气相管道小孔泄漏压力响应试验与仿真研究

管道压力是进行泄漏速率计算和泄漏后果模拟的重要参数,采取试验与数值模拟相结合的方法对小孔泄漏压力响应进行研究。以中国石油大学(华东)泄漏及气体扩散测试试验系统为平台,建立了试验系统的Flowmaster模型,并通过试验数据对模型进行验证。结果表明,试验系统可以用来研究小孔泄漏管道内的压力响应情况并准确计量泄漏速率,可以基于Flowmaster模型预测复杂工况下小孔泄漏管道内的压力响应情况,并且能够较为精确地计算泄漏稳定后管道内的平均压力。     

考虑工艺控制的海底长输气相管道泄漏规律研究

为了研究海底管道泄漏规律,评估管道泄漏风险,建立了海底长输管道泄漏模型,研究了不同孔径、持液率及管道高程对泄漏过程的影响,探讨了在不同响应时间下的泄漏总量及介质损失。研究结果表明:泄漏速率随泄漏孔径增大而增大,小孔泄漏或管道破裂时,泄漏速率上升较缓;管道内持液率低于0.08%时,液体含量对管道泄漏点压力及泄漏速率的影响较小,大于此值时,随着持液率的增加,管道压力及泄漏速率明显降低;对于不同响应时间下的总泄漏量,响应时间越长,泄漏量越大,直接经济损失越高。研究结果可用于海底天然气管道泄漏风险分析及事故预警。     

长输天然气管道事故泄漏速率算法改进研究

泄漏速率是模拟天然气泄漏过程中计算事故后果的重要指标之一,速率通常由小孔泄漏和大孔泄漏推导得出。但在实际泄漏时,泄漏孔径的大小往往不易及时获得,需要通过保守算法估算泄漏口面积以进一步模拟事故后果。运用流体力学和热力学方法,对天然气泄漏速率的经验公式进行了推导验证。同时使用连续性方法对管道的泄漏速率深入探讨,使用更易测量参数参与计算,使得在发生突发泄漏事故的时候,可以忽略孔径大小以更快速的获得泄漏信息,计算泄漏后扩散影响面积,从而为计算事故后果提供依据,以指导应急救援。     

埋地成品油管道泄漏强度模型与试验验证

针对泄漏事故频发的埋地成品油管道,搭建埋地成品油管道泄漏试验平台,以柴油为输送介质开展试验。通过试验获得,管道泄漏量及泄漏强度随输油压力和泄漏孔面积增大而逐步增加,在输油压力较小时,泄漏孔位置对管道泄漏量及泄漏强度有影响,但随着输油压力的逐步增加,泄漏孔位置对泄漏量及泄漏强度的影响逐渐减小。同时根据伯努利方程推导得出埋地成品油管道泄漏强度模型,将试验参数代入模型,对比模型计算值与试验数据,结果表明,计算结果与试验数据吻合良好,验证了模型的正确性,可用于指导埋地成品油管道泄漏事故的定量风险评价及处理。     

管道压力对天然气射流火热辐射灾害的影响

天然气管道时常受到破坏,并诱发巨大的射流火焰,可能引燃周围建构物体。系统地分析了管道压力对天然气射流火热辐射灾害的影响,以建立天然气射流火热辐射灾害的系统定量分析方法。基于压力管道小孔泄漏模型和权重-多点源热辐射计算模型,建立了目标物体最大入射热辐射通量、管道压力和目标物与泄漏小孔水平距离的定量关系式。进而选定10 k W/m~2和31.5 k W/m~2作为城镇建筑物遭受引燃和机械破坏的热辐射通量阈值,得到了不同管道压力下天然气射流火热辐射灾害范围。计算结果表明,GB 50028—2006《城镇燃气设计规范》依据管道压力所规定的燃气管道与建筑物的安全间距不能完全满足天然气管道破坏时射流火焰的安全要求,与某武汉天然气管道射流火事故后果一致。     

超临界二氧化碳泄漏减压模型构建及泄漏量分析

为了解决超临界二氧化碳管道泄漏风险评估问题,基于工业规模超临界二氧化碳小孔泄漏试验结果,提出分别构建超临界泄漏阶段、气液两相泄漏阶段、气相泄漏阶段的理论模型,并通过确定各阶段的传递参数,实现二氧化碳减压过程的理论建模。采用MATLAB软件编制了模型求解程序。通过试验数据验证了理论模型的可靠性。基于理论模型计算结果定量探讨了初始压力、初始温度和泄漏口径对泄漏减压过程压力及质量流量的影响。结果表明：初始压力在8～9.5 MPa变化时,对减压过程压力及泄漏质量流量影响较小;初始温度在33～39℃变化时,压力降至临界值的时间逐渐增加;泄漏口径减小,压降时间显著变长;在泄漏减压初期,泄漏质量流量均出现波动,随后随压力降低而逐渐降低。构建的理论模型能够实现超临界二氧化碳泄漏质量流量预测。     

基于FERC模型的油品流淌火灾定量风险评估方法研究

为了评价油品储运过程中的流淌火灾风险,提出1种基于FERC模型的油品流淌火灾定量风险评估方法。以某汽油管道为例,分析大孔泄漏、中孔泄漏、小孔泄漏３种模式下流淌火各参数的动态变化过程,计算管道周边不同位置处的个人风险值。研究结果表明:流淌火燃烧面积的最大值随泄漏速率的增加而增大,对于给定的算例条件,大孔泄漏情景下的最大燃烧半径较小孔泄漏增大了18.4倍;相较小孔泄漏,大孔泄漏下安全距离增大了6.7倍;在距离泄漏点100 m的位置,小孔泄漏、中孔泄漏和大孔泄漏条件下的辐射热流密度值分别为0.13,1.34,8.02 kW/m2;距离泄漏点34 m处时,大孔泄漏已经占总个人风险的99%;在开展风险评价时,应着重分析大孔泄漏的情景。     

埋地燃气管道泄漏扩散过程数值模拟

为减少天然气输送过程因泄漏引发的安全问题,构建埋地燃气管道泄漏扩散过程的三维计算流体动力学(CFD)模型,研究管道入口压力、泄漏孔尺寸、泄漏孔形状和土壤孔隙率等各参数对泄漏量与扩散范围的影响,拟合埋地管道燃气泄漏量与各参数的经验关联式,并通过公开文献中的试验数据进行验证。结果表明:泄漏量与扩散距离都随着管道入口压力、土壤孔隙率和泄漏孔尺寸的增大而增大,管道直径和泄漏孔形状对泄漏量的影响较小;在设定管道入口压力为2.1和156 k Pa的条件下,拟合的经验关联式计算值与试验值的误差分别为7.18%和19.79%,证明关联式具有其有效性,可为计算埋地管道燃气泄漏量提供理论指导。     

含硫天然气管道中毒潜在影响半径计算方法

含硫天然气的泄漏会造成人员中毒,严重威胁管道附近人员的生命安全,ASME标准中推荐的潜在影响半径计算模型不适用于含硫天然气管道。常用气体扩散模型忽略泄漏气体的喷射作用导致中毒影响半径计算结果过于保守,因此首先分析含硫天然气管道泄漏特点,考虑泄漏气体喷射高度和泄漏速率的变化对硫化氢地面体积分数的影响,基于天然气泄漏扩散规律建立了不同时刻烟团和烟羽体积分数叠加表征的硫化氢中毒潜在影响半径R计算模型。考虑截断阀紧急关闭影响,按照30 s时间提出了泄漏速率分段计算依据,并合理确定了瞬时泄漏气团质量Q、连续性泄漏源强q、扩散参数以及泄漏气团中心高度H等基本参数。针对不同压力、管径、硫化氢体积分数条件,进行了中毒影响半径、热辐射潜在影响半径及忽略喷射高度的影响半径对比分析,合理提出了按照中毒潜在影响半径确定含硫天然气管道潜在影响半径的计算方法。     

基于量纲分析的输液管道泄漏量计算模型研究

在实验室建立管道泄漏实验模型(江苏工业学院油气储运安全实验系统),研究管道在不同泄漏模式下、不同实验条件下的流体泄漏量的规律。运用量纲分析的方法,建立了管道泄漏数学模型,初步确立了泄漏量与泄漏孔的大小、流体的密度、黏度、管内压力以及流体的平均流速等因素的关系,为进一步定量分析管线失效后对环境的影响提供了科学依据。     

Probabilistic multiple model neural network based leak detection system: Experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.     

Leak detection for long transportation pipeline using a state coupling analysis of pump units

Leak detection for long transportation pipeline with a large economic and environmental impact has been an area of intensive research for more than five decades. This paper presents a novel pipeline leak detection scheme based on a state coupling analysis (SCA). Instead of monitoring the pipeline and pump units separately, SCA introduces a new detecting method of analyzing data in a coupling running condition. A novel capture method for abnormal pressure based on logical reasoning algorithm is proposed. Hamming approach degree arithmetic is applied to calculate the matching mode identifying the state of units. SCA is used to reduce the rate of false alarm and detect the leak with a high detecting sensitivity for long transportation pipeline. An on-line software system based on SCA is utilized to achieve superior accuracy and implementation. An industrial case study for coupling system pipeline leak detection is used as an example to validate the effectiveness of the proposed method.     

Real-time leak detection in oil pipelines using an Inverse Transient Analysis model

Based on Inverse Transient Analysis (ITA) method, a real-time leak detection method is proposed to capture leak location and the associated leak rate in oil pipe conveyance systems. In the proposed approach, location and flow rate of leak (if any), the fluid properties, as well as physical parameters of the system, are calculated in consecutive periods through minimizing the discrepancy between the calculated and measured flow parameters of the system. The method of characteristics is employed to numerically calculate the transient responses of the system and the genetic algorithm is utilized as the optimization engine. The proposed approach was applied to several real pipeline systems in which the required transient flow data are either directly collected from the field or fabricated with a third-party numerical software. Extensive numerical explorations were conducted to investigate the performance of the proposed method in real-time leak detection and to determine the extent to which field data errors, stemming from Supervisory Control and Data Acquisition (SCADA) systems and measurement equipment, affect the leak flow rate and location detectability of the proposed approach. The results show that the proposed approach provides promising results under a variety of transient and steady-state flow conditions even in the case with small leak flow rate of around 2% of the line rate. The results also reveal that the noises in the measurement data and the errors originated from SCADA systems do not significantly compromise the leak detectability of the proposed approach, confirming that the proposed approach can be utilized in practice.     

Modelling Complex Pipeline Network Leak Detection Systems

A novel model for detecting leaks in complex pipeline network systems has been developed. The model derives from the theory of Liapunov stability criteria. A leak is detected if the resulting eigenvalues from the deviation flow matrix have values less than a predetermined value. An advanced mesh network algorithm was used to decompose the complex pipeline network system into sub-networks. The flow model (equations of motion and continuity) which incorporates a leaking factor, k_L, is solved by a numerical technique that uses the method of characteristics and an implicit finite function. The unsteady state flow matrix of the complex pipeline network system was analysed using a modified Hardy Cross algorithm, where the velocity and pressure were computed for each node and pipeline loop in the complex network. The plots for the characteristic pressure and velocity eigenvalues show that pressure measurements are faster parameters for leak detection than volume measurements. Volume measurements appear to be suitable for larger leak systems and longer response time.     

Inherently safer sustained casing pressure testing for well integrity evaluation

This paper presents the use of a model to predict sustained casing pressure (SCP), from early pressure buildup data, as a basis for inherently safer well integrity testing. Inherently safer principles aim to eliminate or reduce the hazards by design rather than by using protective features. SCP, a well integrity issue exhibited in many wells, is any measurable pressure that rebuilds after being bled down and attributable to causes other than artificially applied pressure or temperature fluctuations in the well. Intrusion of gas, resulting in SCP, can occur because of poor cement bond in the casing or cement deterioration. Gas entering the annulus migrates to the wellhead and represents a hazard due to increased wellhead pressure and the gas inventory. Compromised well integrity can have catastrophic consequences on both environmental and safety aspects.Most regulations require the monitoring, testing and, eventually, the elimination of SCP. However, test data analysis is predominantly qualitative and limited to arbitrary criteria. Due to the high percentage of wells that present SCP, accurate, safe and preferably fast testing methods are needed. This paper implements an analytical model, rooted in the transport processes and thermodynamics of the system, to predict pressure profiles and gas accumulation during SCP testing from early-time pressure buildup data. The amount of gas accumulated during different testing criteria, being 1) current practices and 2) early diagnostic by the analytical model, is calculated and compared. Results show that using the analytical model as a predictive tool, testing time is reduced significantly, thereby limiting the amount of gas accumulated and reducing the risk. This makes the testing procedure inherently safer as well as less time consuming.     

基于广义极值分布的流化床压力波动风险预警

为预警气泡运动所引起的流化床粉煤气化压力波动风险,提出预测压力波动极值以及压力波动重现水平的方法;首先采用自相关分析法将压力波动母样本数据合理分段,再用区间极值法统计子样本的压力波动极值数据,以广义极值(GEV)分布方法建立GEV分布模型和Gumbel分布模型,并经过模型诊断选择最优模型;然后通过子样本与母样本的参数关...     

A wave change analysis (WCA) method for pipeline leak detection using Gaussian mixture model

This paper presents a novel pipeline leak detection scheme based on gradient and slope turns rejection (GSTR). Instead of monitoring the pipeline under constant working pressure, GSTR introduces a new testing method which obtains data during the transient periods of different working pressures. A novel pipeline leak detection method based on those transient data without failure history is proposed. Wavelet packet analysis (WPA) is applied to extract features which capture the dynamic characteristics from the non-stationary pressure data. Principal component analysis (PCA) is used to reduce the dimension of the feature space. Gaussian mixture model (GMM) is utilized to approximate the density distribution of the lower-dimensional feature space which consists of the major principal components. Bayesian information criterion (BIC) is used to determine the number of mixtures for the GMM and a density boosting method is applied to achieve better accuracy of the distribution estimation. An experimental case study for oil pipeline system is used as an example to validate the effectiveness of the proposed method.     

中压天然气管道泄漏扩散模拟研究

建立了埋地中压天然气管道发生泄漏时时的数学模型,将土壤视为各向同性的多孔介质,采用FLUENT对天然气在土壤中的扩散规律及浓度分布进行模拟,分析不同时刻地表的危险区域范围,并对比了不同管道压力、泄漏孔径大小、泄漏位置等工况下危险半径随时间的变化。结果表明:管道压力越大,泄漏的体积流量越大,同一时间危险范围越大;相同的泄漏压力下,泄漏孔径对危险半径没有很大影响;不同泄漏孔位置,泄漏初期向上开口时危险半径最大,一段时间后向下开口危险半径最大。     

Leak detection of hydrogen–natural gas mixtures in pipes using the characteristics method of specified time intervals

This paper presents a technique for detection and location of leaks in a single pipe, by means of transient analysis, of hydrogen–natural gas mixtures flows. The method uses transient pressure waves initiated by the sudden closure of a downstream shut-off valve. The presence of a leak in a pipe partially reflects these pressure waves and allows for the location of the leak. Pressure waves are governed by two coupled non-linear, hyperbolic partial differential equations with pressure dependent coefficients. The fluid pressure and velocity are considered as two principal dependent variables. To determine the leak location, the mathematical formulation has been solved by the characteristics method of specified time intervals. The computed results describe the influence of the leak on pressure time-history and the effect of hydrogen mass fraction in the mixture on the leak discharge behaviour. It was found that transient pressure is much important in the case of hydrogen than that in the case of natural gas.     

A dual-sensor-based method to recognize pipeline leakage and interference signals

During the detection of pipeline leakages, false alarms of leak detection could be markedly reduced if the interference signals resulting from pressure regulating, pump regulating or valve movements could be accurately distinguished. A digital recognition method for interference signals and leakage signals based on a dual-sensor system is proposed in this paper. It is demonstrated that the direction of the signal can be recognized by a cross-correlation calculation between two signals from the dual-sensor, one of which undergoes forward linear interpolation and backward linear interpolation. Based on this theory, the interference signal and the leak signal can be discriminated exactly, and the distance between the two sensors in the dual-sensor system can be considerably reduced without needing to increase the sampling frequency. The monotonicity of the cross-correlation function is demonstrated, and a fast discrimination algorithm based on a binary extreme search method, which decreases the computational load and maintains global optimization, is also proposed. A pre-processing method of the actual signal is proposed to decrease the identity requirement for the two sensors in a dual-sensor system. In the experiment based on artificial signals, the proposed discrimination algorithm could achieve accurate recognition of the abnormal signal, and as such, the theory and application of pipeline leak detection based on dual-sensor systems are extended.