PSA中人因失误模型化研究

主要研究PSA模型如何考虑人因失误的影响,系统地提出如何在电厂系统模型中建立相对应的人因失误分析模型。利用事件树把系统故障和人因失误相结合的方法,探讨如何最大可能地真实描述事故后的操纵员行为,确定重要人因事件发展序列以及根据系统响应确定合理可分析的人因题头,建立完整的人因失误模型化的体系,并以实例说明具体分析过程。此项研究能够较好地描述硬件可靠性和人因可靠性之间的关联关系,降低HRA出力并满足PSA对于事故后人员行为的概率分析需求。     

事故前人因失误研究

在安全评价中，人因失误特别是事故后人因失误越来越受到重视；但相对而言，事故前人因失误没有引起足够的重视。本通过对大量核电厂安全分析报告和运行事件报告的考察，系统地阐述了事故前人因失误对系统安全的显影响，并在此基础上，归纳出在核电站开展事故前人因(失误)分析的程序。该程序主要包括系统熟悉，定性分析，筛选，定量计算，与故障树的集成，敏感性分析与不确定性分析，形成分析档等几个步骤。     

人因可靠性数据库基础架构研究

针对人因可靠性分析中的数据匮乏问题,在技能-规则-知识(SRK)模型的基础上建立层次化的人因可靠性数据分类体系,其中包括人因失误模式和人因失误影响因素。结合对一些实际人因失误数据的考察,以及可控实验,确定人因可靠性数据库中基准人因失误概率。在人因数据外推系统中,使用层次分析法(AHP)来定量评价人因失误所处的情境的等级,并使用概率方法将基准人因失误概率与情境进行叠加,从而得到人因失误概率。人因数据库有助于人因可靠性数据的搜集和分析,形式化的外推方法减少了对主观因素的依赖。     

基于人因失误率预测法改进的事故后人因可靠性分析技术

人因可靠性分析是概率风险分析的重要组成部分,事故后人因事件分析是人因可靠性分析的核心内容.工程应用中的人因可靠性分析技术应在满足分析准确性需求的基础上尽可能简单与规范.本文分析了人因失误率预测法(THERP)的主要不足及事故序列评估程序人因可靠性分析技术(ASEP HRA)所做出的重要改进,描述了事故后ASEP HRA在工程应用中的基本程序,给出了一个应用实例.     

复杂工业系统中班组人因失误分析

在复杂工业系统中 ,人因可靠性分析 (HRA)是预防和减少人因失误的有效方法。人在复杂工业系统中的生产活动 ,往往是由组织中班组成员集体完成的 ,完整的HRA必须充分考虑班组人误的产生。班组人误的产生有其自身的规律 ,如何合理地定义人员行为形成因子 (PSFs)是班组人因失误分析的难点 ,也是班组人因失误分析的重要手段 ,被广泛应用在核电厂 ,航空和造船工业领域的事故分析中。笔者详细分析和探讨了班组人因失误的定义、产生过程及相关的人的行为形成因子 ,以期能使大规模工业系统中的人因失误分析更加合理和完善。     

核电厂HRA组织定向研究

概率安全评价(PSA)已经成为核电厂定量化安全评价的主要方法,人因可靠性分析(HRA)是其中重要组成部分.传统的HRA方法研究对象主要是"个体失误",而HRA的全面评估必须考虑"组织情景",HRA必须组织定向.分析了HRA各主要方法对于组织因素考虑的不足,提出了HRA组织定向的必要性和基本原则.在提出组织定向的假设条件基础上,建立了HRA(A、B、C类事故)与核电厂相关特定组织之间的映射模型.     

人员可靠性分析及人员可靠性数据管理系统研究

人员可靠性在系统可靠性计算中占的比重越来越大 ,人因失误事件的分析及其管理也成为安全管理的重要组成部分。为更加有效、准确地进行人员可靠性分析和人因失误事件的管理 ,提高系统的安全性 ,建立一个人员可靠性分析及人员可靠性数据管理系统是非常必要的 :首先为人员可靠性分析和人因事件管理提供一个有用的计算机辅助工具 ;再者通过建立具有一定规模的人员可靠性数据库 ,以便为今后进一步的研究提供良好的数据支持。笔者简述了该系统的一些基本原理和实现的主要功能。     

CREAM追溯法在交通事故人因分析中的应用研究

人因失效是道路交通事故发生的主要原因.认知可靠性和失误分析方法(CREAM)可以追溯事故发生的根原因,并对事故隐患进行预测.它强调情景环境对人的行为的重要影响,较符合驾驶员可靠性分析的需求.研究了CREAM中的追溯分析方法在道路交通人因失效事件根原因分析中的应用,建立了道路交通事故的人因失效模式,对人因失效基本原因的分类和后果-前因关系进行归纳、整理和补充,提出了适用于道路交通人因失效事件的“后果-前因”追溯表和具体的追溯分析步骤.进而对其定量计算进行了探索,并通过实例探讨了其应用,得到事故发生的根原因.     

复杂人——机系统中的人因失误

随着人——机系统变得越来越多，装置的可靠性越来越高，人因失误已成为重要的潜在事故源。本文描述了复杂人——机系统的特征，探讨了该系统中人因失误的定义、分类、数据采集和事故模型。这些研究有助于对人因失误的预测、预防和减少。     

核电站人因事件分析与改进对策

对于核电站而言,安全是存在和发展的前提。统计资料显示,全球核电站的人因事故总数超过事故总起数的60%,有的核电站其最高值已达到85%。可见,人因事件是影响核电厂安全稳定运行的主要因素,核电站的人因事件必须得到足够的重视。     

核电厂HRA定性分析

人因可靠性分析(HRA)是核电厂概率安全评价(PSA)的重要组成部分,定性评价对核电厂庞大的数据进行筛选和分析,是HRA的基础和出发点.本文介绍了核电厂HRA定性分析的目的、原则、方法和程序,并以压水堆核电厂蒸汽发生器传热管破裂(SGTR)为具体实例进行说明.     

Human reliability analysis: A critique and review for managers

In running our increasingly complex business systems, formal risk analyses and risk management techniques are becoming more important part to managers: all managers, not just those charged with risk management. It is also becoming apparent that human behaviour is often a root or significant contributing cause of system failure. This latter observation is not novel; for more than 30 years it has been recognised that the role of human operations in safety critical systems is so important that they should be explicitly modelled as part of the risk assessment of plant operations. This has led to the development of a range of methods under the general heading of human reliability analysis (HRA) to account for the effects of human error in risk and reliability analysis. The modelling approaches used in HRA, however, tend to be focussed on easily describable sequential, generally low-level tasks, which are not the main source of systemic errors. Moreover, they focus on errors rather than the effects of all forms of human behaviour. In this paper we review and discuss HRA methodologies, arguing that there is a need for considerable further research and development before they meet the needs of modern risk and reliability analyses and are able to provide managers with the guidance they need to manage complex systems safely. We provide some suggestions for how work in this area should develop. But above all we seek to make the management community fully aware of assumptions implicit in human reliability analysis and its limitations.     

Issues of the Human Reliability Analysis in the Context of Probabilistic Safety Studies

This article addresses methodological issues of the human reliability analysis (HRA) in the context of probabilistic safety studies. Several conventional HRA techniques, more often used for the evaluation of the human error probabilities (HEPs), have been classified. A taxonomy of human actions, failure events, and related factors is outlined in order to distinguish action phases, human behavior types and incorrect outputs (errors of omission or commission), error types (slips, lapses, and mistakes), and performance-shaping factors (PSFs) influencing the human performance. A tree is proposed to facilitate the selection of a specific method for the evaluation of human reliability with regard to attributes of the situation analyzed. A software system based on the expert system technology to facilitate and document PSA and HRA is outlined. At the end of the article some research challenges in the domain are discussed.     

HRA in China: Model and data

Human reliability analysis (HRA) is generally viewed as quite an important part in probabilistic safety assessment (PSA). In this paper, a THERP + HCR HRA model is presented to model the operators’ post-accident behavior in Chinese nuclear power plants. The paper shows how the model is structured and how to consider and acquire the corresponding data, including HCR data modification and HRA event tree data. A case study is presented to make an illustration.     

Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment

To address human error in system reliability, Human Reliability Analysis (HRA) is an essential issue. Human Error Assessment and Reduction Technique (HEART) as a rather straightforward technique for HRA has successfully been used in many areas to predict human error probability (HEP). However, knowledge acquisition of experts during assessed proportion of affect (APOA) calculation is subjected to vagueness and ambiguity. To overcome this challenge, in this paper Intuitionistic Fuzzy (IF) set due to their advantage to represent more fuzzy information than a classical fuzzy set adopted through APOA calculation. To demonstrate this hybrid approach short for, IF-HEART, the furnace start-up operation is handled, since analysis shows that most of explosions and losses occur during furnace start-ups operation. Further, a sensitivity analysis is carried out to approve the proposed integrated approach. In addition to its academic contribution, the results of the paper enable to improve the overall safety level of a furnace by taking into account potential human error.     

第二代人的可靠性分析方法的进展

在探讨第一代人的可靠性分析 (HRA)方法的局限性之后 ,笔者进而探讨第二代HRA方法的模型 ,建立在多种学科 (认知心理学、行为科学、可靠性工程等 )相互结合的基础上 ,又着重研究产生人的行为 /绩效的情景环境以及它们是如何影响人的行为 /动作的 ,并与工业系统的运行经验和现场或模拟机获得的信息紧密结合。重点介绍了以“失误分析技术”(ATHEANA)和“认知可靠性和失误分析方法”(CREAM)为代表的第二代HRA方法。它们是当前HRA领域中的具有应用和发展前景的新框架思想。     

A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks

Organizational factors are the major root causes of human errors, while there have been no formal causal model of human behavior to model the effects of organizational factors on human reliability. The purpose of this paper is to develop a fuzzy Bayesian network (BN) approach to improve the quantification of organizational influences in HRA (human reliability analysis) frameworks. Firstly, a conceptual causal framework is built to analyze the causal relationships between organizational factors and human reliability or human error. Then, the probability inference model for HRA is built by combining the conceptual causal framework with BN to implement causal and diagnostic inference. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual causal model with BN approach can not only qualitatively model the causal relationships between organizational factors and human reliability but also can quantitatively measure human operational reliability, and identify the most likely root causes or the prioritization of root causes causing human error.     

CREAM失误概率预测法在驾驶舱机组判断与决策过程中的应用

CREAM强调人在生产活动中的绩效输出不是孤立的随机性行为,而是依赖于人完成任务时所处的环境或工作条件,它通过影响人的认知控制模式和其在不同认知活动中的效应,最终决定人的响应行为。在驾驶舱内,机组的绩效输出不仅仅是人的自身行为,还依赖于其完成任务时所处的情景环境,所以CREAM方法能够结合驾驶舱环境对机组的认知差错进行分析。在飞行中,驾驶舱内机组非常重要的一个环节是判断与决策过程,这一过程中包括询问、讨论、确定方案、执行、反馈五个环节。本文将通过分析这五个环节的相互关系及影响,以明确这种讨论过程是减少机组人为差错发生的一种有益方式,然后应用CREAM的预测法对这五个环节进行定量化分析,得出机组判断与决策过程的失误概率,完成对机组认知行为的客观评价,并为以后能够定量化研究驾驶舱内飞行员认知差错提供方法的借鉴。