系统安全性与可靠性分析的故障树方法

探讨了大型复杂系统安全性与可靠性分析的故障树技术。阐述了国外具有代表性的几种建树方法。针对实际应用情况,提出了将建树过程划分为5个阶段,应遵循的8条基本准則。导出了典型系统可靠度与故障率等可靠性参数计算的通用公式。论述了故障树分析方法的特点及发展动向。     

基于模糊颜色Petri网的表决DVP安全软件模型初探

把模糊计算理论和有色Petri网有机地结合起来,提出了一种模糊颜色Petri网诊断表决算法,把该算法应用于DVP的软件模型,使之具有故障容忍和表决的能力.笔者对以模糊颜色Petri网为核心的DVP软件模型表决算法进行了较为深入的探讨,该模型对提高软件系统的安全性和可靠性具有实际意义.     

Reliability assessment of safety instrumented systems subject to different demand modes

Safety instrumented systems (SISs) are commonly used in the process industry, to respond to hazardous events. In line with the important standard IEC 61508, SISs are generally classified into two types: low-demand systems and high-demand systems. This article explores this classification by studying the SIS reliability for varying demand rates, demand durations, and test intervals. The approach is based on Markov models and is exemplified by two simple system configurations. The SIS reliability is quantified by the probability of failure on demand (PFD) and the frequency of entering a hazardous state that will lead to an accident if the situation is not controlled by additional barriers. The article concludes that very low-demand systems are similar and may be treated as a group. The same applies to very high-demand system. Between these group, there is a rather long interval where the demand rate is neither high-demand nor low-demand. These medium-demand systems need a specific treatment. The article shows that the frequency of entering into a hazardous state increases with the demand rate for low-demand systems, while it is nearly independent of both the demand rate and the demand duration for high-demand systems. The PFD is an adequate measure for the SIS reliability for low-demand systems, but may be confusing and difficult to interpret for high-demand systems.     

A new approach to quantitative assessment of reliability of passive systems

The objective of this paper is to show how probabilistic reliability can be assessed for complex systems in the absence of statistical data on their operating experience, based on performance evaluation of the dominant underlying physical processes. The approach is to distinguish between functional and performance probabilities when dealing with the quantification of the overall probability of a system to perform a given function in a given period of time (reliability). In the case of systems where sufficient statistical operating experience data are available, one can focus the quantitative evaluation entirely on the assessment of the functional probability for a given active item (e.g. a pump) by assuming that the specification, layout, construction and installation is such that the item is providing the assigned performance, e.g. in the form of generating the required flow rate. This is how traditional probabilistic safety assessments (PSAs) focus the reliability analysis for the various safety features on the calculation of values for the availability per demand. In contrast, for various systems relevant in advanced technical applications, such as passive safety features in innovative reactor designs, it is essential to evaluate both functional and performance probabilities explicitly and combine the two probabilities later on. This is of course due to the strong reliance of passive safety systems on inherent physical principles. In practice, this means that, for example, in case of a passive cooling system based on natural circulation of a given medium, one has to evaluate and to assess the probability to have a medium condition and a flow rate such that a cladding temperature, represented by a probability distribution, can be hold at a required level. A practical example of this method is given for the case of the reliability assessment of a residual passive heat removal system. General conclusions are drawn regarding reliability estimation of complex, interconnected systems in the absence of statistical performance data, such as for infrastructures.     

空气储罐安全临界裂纹的可靠性分析

通用失效评定图在评定焊接结构安全性方面广为采用.但是,材料力学性能的测试、结构中缺陷大小的测试,客观上存在一定不确定性.因此,不论是对评定参数还是评定结果都需要进行可靠性分析.但可靠性分析需要大量数据,有时难于实现.为此,在对随机变量的实验结果进行统计分析中,采用二维单侧容限方法,从而在不增加工作量的同时,确保了分析结果的高可靠性.在空气储罐安全临界裂纹分析计算中,经这一方法处理后,采用成功-失败法对指定失效概率进行求解,裂纹尺寸变动1 mm,其安全评定的失效概率则变动几个数量级.从而在充分挖掘储罐潜能的同时,大大提高了安全临界裂纹分析的可靠度.     

基于安全控制论的株洲冶炼厂的综合安全评价

对生产经营单位进行安全评价可以有效地预防事故发生,减少财产损失和人员伤亡及伤害,安全评价是安全生产管理的一个重要组成部分.综合安全评价是以安全控制论为理论基础的安全评价法.笔者从现代安全控制论角度,通过系统危险辨识、系统危险控制能力诊断,运用综合安全模型对株洲冶炼厂进行了安全评价.综合安全评价结果表明,一方面,株洲冶炼厂的安全度为56.13,处于临界状态;被评价的系统危险控制指数均为-0.24,说明其安全系统总体状况呈下降趋势.近20年来株洲冶炼厂的伤亡事故伤害频率有明显起伏波动的特点,当前的安全管理形势还非常严峻,应通过对全厂的安全评价,全面提高安全管理水平;另方面,基于安全控制论的综合安全评价是一种有效的安全评价方法,可以在各个大型厂矿得以推广应用.     

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.     

Reliability data acquisition and evaluation in process plants

Based on the practical experience of assessing reliability data in two plants of the explosives industry, the organization and scope of the data collection, the component delimitation, the procedures of quality assurance and the data evaluation for their final use in PSA studies are presented. An example is given for the type of detection and repair, etc. The mathematical background for evaluating observed component lifetimes is discussed. Both frequentist and Bayesian methods are addressed. The resulting failure rate distributions and their approximations by log-normal distributions for several key components are presented. They were obtained using a Bayesian approach with a non-informative prior. Remarks on uncertainty, their treatment and a proposal for transferring data to plants other than the ones investigated conclude the presentation.     

The successes and challenges of implementing high reliability principles: A case study of a UK oil refinery

Research conducted on organisations that are able to sustain excellent safety records over long time periods suggests that there are a number of practices that organisations can adopt to achieve high levels of reliability and safety. These practices are often discussed in the context of major incidents to highlight the safety standards that high hazard organisations should try to emulate. However, previous research has predominantly focused on non-profit organisations, and comparatively little research has examined whether high reliability practices may be meaningfully applied to commercial contexts. This paper addresses this gap by using a qualitative approach to explore the types of reliability-enhancing practices implemented in a UK-based oil refinery in its attempt to achieve its ethos of ‘safe and reliable operations’. The findings illustrate the successful application of reliability-enhancing practices in several domains, including: hazard identification and control; emergency preparedness and collection; and analysis of incidents and near misses. Management commitment to safety emerged as an important factor underpinning the successful implementation of reliability-enhancing practices, highlighting its potential significance in the context of commercial organisations. However, promoting an open reporting culture and maintaining high levels of management visibility may be some of the challenges encountered by organisations striving to implement reliability-enhancing practices.     

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

Introduction

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN).

Method

It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators’ values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN.

Conclusions

It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model.

Impact on Industry

The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model.     

Pilot sample risk analysis for underground coal mine fires and explosions using MSHA citation data

After three decades of sustained continuous improvement of mine safety performances in the US, mine disasters in 2006 and 2007 compromised an excellent record and presented new challenges and vulnerabilities for the underground coal mining industry. In the aftermath of the incidents, formal investigations and new scrutiny of mine safety by the US Congress and expert study groups followed. The US Congress passed the Mine Improvement and New Emergency Response Act of 2006 (MINER Act), which mandated new laws to address the issues, including those related to mine fires and explosions from which miners must be protected. The National Mining Association-sponsored Mine Safety Technology and Training Commission report highlighted the role of risk analysis and management in identifying and controlling major hazards, such as fires and explosions. In this paper an approach is given for analyzing the risks for fires and explosions based on the Mine Safety and Health Administration citation database. Using 2006 citation data and focusing on subsystem failures, the methodology is applied to a database for a pilot sample of underground coal mines stratified by mine size and state.     

火工品可靠性(或安全性)评估的Bayes方法

对火工品可靠性（或安全性）评估中通常采用的经典方法进行了剖析。介绍了数理统计方法学中近年来兴起的Ｂａｙｅｓ统计推断方法，并给出了此法在火工品二项分布、正态分布情况下，对可靠度评估的应用实例。     

安全控制论的理论基础和应用(一)

介绍了安全控制论的基本理论和应用。论述了安全系统结构和建模以及系统参数辨识和系统控制方式。在应用方面,讨论了安全计量和系统状态评价建模和系统安全状态宏观预测问题。此外,为了克服计算上的困难。还采用了一些现代统计方法。     

A systems perspective of managing error recovery and tactical re-planning of operating teams in safety critical domains

Introduction

Research in human error has provided useful tools for designing procedures, training, and intelligent interfaces that trap errors at an early stage. However, this “error prevention” policy may not be entirely successful because human errors will inevitably occur. This requires that the error management process (e.g., detection, diagnosis and correction) must also be supported. Research has focused almost exclusively on error detection; little is known about error recovery, especially in the context of safety critical systems. The aim of this paper is to develop a research framework that integrates error recovery strategies employed by experienced practitioners in handling their own errors.

Method and Results

A control theoretic model of human performance was used to integrate error recovery strategies assembled from reviews of the literature, analyses of near misses from aviation and command & control domains, and observations of abnormal situations training at air traffic control facilities. The method of system dynamics has been used to analyze and compare error recovery strategies in terms of patterns of interaction, system affordances, and types of recovery plans. System dynamics offer a promising basis for studying the nature of error recovery management in the context of team interactions and system characteristics.

Impact on industry

The proposed taxonomy of error recovery strategies can help human factors and safety experts to develop resilient system designs and training solutions for managing human errors in unforeseen situations; it may also help incident investigators to explore why people's actions and assessments were not corrected at the time.     

南水北调中线干线工程安全生产管理体系策划方案研究

南水北调中线路干线工程是国家重点建设工程,该工程规模大、覆盖范围广、施工战线长、技术复杂、管理难度大,工程建设对安全生产管理工作提出了很多现时的要求,安全生产工作直接影响着工程的建设质量。根据工程建设的特点,结合现代安全生产管理的要求,笔者提出了“12345”的安全生产管理模式,在实际安全生产管理工作中发挥着很好的作用,为类似工程项目的安全生产管理工作提供了很好借鉴。     

特种劳动防护用品安全标识监管与防伪系统的开发及应用

本系统将特种劳动防护用品在日常管理过程中出现的大量繁杂多变的信息转变为数字信息数据，并建立适当的数学模型，由计算机对模型进行综合分析处理，同时显示结果，从而实现特种劳动防护用品的数字化管理，实现产品的真伪辨别和产品质量的责任追溯。     

事故致因理论的比较分析

本文对事故致因理论进行了总结并对其优缺点进行了介绍,对一些主要的事故致因理论进行了比较,分析了其异同,提出了各自的特点和适用条件,并对其理论发展前景进行了展望。运用事故致因理论对具体事故案例进行了分析,找出了事故原因,提出了预防措施。     

Bayesian sample size determination for inspection of general corrosion of process components

A Bayesian approach-based method is proposed for calculating the minimum size of a sample to assess, with a specified precision, the integrity of process components suffering from general corrosion. The proposed method ensures that the error in the posterior estimate of the mean does not exceed a pre-defined acceptable margin of error at a specified confidence level. An analytical formula to estimate the sample size is introduced. The sample size obtained using the proposed method is smaller than a sample size obtained using the classical method with same confidence level. This reduces sampling inspection cost without affecting the precision of the estimate.     

Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects

Objective: Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR.

Methods: This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model.

Results: Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime.

Conclusions: This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.