Functional safety concept for hazardous systems and new challenges

Selected issues associated with the functional safety analysis according to the international standards IEC 61508 and IEC 61511 are presented. Determining the safety integrity level (SIL) of electric/electronic/programmable electronic (E/E/PE) safety-related systems is outlined. The importance of quantitative probabilistic modeling of these systems in verifying SIL is emphasized. Some aspects concerning the functional safety analysis of systems for detecting the combustible or toxic gases in relation to a CENELEC draft standard prEN 50402 are shortly discussed. Basic principles of methodology for the functional safety assessment of protective systems for potentially explosive atmospheres proposed in a CEN draft standard prEN 15233 are addressed.     

The dynamic flowgraph methodology as a safety analysis tool: programmable electronic system design and verification

The objective of this paper is to demonstrate the use of the Dynamic Flowgraph Methodology (DFM) during the design and verification of programmable electronic safety-related systems. The safety system consists of hardware as well as software. This paper explains and demonstrates the use of DFM, and how DFM can be used to verify the hardware and application software design. DFM is used not only to analyze newly developed software but also to verify existing software. The outcome of the design verification of the safety system is used to define the necessary diagnostic capabilities that are essential to guarantee the correct functioning of the safety functions.     

IEC61508标准指导城市轨道交通设备安全功能指标实施

IEC61508标准提出电气／电子／叮编程电子（E／E／PE）安全相关系统的功能安全，成为了电气／电子／可编程电子（E／E／PE）安全相关系统的功能安全的基本和核心标准。城市轨道交通设备越来越多地采用了电气／电子／可编程电子系统（E／E／PES），确保这些设备功能安全指标的落实是工程建设，以及运营安全的一个重要组成环节。     

智慧工地本质安全度评价方法研究*

为对智慧工地全生命周期的本质安全度进行分析与评价,综合运用本质安全理论,构建智慧工地本质安全度评价模型。首先,根据智慧工地本质安全定义,将智慧工地本质安全度划分为初始级、简单级、标准级、成熟级和卓越级5个等级;其次,基于智慧工地的生产现状,构建包括人员管理系统、机械设备管理系统、现场监测预警系统、过程控制管理系统等4个一级指标和16个二级指标的本质安全度评价指标体系;最后,利用C-OWA算子对指标的权重进行计算,采用未确知测度评价法对系统进行综合评价。结果表明:将模型应用到西安地铁某在建项目中,得到该智慧工地项目现阶段推进状态本质安全度等级为标准级,明确该项目下一阶段提升改进的方向,为智慧工地本质安全管理的持续改进提供理论支持。     

Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model

A substantial amount of oil & gas products are transported and distributed via pipelines, which can stretch for thousands of kilometers. In British Columbia (BC), Canada, alone there are over 40,000 km of pipelines currently being operated. Because of the adverse environmental impact, public outrage and significant financial losses, the integrity of the pipelines is essential. More than 37 pipe failures per year occur in BC causing liquid spills and gas releases, damaging both property and environment. BC oil & gas commission (BCOGS) has indicated metal loss due to internal corrosion as one of the primary causes of these failures. Therefore, it is of a paramount importance to timely identify pipelines subjected to severe internal corrosion in order to improve corrosion mitigation and pipeline maintenance strategies, thus minimizing the likelihood of failure. To accomplish this task, this paper presents a Bayesian belief network (BBN)-based probabilistic internal corrosion hazard assessment approach for oil & gas pipelines. A cause-effect BBN model has been developed by considering various information, such as analytical corrosion models, expert knowledge and published literature. Multiple corrosion models and failure pressure models have been incorporated into a single flexible network to estimate corrosion defects and associated probability of failure (PoF). This paper also explores the influence of fluid composition and operating conditions on the corrosion rate and PoF. To demonstrate the application of the BBN model, a case study of the Northeastern BC oil & gas pipeline infrastructure is presented. Based on the pipeline's mechanical characteristics and operating conditions, spatial and probabilistic distributions of corrosion defect and PoF have been obtained and visualized with the aid of the Geographic Information System (GIS). The developed BBN model can identify vulnerable pipeline sections and rank them accordingly to enhance the informed decision-making process.     

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。     

建立矿井安全评价指标体系的研究

《矿井安全评价系统》（下称《评价系统》），是劳动部１９９４年下达的劳动科学技术（自然科学类）科研项目，其子课题为《建立矿井安全评价指标体系》（下称《指标体系》）。要完成“安全评价”必须解决评价的标准。本文从分析被研究的系统出发，针对每项评价任务，研究需要哪些“标准”；所需“标准”哪些已有“国家标准”；哪些需要研究解决，建立新的“标准”；还讨论了《指标体系》建立的原则、结构及其完善性、合理性和科学性。     

矿井瓦斯防爆监测氧含量线性标定

矿井火灾是采矿业面临的安全生产问题之一。该文研究的目的是评估新的矿井瓦斯防爆监测中最重要的成分氧气的检测策略,在矿井火灾中做出预见与预报。对于密封区域,发生瓦斯爆炸危险安全区时氧气浓度小于8%,按照国家标准,本矿要求氧气检测精度达到1%。氧含量监测系统受到气体气路、传感器运行、信号调理与处理情况和终端处理系统等四个方面的影响。该文通过运用计算机控制技术分别对氧含量监测系统进行硬件线性开环标定与软件线性闭环标定,并采用著名的OriginPRO数据分析软件对系统采样数据进行了分析与解读,以达到对软件线性闭环标定进行程控规划和信息实时纠正,使系统氧气含量监测灵敏限小于0.36%。     

Integrating probabilistic signed digraph and reliability analysis for alarm signal optimization in chemical plant

The alarm system given in industrial plants are massive and complex. Under such condition, critical alarms are overwhelmed by false and unnecessary alarms and thus result in severe safety issues. To address the problem, this paper proposes a probabilistic signed digraph (PSDG) based alarm signal selection method that requires achieving maximal system reliability. In this method, a PSDG model is firstly constructed to visualize the causal relations between process variables. Then the criteria of observability and identifiability are imposed to determine the candidate alarm variables that can qualitatively distinguish all assumed faults. Instead of selecting the minimum number of combinations of candidate variables, the alarm variables are optimized by a reliability formulation that takes into account the missed alarm and false alarm probabilities of the system; this formulation is solved by the receiver operating characteristic (ROC) graph. Finally, the developed methodology is illustrated using a Tennessee Eastman process.     

Dynamic risk assessment using failure assessment and Bayesian theory

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

Optimization of test interval for ageing equipment: A multi-objective genetic algorithm approach

Reducing the unavailability of safety systems at nuclear power plants, by utilizing the probabilistic safety assessment (PSA) methodology, is one of the prime goals in the nuclear industry. In that sense, optimization of test and maintenance activities, which are defined within the technical specifications, represents quite popular and interesting domain. Obtaining optimal test and maintenance schedule is of great significance for improving system availability and performance as well as plant availability in general.On the other side, equipment aging has gradually become a major concern in the nuclear industry since the number of safety systems components, that are approaching their wear-out stage, is rising fast. Nuclear power plants life management programs, considering safety components aging, are being developed and employed. The immense uncertainty associated to the available component aging rates databases poses significant difficulties in the process of incorporation and quantification of the aging effect within the PSA and, subsequently, in the decision-making process.In this paper, an approach for optimization of surveillance test interval of standby equipment with highly uncertain aging parameters, based on genetic algorithm technique and PSA, is presented. A standard standby safety system in nuclear power plant is selected as a case study. A Monte Carlo simulation-based approach is used to assess uncertainty propagation on system level. Optimal test interval is derived on the basis of minimal system unavailability and minimal impact of components aging parameters uncertainty. The results obtained in this application indicate the fact that risk-informed surveillance requirements differ from existing ones in technical specifications as well as show the importance of considering aging data uncertainties in component aging modeling.     

Procedure for assessing hardware safety integrity in legacy systems

Functional safety is related to the safety functions of a safety-related system that uses electrical/electronic/programmable (E/E/PE) devices such as sensors, logic solvers, and final elements. A legacy system is a safety-related system which offers safety functions but which was not designed to comply with the IEC 61508 standard. This paper presents a procedure for assessing the hardware safety integrity of a legacy system so as to confirm its functional safety. The procedure defines the systematic relationship between the safety function and hardware system using a function-structure map (FSM) and assesses the hardware safety integrity centered on the safety function. The proposed procedure is applied to a boiler control system of a fossil-fuel power plant.     

Experts,Bayesian Belief Networks,rare events and aviation risk estimates

Bayesian Belief Networks (BBN) are conceptually sensible models for aviation risk assessment. The aim here is to examine the ability of BBN-based techniques to make accurate aviation risk predictions. BBNs consist of a framework of causal factors linked by conditional probabilities. BBN conditional probabilities are elicited from aviation experts. The issue is that experts are not being asked about their expertise but about others’ failure rates. A simple model of expertise, which incorporates the main features proposed by researchers, implies that a best-expert’s estimates of failure rates are based on accessible quantitative data on accidents, incidents, etc. Best-expert estimates will use the best available and accessible data. Depending on the frequency of occurrence, this will be data on similar events, on similar types of event, or general mental rules about event frequencies. These considerations, plus the need to be cautious about statistical fluctuations, limit the accuracy of conditional probability estimates. The BBN framework assumes what is known as the Causal Markov Condition. In the present context, this assumes that there are no hidden common causes for sequences of failure events. Examples are given from safety regulation comparisons and serious accident investigations to indicate that common causes may be frequent occurrences in aviation. This is because some States/airlines have safety cultures that do not meet ‘best practice’. BBN accuracy might be improved by using data from controlled experiments. Aviation risk assessment is now very difficult, so further work on resilience engineering could be a better way of achieving safety improvements.     

Building an Executive Information System for Maintenance Efficiency in Petrochemical Plants—An Evaluation

This study used the manufacturing process in the petrochemical industries as an example and developed a dedicated maintenance programme and executive information system (EIS) for this industry. The software for EIS was established on a CMMS platform, with logical and extractive analysis used to store the information in a KPI databank. The system developed can provide plant managers and engineers with a complete summary of information and keep them updated regarding the present status of their maintenance efforts. The objective of this study was to establish a management system for maintaining knowledge in the petrochemical industries, such as the management of standard operating procedures (SOPs), historical records and the analysis of data for the facility. To design the software, a review of petrochemical facility was purposed to enhance the maintenance efforts and facilitate the decision-making process. The main functions of the system include asset reliability analysis, failure analysis and maintenance benefit cost analysis. For the petrochemical industry, the impact of safety and environment caused by equipment malfunction is more substantial than that of other industries. If executives can manage essential points effectively and make decisions according to a key performance index, risks to safety and environment, which result from equipment malfunction, can be decreased and safety can be enhanced for petrochemical refineries.     

基于建筑信息模型的铁路工程安全管理体系研究

为解决铁路施工现行安全管理强度大、施工准备不足、部门间协作性与联系性较弱、信息滞后、施工保障不足等问题,充分考虑建筑信息模型的优势,结合建筑信息模型对铁路施工进行全生命周期安全管理。利用Revit对工程项目进行建模,结合三维模型对人员进行技术交底与安全教育,导入广联达BIM5D软件对工程项目的即时性管理。研究结果表明:该安全管理体系可以通过可视化设计、施工模拟在施工前充分准备,预先采取针对性安全措施;同时实现信息的全程实时共享,增强各部门之间的协调性和管理的及时性;结合建筑信息模型与云平台充分保障后期的运行与维护,达到对铁路工程进行高效、可行的全生命周期信息化安全管理的目的。     

浅议风险观对风险评价方法论的影响

风险观对安全科学的发展具有重要的指导意义。本文从风险本体论、风险认识论和风险方法论三个方面论述了风险观的发展变迁。简述了风险本体论从一维、二维到三维或多维的发展历程,总结了风险认识论从技术导向到社会文化导向的变化,给出了风险方法论的分类。总结了风险方法论的重要组成部分即风险评价的发展过程,探讨了确定性风险评价、概率性风险评价和定量风险评价等评价方法在风险本体论和认识论发展背景下的继承性等问题,探讨风险本体论和认识论对风险评价方法论的影响,提出风险沟通研究的必要性。     

安全控制系统的设计思想

介绍了安全控制领域的国际标准IEC61508.给出了安全整体性要求的4个等级(SIL)相应的技术指标.从硬件故障的控制、系统故障的避免及安全系统软件的设计3个方面阐述了安全控制系统的设计思想.对硬件故障控制中的1oo2D和2oo3系统进行了比较,给出了相应的SIL计算方法.针对避免系统故障,提出了系统设计的6条原则和方法.介绍了 3种面向过程控制和对实时性要求较高的安全系统软件的设计方法.     

基于有限元与极限平衡分析的露天矿边坡角优化

为保证露天边坡的安全稳定,提出用有限元与极限平衡综合分析法分析其稳定性并优化边坡角。利用数值分析软件ABAQUS模拟出边坡潜在滑动面和张裂缝的位置,再根据极限平衡法计算出不同边坡角下的安全系数值,绘制安全系数随边坡角的变化曲线,最后得到安全稳定条件下的最终边坡角的优化值。采用该方法对某露天矿的边坡进行优化,最终边坡角由原设计的53.5°提高至55.4°,能同时降低剥离工程量,保证边坡的稳定性。     

石油天然气钻井工程风险量化技术

基于风险的概念,在对石油天然气钻井工程设计、工艺设备、施工管理、复杂情况和事故等总体分析的基础上,提出钻井工程风险量化方法———风险评估指数系统。此方法结合科学计算和专家经验,确定了固有风险指标、事故易发性指标和后果严重度指标等三个指标及量化标准,并将钻井工程风险划分为4个等级,最终建立了由指数体系、评分体系、风险分级标准组成的风险评估系统。本方法可用于专业机构的风险评估,也可用于安全管理部门的检查,以指导采取相应措施降低工程的危险性。     

Epistemic uncertainty in fault tree analysis approached by the evidence theory

Process plants may be subjected to dangerous events. Different methodologies are nowadays employed to identify failure events, that can lead to severe accidents, and to assess the relative probability of occurrence. As for rare events reliability data are generally poor, leading to a partial or incomplete knowledge of the process, the classical probabilistic approach can not be successfully used. Such an uncertainty, called epistemic uncertainty, can be treated by means of different methodologies, alternative to the probabilistic one. In this work, the Evidence Theory or Dempster–Shafer theory (DST) is proposed to deal with this kind of uncertainty. In particular, the classical Fault Tree Analysis (FTA) is considered when input data are supplied by experts in an interval form. The practical problem of information acquisition from experts is discussed and two realistic scenarios are proposed. A methodology to propagate such an uncertainty through the fault tree up to the Top Event (TE) and to determine the belief measures is supplied. The analysis is illustrated by means of two simple series/parallel systems. An application to a real industrial safety system is finally performed and discussed.