Corrosion failure probability analysis of buried gas pipelines based on subset simulation

Corrosion is the main reason for the failure of buried gas pipelines. For effective corrosion failure probability analysis, the structural reliability theory was adopted in this study to establish two calculation models for pipeline corrosion failure: the pressure failure model and von Mises stress failure model. Then, two calculation models for the corrosion failure probability were established based on a corrosion depth growth model obtained from actual survey data of soil corrosion characteristics. In an example, Monte Carlo simulation (MCS) and subset simulation (SS) were used to analyze the corrosion failure probability of pipelines, and the results were compared. SS can compensate for the shortcomings of MCS as it has higher computational efficiency and accuracy. Therefore, SS was adopted to simulate variations in the corrosion failure probability of buried pipelines with the service time for the two failure probability calculation models, which were applied to a natural gas pipeline located in a chemical industry park in Zhuhai, China. A sensitivity analysis was carried out on the relevant parameters that affect the failure probability. The results showed that multiple loads caused by the covering soil, residual stress, temperature differential, and bending stress have a non-negligible effect on the pipeline reliability. The corrosion coefficients gradually become the most important factors that affect the failure probability with increased service time. The proposed methodology considers the actual operating conditions of pipelines to provide a reliable theoretical basis for integrity management.     

基于ANSYS的可靠度分析方法及应用

通过对可靠度分析的概述理解到现代工程分析中实体模型不确定因素众多,进而带来分析的不准确性。基于有限元分析软件ANSYS提供的概率设计系统(PDS)的概率分析功能,使对结构的概率分析非常容易。根据结构的失效模式来确定结构功能函数,由此建立结构极限状态方程,再运用结构可靠度分析中的蒙特卡洛法(MCS法)利用结构的失效频率来估算其失效概率。在本文中提出了利用ANSYS的概率分析功能结合MCS法进行结构的可靠性分析的方法,并通过一个实例具体说明了利用ANSYS的概率分析功能实现结构的可靠性分析的可行性。     

隧道地层变位的可靠性分析

分析了隧道与围岩设计中的不确定性因素 ,指出由于隧道及岩土参数分布的随机性 ,地层变位具有不确定性。运用ANSYS有限元程序建立隧道地层变位的计算模型 ,进行数值模拟并取得地层变位的原始数据。在此基础上把主要影响因素视为随机输入变量 ,地层变位为随机输出变量 ,采用蒙特卡洛方法模拟出地层位移的统计值 ,进而计算出地层变位的可靠指标与失效概率 ,并通过相关系数矩阵和概率灵敏度图分析了随机输入参数对地层变位的影响 ,为隧道地层变位的可靠性分析提供了一种新的途径。     

An optimization of artificial neural network modeling methodology for the reliability assessment of corroding natural gas pipelines

A fast calculation of the reliability is meaningful to the in-line inspection of corroding natural gas pipelines. However, the traditional Monte Carlo simulation(MCS) method is time consuming for the low possibilities of the pipeline failure. The artificial neural network(ANN) is preferable for the complex nonlinear situation. An optimization of artificial neural network modeling methodology for the reliability assessment of corroding natural gas pipelines is proposed in this paper. To reduce the influence of training sets random behaviors on the calculation results, some algorithms are used to optimize the sequence of the training samples and the initial parameters of ANN models. The optimized model is applied to the reliability assessment of a corroded pipe with two successive inline inspections. According to the physical parameters of the pipeline, the trend of corroding pipeline reliability in time is predicted. The comparison between the trained ANN model, the MCS method and non-optimized ANN model shows the advantages the proposed modeling process. The methodology given in this paper is general and it can be applied to evaluate the reliability of other kind of structure safeties in practical systems.     

第三方挖掘作用下管道可靠性评估研究

为研究第三方损坏中挖掘作用对管道可靠性的定量影响,阐述了第三方挖掘作用下管道失效模式与失效机理,确定了管道第三方挖掘作用下的2个极限状态:穿孔失效和凹陷—划伤失效,提出了1种综合考虑管道运行及管理条件,建立了管道第三方挖掘极限状态方程求解其失效概率的模型。以某长输天然气管道为例,基于蒙特卡洛模拟计算了研究管段的失效概率值,并进行了参数的敏感性分析。结果表明,该方法能够定量描述第三方挖掘对管道可靠性的影响程度,评估结果便于管理者制定相应的维修维护策略。     

基于模拟的腐蚀管道可靠性分析

腐蚀失效是压力管道失效的主要模式之一。通常采用腐蚀管道剩余强度估算的方法 ,评价腐蚀管道的安全性。腐蚀管道的剩余寿命则采用可靠性理论计算得到。以各种局部腐蚀缺陷的评定方法来建立模拟模型 ,直接采用蒙特卡罗模拟可以计算得到不同时间下的管道的失效概率 ,同时根据目标可靠度来确定腐蚀管道的剩余寿命。含多个腐蚀缺陷的管道的失效概率需要考虑缺陷间的相关性。采用模拟方法可以计算失效概率的秩相关 ,避免采用独立假设来计算管道的失效概率     

生命周期评价中清单的不确定性分析

生命周期评价中存在着广泛的不确定性,尤其是生命周期评价中清单的不确定性因素会严重影响研究结果的可信性.结合生命周期清单中不确定性的特点,指出不确定性分析的作用.综述目前常用的生命周期清单的不确定性分析方法,包括在不确定性评估中常用的质量指标法、蒙特卡罗(Monte Carlo)法、结合法及常用的敏感性分析方法.指出各种方法存在的优缺点以及在实际中的应用,最后提出生命周期清单中不确定性分析的研究方向.     

基于FITNET FFS模型的腐蚀管道失效概率敏感性分析

为了获取影响腐蚀管道失效概率的关键因素及敏感性规律，基于FITNET FFS模型，采用可靠性理论对国内某腐蚀管道的失效概率进行计算和分析。通过全寿命方法计算了腐蚀增长速率，从而得到了与时间相关的腐蚀管道损伤概率模型，并采用蒙特卡罗模拟算法进行求解，得出了不同年限下腐蚀管道的失效概率；采用变异系数法对各影响因素进行参数敏感性分析。研究结果表明:管道直径、壁厚及径向腐蚀速率的分散性对管道失效概率具有双向扰动作用，其机理在于随机变量的分散性和腐蚀速率同时影响失效概率的波动，开始阶段随机变量分散性起主导作用，两者在管道失效概率达到50%会趋于一个平衡状态，之后腐蚀速率起主要支配作用；另外，管材的抗拉强度对腐蚀管道失效概率的影响较屈服强度的影响更大，可靠性分析时采用只考虑屈服强度的强度模型将存在一定的局限性，建议同时考虑管材抗拉强度的影响。     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

基于子集模拟的埋地管道失效概率评估

对失效概率的评估是管道系统风险评价的核心内容,针对目前对埋地管道失效概率问题研究的不足,采用子集模拟方法（SS）建立埋地管道失效概率的定量评估模型以及参数敏感度模型,并对随机变量进行敏感分析。研究结果表明:子集模拟能利用少量样本定量计算出管道失效概率,有效弥补了管道结构可靠性模型中的不足;在管道运行中期,工作压力、腐蚀速率、管道壁厚和屈服强度是对管道失效概率影响较大的4个因素,而腐蚀因素在管道运行后期成为对系统失效概率影响最大的因素。     

可控震源振动器系统不确定性分析

为了解决可控震源施工过程中振动器系统的安全性问题,采用故障树法建立仿真 模型。通过失效分析得出各故障单元的失效模式及单元间分布规律,计算出振动器系统 的可靠度。开展对该系统敏感性的不确定性分析,得出影响振动器系统可靠性的关键因 素为重锤上部密封失效。采用有限元法对其应力场进行模拟仿真。结果表明:随着工作 频率的升高,O形圈应力波动越大,密封越容易失效。Von Mises应力随压缩率的增大先 减小后增大,随槽口半径的增大而增大;接触应力在一定范围内随压缩率及槽口半径的 增大而增大。为振动器的结构优化与可靠性设计提供理论依据,并为油气资源勘探开发 的安全作业提供工程应用指导。     

基于Matlab的火灾探测报警系统可靠度Monte Carlo仿真

介绍了火灾探测报警系统的结构,指出了火灾探测报警系统失效原因,针对火灾探测报警系统的特点,确定了蒙特卡洛可靠度分析法.给出了系统的概率模型,确定了在Matlab下应用Monte Carlo方法对火灾探测报警系统的可靠度进行仿真的具体步骤,得到火灾探测报警系统可靠度仿真曲线.将仿真结果与试验结果相比较,基本一致,验证了该仿真方法能正确描述火灾探测报警系统的可靠度随使用寿命的变化规律,为进一步应用该方法来分析火灾探测报警系统的的各可靠性指标提供了理论基础.     

Reliability assessment of ultra-deep oil and gas wellbore casing using data statistics and numerical simulations

Ultra-deep oil and gas wells have become a new development trend in onshore oil and gas exploitation. However, Ultra-deep oil and gas wellbore casing is with high failure risk due to the harsh environment. It is essential to evaluate the reliability of wellbore casing. This paper assesses the operational reliability of wellbore casing using data statistics and numerical simulation. Firstly, the theoretical model for reliability analysis of wellbore casing is established, and the variables in the model are determined, including rock mechanics, cement ring, and casing string strength factors. Subsequently, considering the random distribution of model variables, many statistics and analyses are performed to determine the distribution parameters of the model variables. Eventually, Monte Carlo based numerical simulations are carried out to obtain the residual strength distribution and the reliability of wellbore casing. The production casing in the ultra-deep well with a depth of 6.5 km in China as an industrial case is used to illustrate the present study. It is observed that this study can be useful to guide a more accurate assessment of the reliability of ultra-deep wellbore casing.     

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.     

接管高应变区缺陷的安全评定概率方法研究

随着计算机技术飞速发展,Ｍｏｎｔｅ Ｃａｒｌｏ 法在压力容器可靠性分析中得到广泛应用。但对于小概率情形,利用直接抽样的Ｍｏｎｔｅ Ｃａｒｌｏ 法进行失效概率计算,费用较高。为此,笔者提出了几种新的失效概率近似计算方法,并以压力容器接管为例,对其断裂失效概率进行了计算,同时还和直接抽样的Ｍｏｎｔｅ Ｃａｒｌｏ 法的计算数值进行了比较。结果表明,新的失效概率近似计算方法具有精度高、节省机时的优点。     

Comprehensive framework for underground pipeline management with reliability and cost factors using Monte Carlo simulation

A reliability model for underground pipeline management that can quantify the trade-off between risk reduction and increased maintenance costs in various underground piping management scenarios can be useful for many pipeline-maintenance decision-makers. In this paper, we propose a comprehensive framework for analyzing underground pipeline management options. Pipeline reliability is calculated using time-dependent and independent limit state functions with a probabilistic model and a deterministic model about the frequency of a failure occurrence event. The proposed framework includes the target reliability, consequences, and cost model, and has the advantage that it can be intuitively utilized for piping management decision-making. We conducted several case studies using a Monte Carlo simulation on pipelines in industrial complexes in Korea.     

System failure probability evaluation using fault tree analysis and expert opinions in intuitionistic fuzzy environment

In quantitative fault tree analysis of a system, exact failure probability values of components are utilized to calculate the failure probability of the system. However, in many real world problems, it is problematic to get precise and sufficient failure data of system components due to insufficient or imprecise information about components, changing environment or new components. A methodology has already been developed by employing fuzzy set theory for the system reliability evaluation by utilizing qualitative failure data of system components when quantitative failure data of components are inaccessible or insufficient. This paper extends the concept of fuzzy set to intuitionistic fuzzy set and proposes a novel approach to evaluate system failure probability using intuitionistic fuzzy fault tree analysis with qualitative failure data of system components. The qualitative failure data such as expert opinions are collected as linguistic terms. These linguistic terms are then quantified by triangular intuitionistic fuzzy numbers in form of membership function and non-membership function. Additionally, a method is developed for combining the different opinions of experts. To illustrate the applicability of proposed approach, a case study of the crude oil tank fire and explosion accident is performed. The obtained results are very close to the results from pre-existing approaches which confirm that the proposed approach is a more realistic alternative for the study of system reliability in intuitionistic fuzzy environment when quantitative failure data of system components are not known. To help decision makers for improving the security execution of the crude oil tank system, importance measures including Fussell-Vesely importance and cut sets importance are also executed.     

油气管道腐蚀可靠性的贝叶斯评价法

对油气管道腐蚀危害因素进行分析,建立其失效故障树。根据故障树分析原理,找出导致管道腐蚀穿孔破坏的23个因素。通过对故障树的定性分析,采用下行法求出油气管道腐蚀失效故障树的96个全部最小割集,并确定失效的主要影响因素。结合最小割集不相交化法和贝叶斯可靠性评定法对管道腐蚀失效进行定量分析,通过某油气管道事故统计数据,利用贝叶斯可靠性评定方法求出油气管道腐蚀可靠性的一阶矩和二阶矩。对一阶矩和二阶矩进行拟合,求出油气管道腐蚀可靠性的第一近似下限和第二近似下限。结果表明:得出的油气腐蚀管道贝叶斯可靠性评价结果可以指导管道系统的维护和维修,降低管道运行的风险。     

考虑冰风载荷影响的输电线路运行风险评估方法*

为预防在极端冰灾环境下大规模停电事故的发生，提出1种考虑冰风载荷的输电线路运行风险评估方法。在极端冰风环境下，计算输电线路与杆塔所承受的总载荷，利用强度与应力干涉模型确定输电线路与杆塔的故障率，同时结合串联可靠性原理确定线路故障综合概率；利用非贯序蒙特卡洛法与线路故障综合概率设置预想故障集，结合直流潮流优化模型计算每条线路的失负荷量；综合考虑负荷等级与抢修恢复时间，确定线路失负荷的经济价值并定义为故障后果；将故障后果与线路故障综合概率的乘积定义为输电线路风险评估指标。以实际拓扑结构修正的IEEE30节点开展算例分析。结果表明:所提方法可对输电线路运行风险进行有效评估。     

基于贝叶斯网络的人因可靠性评价

提出一种贝叶斯网络的人因可靠性评价(HRABN)方法,其中的每个因子对应于贝叶斯网络中的节点,该方法可对人因可靠性作定量分析和定性分析。在定性分析上,节点的因果关系(HRA中的因子关系)及需要改进的薄弱节点都直观地显示在层次图中;在定量分析方面,对节点因子后验概率的推断通过HRA中的先验信息(包含仿真数据、现场操作及专家知识等)和最新信息得到。如果人因可靠性贝叶斯网络中的每个节点的先验概率分布和后验概率分布都已知,模型的可信性就可通过贝叶斯因子进行定量验证。贝叶斯网络扩展性好,当有新的节点因子需要考虑时,只需要补充对应的节点;笔者的方法也能很好地应用在不同行业的HRA。