基于FTA-BN模型的页岩气井口装置失效概率分析

为研究页岩气井口装置失效问题,采用故障树分析法(FTA)和贝叶斯网络(BN)相结合的方法,构建井口装置失效概率分析模型。首先,分析井口装置失效原因,建立失效故障树;其次,基于映射算法,将失效故障树转化成BN模型;然后,对BN模型进行多态性和不确定性修正;最后,依托BN的双向推理能力,预测井口装置失效概率,辨识失效关键因素。结果表明:井口装置失效概率为1. 31×10~(-2);导致井口装置失效的关键因素为误操作、盘根老化和螺栓松动; BN模型经过修正后,失效概率相对提高3×10~(-3)。     

基于BN的FTA在通用航空风险评价中的应用

针对事故树分析法(FTA)在风险评价中的局限性,采用以事故树为基础建立的贝叶斯网络(BN)风险模型,对通用航空中的两机空中相撞事故进行分析和推理,对事故模型进行改进和修正时,注重基事件的多态性和事件间的逻辑合理性。根据贝叶斯推理得出的数据,找到了事故的主要致因。结果表明,基于BN的FTA既能向前预测顶事件的发生概率,又能向后诊断基本事件的后验概率,可以更好地对通用航空风险进行评价。     

基于FDHHFLTS-BN的海底管道泄漏失效风险定量分析

为预防海底油气管道泄漏失效事故,提出基于自由双层次犹豫模糊语言术语集(FDHHFLTS)和贝叶斯网络(BN)的FDHHFLTS-BN风险分析方法,用于分析海底油气管道泄漏失效事故概率及事故的关键风险因素。将故障树模型转换为BN结构,由专家根据FDHHFLTS评估基本事件发生可能性;采用最佳最差法(BWM)确定专家权重,结合相似性聚合方法(SAM)聚合专家意见;依据构建的BN模型,正向推理得到事故发生概率,反向推理得到后验概率,并进行敏感性分析。将该方法应用于实例分析,结果表明：分析段海底管道泄漏事故的概率值为P=6.20×10^-3;焊缝施工缺陷、材料施工缺陷和渔具作用等为事故发生的关键因素;与传统方法对比分析结果证明,所提方法在确定海底管道风险方面具有一定的优势。     

飞行区外来物入侵安全风险致因FTA-BN模型

为探究机场飞行区外来物(FOD)入侵安全风险,集成事故树分析(FTA)和贝叶斯网络(BN),构建风险致因分析模型;运用FTA分析FOD入侵的风险致因结构,结合BN表达风险的多模态性,通过FTA的结构推理和BN的双向推理分析、诊断和评价系统风险。研究结果表明:从系统的致险结构来看,违章因素的位置最关键;从系统的敏感性来看,道面破损、航班流量因素最敏感,2个节点最危险状态发生概率分别提升3.57%、0.43%即可导致顶事件发生;从系统的贡献度来看,违章、技能欠缺节点贡献最大,2个节点处于最危险状态时,顶事件发生概率最高,分别为4.18%、1.50%。样本机场FOD入侵发生概率为0.13%,增加飞行区作业人员的经验更能有效降低FOD入侵事件发生的概率。     

船舶溢油应急反应人的可靠性分析研究

为减小船舶溢油事故应急反应人员失误概率,提升应急处置效果,在对应急人员可靠性主要影响因素识别的基础上,利用模糊贝叶斯网络(BN)建立船舶溢油应急人的可靠性分析(HRA)模型,将应急反应流程抽象为可进行概率推算的BN,实现单个应急任务和全过程人的可靠性的量化评估,并依据该模型对一起船舶溢油事故进行实例研究。结果表明,首先模糊集值专家评估较好地解决应急人员可靠性情境依赖性强,难以量化评估的问题;其次,BN卓越的概率推理性能实现由单个应急任务向全过程人的可靠性的推算;最后得到应急反应人的可靠性主要取决于关键应急任务的完成情况和相关情境因素的影响。     

基于ET-DFT分层模型的复杂系统动态概率安全评价方法研究

为充分体现复杂系统的动态行为对其可靠性的影响,减少系统动态故障概率计算时的工作量,应用层次化分析思想,综合事件树(ET)和动态故障树(DFT),提出基于ET-DFT模型的动态概率安全评价(DPSA)方法。应用二元决策图(BDD)和马尔科夫链(MC)分别对静态故障树和DFT进行求解,给出将静态故障树和DFT向BDD及马尔科夫链转移图的转化算法,以及系统各状态概率的求解方法。通过应用实例的分析验证,得到系统静态模块定量的发生概率及动态模块各个状态概率随时间变化的曲线,经综合求解得到系统故障发生的概率,实现对系统较为精确的DPSA。     

数据缺失情况下水淹天然气管道泄漏风险分析

面向数据缺失情况下水淹天然气管道泄漏风险量化分析的需求,提出一种基于贝叶斯网络(BN)和模糊集理论(FST)的概率风险分析方法。首先采用故障树分析(FTA)法分析水淹天然气管道泄漏失效致因,并映射得到相应的BN模型;然后针对基本事件失效概率数据缺失的情况,用专家知识引出概率,替代缺失的统计失效概率;为处理概率引出过程中专家知识的模糊性和主观性导致的不确定性,结合FST与多专家层次分析引出模糊概率,将其作为实际先验概率输入BN模型,进行量化分析。以某复线水淹天然气管道为例,应用所提方法分析其泄漏风险,结果表明:用该方法能够在数据缺失情况下表征并量化泄漏风险,同时BN的正向预测和概率更新能力可用来评估动态风险、识别关键失效因素。     

海底泥浆举升钻井系统钻遇天然气水合物时的动态风险分析

海底泥浆举升钻井(Subsea Mud Lift Drilling, SMD)系统属于双梯度钻井系统。在钻井过程中遇到天然气水合物层(Natural Gas Hydrate, NGH)时,NGH的分解和二次生成造成了重大的风险。为了预测风险事故,对环境因素和设备因素进行了分析。首先,在建立蝴蝶结模型后,利用映射算法将其转化为贝叶斯网络(Bayesian Networks, BN);其次,考虑不确定性影响,在BN中进行不确定性建模;然后,考虑设备因素的动态不确定性,通过转移概率矩阵将建立的BN转化为不确定性动态贝叶斯网络(Uncertain Dynamic Bayesian Networks, UDBN)。此外,还利用模糊理论和专家判断来量化设备故障的先验概率。结果表明,钻遇NGH层时,钻井风险概率比正常工况下有所增加。由于有天然气水合物的影响,发生风险的概率也变得具有不确定性。     

基于FTA-BN的云ERP不安全事件的人因失误分析

为明确云企业资源计划(ERP)不安全事件的人因失误因素,构建基于故障树分析-贝叶斯网络(FTA-BN)的人因失误分析模型,以避免单一方法的局限性。首先,对云ERP安全审计记录披露的不安全事件进行分类和追因分析,构建云ERP不安全事件故障树,并定量分析最小割集、结构重要度;然后,将故障树映射为BN结构,利用案例数据进行结构学习和参数学习得到最终的贝叶斯网络;最后,依托贝叶斯网络的敏感性分析辨识关键人因失误因素,凭借预测推理计算发生不安全事件的概率。研究结果表明：云ERP安全人因失误因素中工作不到位、培训不足、资源分配不足、管理流程存在问题、职责不清等因素在对应的事件域中应得到重点关注,以保障持续安全。     

基于模糊BN的企业业务中断风险分析:以洪涝灾害情景为例

为量化极端暴雨洪涝灾害导致企业业务中断的风险,并识别导致中断发生的关键因素,分析2008年以来新闻报道的183例企业因洪涝受灾的案例,利用故障树映射方法构建企业业务中断风险贝叶斯网络(BN)模型;通过模糊集理论(FST)降低案例数据的不确定性,优化该BN模型的概率推理过程,并通过灵敏度分析识别出业务中断的关键因素。结果表明:洪涝灾害情景下,国内企业业务中断风险为35. 5%,供水中断及供电中断等2个因素是洪涝灾害情景下导致企业业务中断最关键的风险因素。     

Multi-hazard failure assessment of atmospheric storage tanks during hurricanes

Hurricane as one of the most destructive natural hazards can make a devastating impact on the industrial equipment, especially atmospheric storage tanks, leading to the release of stored chemicals and disastrous safety and environmental issues. These catastrophic consequences are caused not only by strong winds but also by the torrential rainfall and inundating floods. The objective of this study is to present a risk-based methodology for assessing and reducing the vulnerability of atmospheric storage tanks to hurricanes. Considering the shell buckling, flotation, sliding, and roof sinking as dominant failure modes of atmospheric storage tanks during hurricanes, Bayesian network (BN) has been employed to combine the failure modes while considering their conditional dependencies. The probability updating feature of the developed BN was employed to indicate that the flood is the most critical hazard during hurricanes while the impact of wind and rainfall cannot be neglected. Extending the developed BN to an influence diagram, the cost-benefit filling of storage tanks with water prior to the advent of hurricanes was shown as a viable measure for reducing the damage probability. The results show that the proposed methodology can be used as an effective decision support tool for assessing and reducing the vulnerability of atmospheric storage tanks to natural hazards.     

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.     

基于BN-CREAM的深水井控压井作业风险诱因研究

深水井控压井作业是有效控制溢流演化为井喷事故的二级井控工艺屏障。为提高深水井控压井作业可靠性,采用 BN-CREAM方法对其风险诱因进行研究。结合深水井控压井作业特点,考虑共因失效等因素,采用贝叶斯网络方法建立深 水井控压井作业风险演化模型。应用人因可靠性分析CREAM法计算深水压井人因失误先验概率,参考海洋可靠性数据手 册OREDA确定深水井控设备失效先验概率。依托贝叶斯网络的逆向推理能力辨识压井作业的主要风险节点,从而实现对 深水井控压井作业风险诱因的有效预测和评估。研究表明:深水井控压井作业共包含6个关键风险根节点,且压井作业人 因可靠性要低于设备可靠性;3级子节点“压井方法选择不合理”对深水压井作业的成功起到至关重要的作用,需进一 步开展风险分析研究。     

贫数据条件下海底电缆故障概率评估方法*

为解决贫数据引起海底电缆失效概率评估的不确定性影响,实施有效的海底电缆故障风险管理,提出1种耦合模糊集理论、层次贝叶斯分析（HBA）和贝叶斯网络的海底电缆失效概率评估方法,识别海底电缆失效致因因素,梳理各因素之间的关联关系,并采用贝叶斯网络(BN)构建海底电缆失效模型;根据数据源特点将电缆失效因素分为数据完全缺失和具有稀少的先兆数据,采用模糊集理论(FST)计算完全没有可用数据的失效致因发生概率,通过HBA估计有稀少数据失效致因的发生概率;以失效致因发生概率为输入,通过贝叶斯网络实现海底电缆失效概率的动态评估。研究结果表明:FST-HBA-BN方法可以解决基本风险因素的数据稀缺问题,量化评估海底电缆失效概率,研究结果可为贫数据条件下的电缆失效风险管理提供支撑。     

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.     

Risk-based reliability assessment under epistemic uncertainty

Existing risk in production systems has a direct relationship with unreliability of these systems. Under such circumstances, the approach to maximize the reliability should be replaced with a risk-based reliability assessment approach. Calculating the absolute reliability for systems and complex processes, when we are not provided with any data on failure, is extremely complex and difficult. Until now, studies of reliability assessment have been based on the probability theory, in which the failure time is anticipated after determining the type of size distributions. However, in this paper, the researchers have developed an approach to apply the possibility theory instead of the probability theory. Instead of using absolutely qualitative methods, this new approach applies the Dempster–Shafer Theory. It is obvious when there are insufficient data; an index is needed to make a decision. Then, a novel method is proposed and used in a real case study in order to determine the reliability of production systems based on risk when the available data are not sufficient, helping us to make decisions. After calculating the failure probability and analyzing the assessment matrix and risk criteria, we may conclude that the failure risk of equipment is reduced while the system reliability is increased.     

基于故障树与贝叶斯网络的钻井井塌事故的定量分析

井塌事故在钻井过程极其常见,由于钻井液、井身结构等设计不合理,以及钻井过程的误操作均会造成井塌的发生,其后果主要是造成卡钻、卡套管等事故,严重时造成井眼毁坏。为了对井塌事故进行危险性分析,采用贝叶斯网络与故障树相结合的方法,避免传统故障树方法的局限性。首先对井塌事故的所有危险因素进行辨识建立故障树,然后将故障树转化为贝叶斯网络,建立条件概率表,运用贝叶斯网络的推理能力对井塌事故进行危险性分析。对井塌事故各基本事件概率分布的计算分析结果表明,考虑事件的多态性,综合利用故障树分析法和贝叶斯网络法能有效提高井塌事故分析的有效性,推算出井塌事故概率分布更为准确。     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

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.