May 2009. A two-step approach is used in the statistical analyses to model the consequences and the costs associated with pipeline incidents. In the first step the probability that there is a nonzero consequence associated with an incident is estimated as a function of the characteristics of the incident. In the second step the magnitudes of the consequence measures, given that there is a nonzero outcome, are evaluated as a function of the characteristics of the incidents. It is found that the important characteristics of an incident for risk management can be quite different depending on whether the incident involves a transmission or distribution pipeline, and the type of cost consequence being modeled. The application of this methodology could allow decision-makers in the energy industry to construct scenarios to gain a better understanding of how cost consequence measures vary depending on factors such as incident cause and incident type.     

事故致因理论的研究与应用简评

阐明事故致因理论的重要性和应用情况对于促进其发展、应用及提高事故预防效果十分重要。通过分析国内外的重要观点得知,安全科学是事故预防的科学,事故致因理论是发现事故原因、有效预防事故的工具,当然具有特别的重要性;但事故致因理论研究在我国开展较晚,所以目前的研究与应用并不充分。综合以往文献,给出了事故致因理论的实质性科学含义是事故的原因定义、原因间、原因与事故间的逻辑关系,它们可形象地综合表达为事故致因模型,其获取过程中不可或缺的方法是对以往事故案例的原因分析;通过观察安全管理实务认识到,社会组织要有效管理其安全健康和环保业务,选择一种事故致因模型作为总体思路且连续运转,十分必要。     

Migrating an incident reporting system to a CCPS process safety metrics model

A major chemical company established a formal incident investigation and reporting system several years ago. The original system focused heavily on worker-related injuries, illnesses, and near-misses and was used primarily to track statistics reportable to the Occupational Safety and Health Administration (OSHA). This Occupational Injury and Illness (OII) approach has been recognized to be an ineffective tool for measuring, predicting, and preventing process safety incidents. The Center for Chemical Process Safety (CCPS) recently published guidelines on how to establish safety metrics for the measurement and reduction of process safety incidents. The process safety metrics approach relies upon leading and lagging metrics to improve organization process safety. This paper is a case study of the analysis of one organization’s incident database, which represents approximately five years of data from over a dozen facilities. The aim of this investigation was to extract useful process safety metrics from the incident investigation and reporting system, which would be pertinent to the types of process units and process functions at these facilities. This paper will discuss the approach taken to extract process incident information from an OII-based database and present the difficulties of performing an analysis on such a database. This paper provides guidance on how to migrate an existing OII-based reporting system to a program that includes process safety metrics in accordance with industry best practices.     

一种基于层次分析法的危险化学品源安全评价综合模型

危险化学品源的安全评价是安全生产管理中的一项重要内容.目前用于危险化学品源安全评价与分级的常用方法有后果分析法、道指数法、蒙德指数法以及使用临界系数判别重大危险源的方法等.在实际应用中,单独使用某一方法时,由于存在各种片面性问题而得不到满意的评价结果; 几种方法同时使用时,其评价指标、评价结果以及结果的形式又会互相冲突.为解决上述问题,建立了基于层次分析法的综合评价模型.首先,根据安全评价要求构建3层次的评价体系,在各层次中构造判断矩阵,并计算4种常用方法相对综合评价模型的置信度; 其次,对各方法统一危险分级标准,均采用危险分数划定危险级别,并取各危险分数的加权平均值--综合危险分数作为综合评价模型下的危险源分级标准.采用综合评价模型可消除单一方法进行评价时的片面性和偏差,同时,评价结果的一致化使得判断危险化学品源的危险级别以及由此采取相应级别的管理措施成为可能,将更有利于实际安全生产管理指导.     

Uncertainty aspects in process safety analysis

Uncertainties of input data as well as of simulation models used in process safety analysis (PSA) are key issues in the application of risk analysis results. Mostly, it is connected with an incomplete and uncertain identification of representative accident scenario (RAS) and other vague and ambiguous information required for the assessment of particular elements of risk, especially for determination of frequency as well as severity of the consequences of RAS. The authors discuss and present the sources and types of uncertainties encountered in PSA and also methods to deal with them. There are different approaches to improve such analysis including sensitivity analysis, expert method, statistics and fuzzy logic. Statistical approach uses probability distribution of the input data and fuzzy logic approach uses fuzzy sets. This paper undertakes the fuzzy approach and presents a proposal for fuzzy risk assessment. It consists of a combination of traditional part, where methods within the process hazard analysis (PHA) are used, and “fuzzy part”, applied quantitatively, where fuzzy logic system (FLS) is involved. It concerns frequency, severity of the consequences of RAS and risk evaluation. In addition, a new element called risk correction index (RCI) is introduced to take into account uncertainty concerned with the identification of RAS. The preliminary tests confirmed that the final results on risk index are more precisely and realistically determined.     

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.     

Risk analysis system for the transport of hazardous materials

IntroductionIn this paper, a literature study on risk analysis systems for the transport of hazardous materials was conducted.ResultsThe insights that resulted from this literature review have led to the development of a refined approach to map the risk of hazmat transport in Flanders based on historical accident data. The proposed framework allows setting up an overall risk map for hazmat transport by different transport modes. Additionally, a methodology to calculate a local accident risk, which takes local infrastructure parameters and accident data into account, is being introduced. In the presented framework one of the general principles is that the risk of a catastrophic hazmat incident can be divided into two parts, which can both be validated on the basis of accident data: (a) the calculation of the general probability of the occurrence of an accident based on international accident data of transport of hazardous materials – this is the basis for the global risk map, and (b) the calculation of the local probability of the occurrence of an accident based on accident data and infrastructure parameters of the complete available freight transport in Flanders – this is the basis for the local risk map. The ratio between these two results in a locality parameter, which represents the local specific circumstances that can lead to an accident.ConclusionsThis evaluation framework makes it possible to estimate the risks of hazmat transport along a specific route for transport by road, rail, inland navigation and even pipelines.     

高危行业B类安全文化关键要素研究

为加强安全文化研究成果对企业实践的指导作用,对研究成果的研究样本、思路到方法进行分析,找出在安全文化关键要素研究方面没有得出一致性结论的原因,并按对安全文化内涵理解的不同将其归纳为A,B两大类。采用文本资料分析法,对高危行业的经验文本资料进行定性研究,得到高危行业B类安全文化的7个维度和29个题项要素,最终得出B类安全文化要素关系模型。从实践和理论的角度,支持了安全文化是"有影响安全业绩的、存在于企业行动、管理政策、作业过程中的企业的安全理念、安全态度"的观点。