Safety analysis approach based on thermodynamic and chemical reactions modelling

Safety analysis of nuclear and chemical/petrochemical facilities is the systematic process that is carried out throughout the design process to ensure that all the relevant safety requirements are met by the proposed design of the plant. Safety analysis should incorporate both deterministic and probabilistic approaches. These approaches have been shown to complement each other and both should be used in the decision making process on the safety and ability of the plant to be licensed.This paper deals with the deterministic safety approach in order to distill the experience of nuclear and chemical/petrochemical protection engineering through a safety analysis approach aiming at analysis of chemically reacting processes including thermodynamic and chemical reactions modelling that are present in both industries. For instance, there are some similarities between the Bhopal disaster and Three Mile Island-Fukushima-like H₂ deflagration-detonation scenarios in nuclear containments. The phenomenology is similar in that the temperature and the pressure caused by exothermic reactions had increased dramatically leading to a loss of containment.The study aims to translate and adapt to general chemically reacting modelling, major features of the equivalent analysis inside the nuclear containments. Compartment containment for H₂ deflagrations has been translated and adapted, with fixed tools, to the methyl-isocyanate storage tank 610 of the Bhopal plant.     

Rail ruminations for process safety improvement

Process safety practices have undergone multiple refinements over the past few decades, but major accidents continue to occur. Most organizations strive to improve performance by strengthening existing methods or by adopting new and/or different approaches. Central to these continual improvement efforts is the practice of applying lessons learned as a means to drive out potential risk exposures. Often, lessons learned may be transferred from other industries; indeed, high-performing organizations regularly benchmark practices outside of their immediate industry.In pursuit of continual process safety improvement, this paper examines risk management practices in the Rail Industry, and explores how methods intended for managing passenger and public rail safety may be transferred to drive continual improvement of process safety. Rail safety has its roots in engineered safety solutions; modern practices have additionally embraced the human aspects of safety performance. A selection of approaches for rail safety assessment and risk management are described in three areas considered fundamental to safety management: management of systems, management of technology, and management of human elements. In light of these examples, the authors provide views regarding how the field of process safety management may leverage the rail experience.     

Use of safety barriers in operational safety decision making

Operational personnel in complex hazardous industries are regularly called upon to make decisions that balance the production and safety objectives of their organisation. Regulations and industry standards focus on defining and complying with operating limits of various kinds as the primary method of achieving the right balance. Such limits remove the need in many cases for in-the-moment judgements about safety and production priorities.Focussing solely on the compliance with a pre-defined envelope underestimates the direct contribution to safety from operational managers based on their professional judgement. Research in a chemical plant, a nuclear power station and an air navigation service provider has identified a “line in the sand” approach taken by experienced operating personnel when abnormal situations arise. In developing these situation-specific self-imposed limits, operational managers focus on the status of safety barriers, rather than considering risk from first principles. This approach could form the basis of a new procedure, which lays out the process to be followed in determining how best to proceed (similar to job safety analysis or permit to work). This would acknowledge that such decisions are necessary, assist operational personnel in making better choices and open such decisions to appropriate audit and scrutiny.     

Layer of Protection Analysis – Quantifying human performance in initiating events and independent protection layers

Layer of Protection Analysis (LOPA) is widely used within the process industries as a simplified method to address risks and determine the sufficiency of protection layers. LOPA brings a consistent approach with added objectivity and a greater degree of understanding of the scenarios and risks as compared to purely qualitative studies such as Process Hazard Analyses. LOPA can be used to address a wide range of risk issues and serves as a highly effective aid to decision making.Incorporation of human performance within LOPA is recognized as an important, though often challenging, aspect of the analysis. The human role in potential initiating events or within human independent protection layers is important throughout the process industries, and becomes even more critical for batch processing facilities and in non-routine operations. The human role is key to process safety and the control of risks, necessitating the inclusion and quantification of human actions in independent protection layers for most companies. Human activities as potential initiating events and human performance within independent protection layers are reviewed and methods for quantification outlined. An extension into Human Reliability Analysis (HRA) is provided, including methods to develop Human Error Probabilities specific to the process safety culture and operations at a given plant site.     

Dynamic management of human error to reduce total risk

Safety management in companies at the limit of risk criteria must be implemented in order to survive in the very aggressive and competitive environment of modern society. It implies that the risk in process industries is crossing the limit of safe practices. Most major accidents consist of human errors and mechanical component failures, and cannot be explained by a stochastic coincidence of independent events. This work focuses on the coincidence of human error and mechanical failure to introduce a concept of dynamic management of human error. By the dynamic management of human error during a short period, when a mechanical component is temporarily unavailable during periodic testing or maintenance, the probability of a major accident may be reduced significantly without additional investment on improving safety. For the periodically-tested standby component, the majority of total average unavailability of the component may be recognized by operators or workers as well as maintenance mechanics. During this short period, an appropriate dynamic management of human error for improving human performance temporarily may be very effective in reducing total risk in industries. The dynamic management of human error may be a useful method to prevent loss effectively in the process industries     

基于风险指引的核电厂设计改进评价研究

核电厂概率安全评价(PSA)可以论证核电厂的风险满足安全目标,也是对运行核电厂进行风险管理的有效工具,例如核电厂的在役检查、安全分级、技术规格书优化等。核电厂的风险指引管理是在确定论的基础上,充分利用概率安全评价的结果进行风险影响评价,以此来论证决策的合理性。核电厂的重要设计改进通常基于传统的工程分析结果,没有分析其对核电厂整体风险的影响。重点探讨风险指引决策的基本原则以及方法,以核电厂设计改进实例探讨如何在分析时引入风险指引方法,并提出相关建议。     

建筑工程安全的风险识别及评价方法研究

建筑项目安全风险管理主要分为 3个阶段进行 :风险识别阶段 ;风险评价阶段 ;风险决策阶段。笔者主要对整个建筑工程项目建设过程中安全风险管理的前两阶段进行了探讨 ;在分清不同阶段的风险管理职责的基础上 ,提出了应用性较强的“子系统风险管理模型” ;进行了相关的实例分析 ,证明了其在风险的识别和评价阶段的适用性 ;并在风险评价方法中 ,合理制定了对不希望发生事件的发生概率和结果严重度的评价标准 ,为建筑安全风险的科学评价提供了依据     

Modelling of BP Texas City refinery accident using dynamic risk assessment approach

Process industries involve handling of hazardous substances which on release may potentially cause catastrophic consequences in terms of assets lost, human fatalities or injuries and loss of public confidence of the company. In spite of using endless end-of-the-pipe safety systems, tragic accidents such as BP Texas City refinery still occur. One of the main reasons of such rare but catastrophic events is lack of effective monitoring and modelling approaches that provide early warnings and help to prevent such event. To develop a predictive model one has to rely on past occurrence data, as such events are rare, enough data are usually not available to better understand and model such behavior. In such situations, it is advisable to use near misses and incident data to predict system performance and estimate accident likelihood. This paper is an attempt to demonstrate testing and validation of one such approach, dynamic risk assessment, using data from the BP Texas City refinery incident.Dynamic risk assessment is a novel approach which integrates Bayesian failure updating mechanism with the consequence assessment. The implementation of this methodology to the BP Texas City incident proves that the approach has the ability to learn from near misses, incident, past accidents and predict event occurrence likelihood in the next time interval.     

Risk informed optimization of a hazardous material multi-periodic transportation model

This paper presents a systematic framework toward the development of a Transportation Model for Hazardous Materials (HazMat). In practice, the proposed modeling framework is realized through an appropriate generalization of the traditional transportation network problem in the presence of safety constraints that need to be satisfied. The objective is to minimize transportation cost while reducing risks at the desired levels.In particular, the present research study identifies and evaluates different risk factors that influence the HazMat transportation network. Next, the transportation model is depicted graphically using nodes and arcs and optimal conditions are identified by solving the associated minimum cost flow network problem. The results show safety levels that help making informed decisions on choosing the optimal transportation configuration for hazardous material shipments.Within the proposed methodological context, appropriately parameterized simulation studies elucidate the effects of occurrence probabilities of the different risk events on transportation cost. Furthermore, as the appropriate management decisions must consider the effect of actions in one time period on future periods, the proposed model is structured as a multi-periodic model.Finally, the proposed methodological approach is employed to demonstrate the utility of proper analytical tools in decision making and particularly in ensuring that scientifically informed safety procedures are in place while transporting goods that can be potentially proven dangerous to the public and the surroundings.     

Using risk tolerance criteria to determine safety integrity levels for safety instrumented functions

Standards and industry guidelines for Safety Instrumented Systems (SISs) describe the use of hazard and risk analysis to determine the risk reduction required, or Safety Integrity Levels (SILs), of Safety Instrumented Functions (SIFs) with reference to hazardous events and risk tolerance criteria for them. However, significant problems are encountered when putting this approach into practice. There is ambiguity in the meaning of the term hazardous event. Notably, even though it is a key concept in the process-sector-specific SIS standard, IEC 61511/ISA 84, it is not defined in the standard. Consequently, risk tolerance criteria for hazardous events are ill-defined and, therefore, they are not the most appropriate criteria to use. Most current approaches to SIL determination use them and therefore they are flawed fundamentally.An informed decision on the tolerability of risk for a facility cannot be made by determining only the tolerability of risk for individual hazardous events. Rather, the tolerability of the cumulative risk from all hazard scenarios and their hazardous events for a facility must be determined. Such facility risk tolerance criteria are the type used by regulators. This issue applies to all per event risk tolerance criteria. Furthermore, determining the tolerability of risk for a facility based only on the risks of single events, be they hazard scenarios or hazardous events, and comparing them to risk tolerance criteria for the events is not meaningful because there is no consideration of how many such events can actually occur and, therefore, no measure of the total risk. The risks from events should be summed for a facility and compared with overall facility risk tolerance criteria.This paper describes and illustrates SIL determination using a risk model implemented within the framework of Layers of Protection Analysis (LOPA) that overcomes these problems. The approach allows the allocation of risk across companies, facilities, processes, process units, process modes, etc. to be managed easily.     

How can process safety and a risk management approach guide pandemic risk management?

The coronavirus disease (COVID-19) brought the world to a halt in March 2020. Various prediction and risk management approaches are being explored worldwide for decision making. This work adopts an advanced mechanistic model and utilizes tools for process safety to propose a framework for risk management for the current pandemic. A parameter tweaking and an artificial neural network-based parameter learning model have been developed for effective forecasting of the dynamic risk. Monte Carlo simulation was used to capture the randomness of the model parameters. A comparative analysis of the proposed methodologies has been carried out by using the susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD) model. A SEIQRD model was developed for four distinct locations: Italy, Germany, Ontario, and British Columbia. The learning-based approach resulted in better outcomes among the models tested in the present study. The layer of protection analysis is a useful framework to analyze the effect of different safety measures. This framework is used in this work to study the effect of non-pharmaceutical interventions on pandemic risk. The risk profiles suggest that a stage-wise releasing scenario is the most suitable approach with negligible resurgence. The case study provides valuable insights to practitioners in both the health sector and the process industries to implement advanced strategies for risk assessment and management. Both sectors can benefit from each other by using the mathematical models and the management tools used in each, and, more importantly, the lessons learned from crises.     

Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

Dynamic failure assessment of an ammonia storage unit: A case study

Chemical Process Industries usually contain a diverse inventory of hazardous chemicals and complex systems required to perform process operations such as storage, separation, reaction, compression etc. The complex interactions between the equipment make them vulnerable to catastrophic accidents. Risk and failure assessment provide engineers with an intuitive tool for decision making in the operation of such plants. Abnormal events and near-miss situations occur regularly during the operation of a system. Accident Sequence Precursors (ASP) can be used to demonstrate the real-time operating condition of a plant. Dynamic Failure Assessment (DFA) methodology is based on Bayesian statistical methods incorporates ASP data to revise the generic failure probabilities of the systems during its operational lifetime.In this paper, DFA methodology is applied on an ammonia storage unit in a specialized chemical industry. Ammonia is stored in cold storage tanks as liquefied gas at atmospheric pressure. These tanks are susceptible to failures due to various abnormal conditions arising due process failures.Tank failures due to three such abnormal conditions are considered. Variation of the failure probability of the safety systems is demonstrated. The authors use ASP data collected from plant specific sources and safety expert judgement. The failure probabilities of some safety systems concerned show considerable deviation from the generic values. The method helps to locate the components which have undergone more degradation over the period and hence must be paid attention to. In addition, a Bayesian predictive model has been used to predict the number of abnormal events in the next time interval. The user-friendly and intuitive nature of the tool makes it appropriate for application in safety assessment reports in process industries.     

Offshore safety case approach and formal safety assessment of ships

PROBLEM: Tragic marine and offshore accidents have caused serious consequences including loss of lives, loss of property, and damage of the environment. METHOD: A proactive, risk-based "goal setting" regime is introduced to the marine and offshore industries to increase the level of safety. DISCUSSION: To maximize marine and offshore safety, risks need to be modeled and safety-based decisions need to be made in a logical and confident way. Risk modeling and decision-making tools need to be developed and applied in a practical environment. SUMMARY: This paper describes both the offshore safety case approach and formal safety assessment of ships in detail with particular reference to the design aspects. The current practices and the latest development in safety assessment in both the marine and offshore industries are described. The relationship between the offshore safety case approach and formal ship safety assessment is described and discussed. Three examples are used to demonstrate both the offshore safety case approach and formal ship safety assessment. The study of risk criteria in marine and offshore safety assessment is carried out. The recommendations on further work required are given. IMPACT ON INDUSTRY: This paper gives safety engineers in the marine and offshore industries an overview of the offshore safety case approach and formal ship safety assessment. The significance of moving toward a risk-based "goal setting" regime is given.     

Examining the asymptote in safety progress: a literature review

Many industries are confronted by plateauing safety performance as measured by the absence of negative events – particularly lower-consequence incidents or injuries. At the same time, these industries are sometimes surprised by large fatal accidents that seem to have no connection with their understanding of the risks they faced; or with how they were measuring safety. This article reviews the safety literature to examine how both these surprises and the asymptote are linked to the very structures and practices organizations have in place to manage safety. The article finds that safety practices associated with compliance, control and quantification could be partly responsible. These can create a sense of invulnerability through safety performance close to zero; organizational resources can get deflected into unproductive or counterproductive initiatives; obsolete practices for keeping human performance within a pre-specified bandwidth are sustained; and accountability relationships can encourage suppression of the ‘bad news’ necessary to learn and improve.     

Evaluation of risk and cost using an age-dependent unavailability modelling of test and maintenance for standby components

The improvement of safety in the process industries is related to assessment and reduction of risk in a cost-effective manner. This paper addresses the trade-off between risk and cost related to standby safety systems. An age-dependent unavailability model that integrates the effects of the test and maintenance (T&M) activities as well as component ageing is developed and represents the basis for calculating risk. The repair “same-as-new” process is considered regarding the T&M activities. Costs are expressed as a function of the selected risk measure. The time-averaged function of the selected risk measure is obtained from probabilistic safety assessment, i.e. the fault tree analysis. This function is further extended with inclusion of additional parameters related to T&M activities as well as ageing parameters related to component ageing. In that sense, a new model of system unavailability, incorporating component ageing and T&M costs, is presented. The testing strategy is also addressed. Sequential and staggered testings are compared. The developed approach is applied on a standard safety system in nuclear power plant although the method is applicable to standby safety systems that are tested and maintained in other industries as well. The results show that the risk-informed surveillance requirements differ from existing ones in technical specifications, which are deterministically based. Moreover, the presented approach achieves a significant reduction in system unavailability over a relatively small increase of total T&M costs.     

浅析AP1000核电在役无损检测安全管理的重要性

作为第三代核电自主技术,AP1000是目前全球核电市场中最安全、最先进的商业核电技术。在役无损检测作为AP1000核电运营安全性的重要保证之一,其安全管理的好坏直接关系到无损检测作业的成功与否。AP1000核电在役无损检测是十分复杂的系统工程,作业过程中存在诸多危险因素,检测工序复杂,因此核电厂无损检测服务企业必须将安全管理贯穿于整个在役无损检测管理过程之中。     

核电站火灾与核安全相关性的研究

根据核电站３０年来火灾和核安全事故统计数据,运用概率风险分析方法对核电站火灾与核安全事故相关性作出定量的估计。     

On the use of probabilistic and deterministic methods in risk analysis

Risks to human beings arise from an inherent characteristic to make plans and try to make them happen, while external forces resist and tend to move our endeavours away from the plan. Any such “endeavour” is a complex ensemble of a bewildering variety of interacting elements which together form something “whole”, usually called a “system” (e.g. a chemical process plant, a nuclear power plant, the stock market, air traffic control). A system has a certain state in the present and subsequent states in the future. There are deterministic and probabilistic systems and corresponding approaches to analyse them, that is to make their current states apparent and predict their future behaviour. In this paper, it is shown in which ways both analyses appear in risk analysis and it is hypothesised that both approaches are modelling the same process, though probabilistic analysis may reveal more information since it explicitly incorporates uncertainty in the form of numbers (and “there is safety in numbers”). The overall objective of this paper is to make clear what the differences between the two approaches really are. Their respective main strengths and weaknesses are discussed. A more refined objective is to discuss the specific role of probabilities in risk analysis. Examples of both approaches are given from applications in the nuclear power and chemical process industries, and some of the main problems encountered thereby are identified. Further, the challenge to system analysis posed by “chaos theory” is discussed. Due to its non-linear dynamic character, the future behaviour of a “chaotic system” is difficult to predict over a long period of time because it depends on arbitrarily small and thus not observable variations in the current state. Such behaviour might have serious consequences for human operators involved in the control of such systems. The paper concludes that, although both approaches to risk analysis can provide adequate safety levels to systems if applied in a correct and non-biased way, probabilistic methods seem to be more cost-effective and the results easier to communicate to decision- and policy-makers.     

低功率和停堆工况下人员可靠性分析

低功率和停堆工况下人的错误操作引起的人误事件,是电站风险的重要根源之一,应对其进行认真分析并找出其发生的主要原因。笔者根据低功率和停堆工况下人误事件的特点,通过对5种人员可靠性分析方法的比较,选择了SPAR -H作为人误事件定量化分析的方法;以停堆工况下的抽水过多事件为实例,对该事件中包含的3个人误事件进行了定量化分析,给出了定量化分析结果;通过分析、比较及实例应用的结果表明,SPAR H作为低功率和停堆工况下HRA分析方法是合适的,符合该工况下人误事件的特点,同时SPAR H过程简单,有利于电站人员进行实际应用。