基于动态贝叶斯网络的城市综合管廊燃气泄漏动态风险评价

为解决综合管廊燃气管网系统风险因素多、风险状态随时间动态变化等问题，在传统故障树和静态贝叶斯网络等方法的基础上提出了基于动态贝叶斯网络的城市综合管廊燃气泄漏动态风险评价方法。首先利用蝴蝶结模型分析总结了导致综合管廊燃气管网发生泄漏的主要风险源和不同事故后果。然后，引入时间因素与Leaky Noisy-or Gate模型，根据故障树模型的映射规则，建立城市综合管廊燃气泄漏的动态贝叶斯网络模型。最后，利用动态贝叶斯网络的双向推理功能对模型进行求解。由实例分析得到了某综合管廊燃气泄漏概率及各事故后果概率的时序变化曲线，通过反向推理得到了导致燃气泄漏的主要风险源。研究成果可为综合管廊的风险评估、日常维护提供理论支持。     

“三高”气田钻井过程硫化氢泄漏动态风险分析

传统的H2S泄漏风险分析方法不能很好地对事故发展过程进行动态分析,导致分析结果偏离实际。基于贝叶斯方法,构建了高温、高压、高含硫（“三高”）气田钻井过程中H2S泄漏的蝴蝶结模型并提出将其转化为贝叶斯网络,在事故已发生的情况下更新基本事件发生的概率。然后,假定事故后果在确定的时间段内发生的累积次数已知的条件下,更新安全屏障及事故后果发生的概率,从而完成对H2S泄漏的动态风险分析。结果表明,该方法克服了传统静态定量分析方法中的不足,可动态评估导致H2S泄漏的基本事件发生的概率和对顶事件发生的影响程度,并动态反映安全屏障和事故后果的风险变化,能为钻井过程中H2S泄漏的风险分析及防控措施提供参考。     

海底油气管道泄漏事故风险分析的贝叶斯动态模型

为研究海底油气管道泄漏事故风险的动态性,预防重大事故发生,针对传统风险分析方法的局限性,基于安全屏障和事件树分析,建立海底管道泄漏事件序列模型。根据事故先兆数据和贝叶斯理论,对安全屏障的失效概率进行实时动态更新。最后,由事件树的逻辑关系得出不同泄漏场景的发生概率。结果表明:用上述的基于事件序列模型和贝叶斯理论的方法,能够克服传统风险分析方法的不足,描述不同泄漏场景发生概率随时间变化的动态特征,实现对海底管道泄漏事故风险的动态分析。     

燃气管网定量风险分析方法综述

以城市燃气管网的风险为研究对象,分析并提出一种可用于城市燃气管网定量风险分析的新思路,包含了不同事故后果及其物理模型的分析即事故可能性分析、后果分析和风险评价,分为失效事故假定、泄漏率计算、物理效应计算、致死率计算、风险值计算、风险评价等环节;整理、研究城市燃气管网定量风险分析所涉及的多种物理模型,并通过比较不同模型的特点,分析各个模型的不足之处;最后针对国内外研究现状及燃气管网风险的特点,指出研究发展方向:研究风险在燃气管网内的传播,提出燃气管网相继失效的风险分析方法。所提出的分析思路、计算方法可与工程应用相结合。     

一种城市燃气管网泄漏风险动态计算模型

为科学地评估并及时控制城市燃气管网泄漏的风险,采用贝叶斯网络(BN)与地理信息系统(GIS)相结合的方法,建立燃气管网泄漏风险动态计算模型。首先,利用故障树(FT)系统地分析管网泄漏事故,考虑到管网服役时间和外界干扰事件的动态性,将建成的FT映射到BN中,进而动态计算燃气管网的泄漏概率;然后运用GIS技术对管网泄漏后果的严重度指标进行赋值,并将动态泄漏概率和后果严重度值结合,建立上述模型;最后,以某区域的燃气管网为研究对象,验证该模型的有效性。结果表明:该模型能够综合时间因素以及突发事件对管网泄漏的影响,实现对管网泄漏风险的动态计算和可视化显示。     

基于前导事件和贝叶斯网络的储罐溢油动态风险评价

部分高风险危化品企业搬迁改造困难重重,为控制风险、保护周围人民生命和财产安全,有必要建立动态风险评价系统,对事故发生概率进行监控和预测。采用贝叶斯网络对事故发生概率进行定量分析。先在利用蝴蝶结模型辨识事故原因和后果的基础上,将其转化为贝叶斯网络模型;再导入"前导事件"信息和先验概率推导后验事故发生概率,量化分析事故发生随时间的变化概率;最后,以储罐溢流场景为例进行动态风险计算,结果表明,随化工装置生产时间和"前导事件"增长,元件失效概率和事故风险呈显著增长趋势。因此建议企业应重视"前导事件"并采取措施减少"前导事件",如优化检维修方案、及时更换关键部件、进行全面的事故调查等。     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为（Unsafe Human Behaviors,UHBs）对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析。构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,将不同等级高后果区划分为不同等级人口敏感区;利用专家经验评判法得到不同等级人口敏感区基本事件的先验概率和中间事件的条件概率表;运用贝叶斯网络双向推理算法求解模糊Bow-tie模型。结果表明:随着地区人口敏感等级的提高,输气管道泄漏燃爆事故发生的概率随之增大,发现导致输气管道失效泄漏事故发生的最主要原因为施工破坏,失效原因与EGIG分析的结果基本相符,验证该方法在高后果区输气管道泄漏燃爆事故分析上的可行性,可为输气管道高后果区的安全管理提供决策依据。     

不完全信息条件下的FPSO油气泄漏风险分析

为解决数据稀缺情况下的浮式生产系统(FPSO)油气泄漏重大事故风险评价问题,引入新的层次贝叶斯风险分析(HBA)方法。首先,基于安全屏障和事件树分析,建立FPSO油气泄漏事件序列模型;其次,根据事故先兆数据和贝叶斯推断,对安全屏障的先验分布增加一层估计,得到FPSO油气泄漏连锁事故的发生概率;最后,通过实时更新屏障失效概率,实现对FPSO事故风险的动态定量分析。结果表明:HBA法可以充分利用稀缺数据,并从相关数据中添加先验信息,得到各参数的后验概率,并据此确定,初始的油气泄漏大多会演变为大范围泄漏和小范围火灾。     

基于故障树-贝叶斯-蝴蝶结分析的复合事故风险模型研究

为解决现有单一风险评价方法存在的不足,引入了基于故障树分析、贝叶斯网络与Bow-tie分析(蝴蝶结分析)相结合的复合风险分析模型:首先找出引起故障的基本事件,绘制故障树(FTA)模型;然后以故障树模型为基础,将其转化为贝叶斯网络,计算其中基本事件的后验概率和重要度;最后对重要度等级较高的事故节点进行Bow-tie分析,提出预防事故发生的防护措施和减轻事故后果的控制措施。以粘结漏钢事故为例,应用该模型对粘结漏钢事故进行了系统风险分析,验证了该模型的科学性和合理性,其结果表明:引起粘结漏钢事故占比较大的事故节点为保护渣异常,结合风险分析结果提出了相关预防及控制措施,以期最大程度地降低事故发生概率及减小事故损失的目的。     

基于改进Bow-tie模型的城镇燃气管网风险分析

燃气管网是城镇中的重大危险源,一旦发生事故,后果多数较为严重。为更清晰地了解事故发生原因、后果,制定预防、减缓措施,笔者提出改进Bow-tie模型对城镇燃气管网进行风险分析。改进Bow-tie模型从人、机、环、管四方面分析事故原因,从人员、财产、环境、社会四方面分析事故后果,将风险识别、风险分析、风险评估、风险控制、风险管理在图中展示,并为燃气管网事故提出预防和减缓措施,降低事故率。结果表明应用改进Bow-tie模型可直观掌握事故全过程动态,清晰了解事故的起因、结果,对分析燃气管网泄漏事故具有重要意义。     

Dynamic failure probability analysis of urban gas pipeline network

The gas pipeline network is an essential infrastructure for a smart city. It provides a much-needed energy source; however, it poses a significant risk to the community. Effective risk management assists in maintaining the operational safety of the network. The risk management of the network requires reliable dynamic failure probability analysis. This paper proposes a methodology of condition monitoring and dynamic failure probability analysis of urban gas pipeline network. The methodology begins with identifying key design and operational factors responsible for pipeline failure. Subsequently, a causation-based failure model is developed as the Bowtie model. The Bowtie model is transformed into a Bayesian network, which is analyzed using operational data. The key contributory factors of accident causation are monitored. The monitored data is used to analyze the updated failure probability of the network. The gas pipeline network's dynamic failure probability is combined with the potential consequences to assess the risk. The application of the approach is demonstrated in a section of the urban gas pipeline.     

基于贝叶斯网络的页岩气集输管道失效概率计算方法研究

页岩气集输管道运行压力和出砂量在生产过程中衰减显著，这导致管道失效概率不断变化，针对这一问题，采用贝叶斯网络方法，建立了页岩气集输管道失效概率动态计算模型。首先，分析页岩气气质特征、管道运行工况及失效原因，利用逻辑门的连接关系，建立了页岩气集输管道失效故障树；其次，基于贝叶斯网络与失效故障树的结构映射关系，将失效故障树转化成贝叶斯网络结构；然后，通过贝叶斯网络的参数学习，实现模型求解；最后，进行了实例应用。研究结果表明:该模型不仅可有效计算页岩气集输管道的失效概率，还能确定影响管道失效的关键风险因素，并且可通过调整节点的状态及概率分布，实现页岩气集输管道失效概率的更新。     

基于贝叶斯网络的物流无人机失效风险评估*

为降低城市物流无人机（UAV）失效坠落风险，通过考虑其运行环境和系统故障等因素的影响，以城市物流无人机运行数据为基础，从系统故障、运行环境和人为因素3方面提取失效诱因；分析物流无人机失效模式，并构建意外坠落事故的贝叶斯网络；基于所建网络和失效诱因发生概率分别计算不同工况下意外坠落事故及各中间事件概率，并基于网络拓扑结构展开反向推理，推演事故的主要失效诱因。结果表明:物流无人机正常运行时发生安全事故的概率为6.54×10-3；其中，电池电量不足、桨叶失效和电池故障是坠落事故的主要诱因，计算结果可为无人机运行安全风险防控提供依据。     

Integrated dynamic risk assessment of buried gas pipeline leakages in urban areas

In urban areas, buried gas pipeline leakages could potentially cause numerous casualties and massive damage. Traditional static analysis and dynamic probability-based quantitative risk assessment (QRA) methods have been widely used in various industries. However, dynamic QRA methods combined with probability and consequence are rarely used to evaluate gas pipelines buried in urban areas. Therefore, an integrated dynamic risk assessment approach was proposed. First, a failure rate calculation of buried gas pipelines was performed, where the corrosion failure rate dependent on time was calculated by integrating the subset simulation method. The relationship between failure probability and failure rate was considered, and a mechanical analysis model considering the corrosion growth model and multiple loads was used. The time-independent failure rates were calculated by the modification factor methods. Next, the overall evolution process from pipeline failures to accidents was proposed, with the accident rates subsequently updated. Then, the consequences of buried gas pipeline accidents corresponding to the accident types in the evolution process were modeled and analyzed. Finally, based on the above research, dynamic calculation and assessment methods for evaluating individual and social risks were established, and an overall application example was provided to demonstrate the capacity of the proposed approach. A reliable and practical theoretical basis and supporting information are provided for the integrity and emergency management of buried gas pipelines in urban areas, considering actual operational conditions.     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines.     

基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*

为分析海底管道运行中存在的泄漏风险,提出1种基于毕达哥拉斯模糊数与贝叶斯网络的风险评估模型。首先,通过毕达哥拉斯模糊数转换专家定性评价,拓展专家意见模糊范围;然后,结合主客观组合赋权法,利用毕达哥拉斯梯形爱因斯坦混合几何算子（PTFEHG）实现专家意见的聚合;最后,通过贝叶斯网络的推理与敏感性分析,计算海底管道泄漏风险的失效概率,并辨识关键风险因素。研究结果表明:该方法可以结合专家意见对海底管道泄漏风险进行定量分析,并识别导致泄漏事故的关键风险因素,对海底管道安全管理具有指导意义。     

城市燃气管网泄漏事故分析知识图谱构建及应用研究*

为深入认识燃气管网泄漏事故的发生发展机理,提高事故分析预测的自动化、智能化、数字化水平,利用知识图谱对燃气管网泄漏事故进行研究。在事故案例分析的基础上,从人-物-环-管的角度对燃气泄漏过程以及火灾爆炸次生事故的相关实体进行归纳梳理,对实体间的逻辑关系和非逻辑关系进行辨识,并对实体的属性进行分类,进而构建出较为全面的燃气管网泄漏事故知识图谱。在此基础上,搭建BP神经网络模型,基于已知实体或属性状态,预测相关联其他实体或属性的状态。研究结果表明:燃气管网知识图谱能够有效展示燃气管网泄漏事故发展的动态过程及相关要素,结合BP神经网络能够有效预测事故的发展路径及相关状态,从而提高燃气管网泄漏事故的分析预测水平与效率。