Natural Gas Pipeline System Research Articles

Mechanical Properties and Microstructural Characteristics of Steel Pipes after Long-Time Hydrogen Exposure

There are three possibilities to transport hydrogen by high pressure pipeline (i) blending hydrogen into the existing natural gas pipeline system, (ii) after checking the integrity, using the natural gas transporting pipeline system to transport hydrogen, (iii) building a new pipeline system to transport pure hydrogen. In all three cases should be known the behaviour of the pipe material and its welded joints influenced under high pressure hydrogen. For this aim pipeline sections made of P355NH base material were investigated without and with hydrogen exposure, where the exposure time was 41 days. Gas metal arc welding and hybrid tungsten arc welding / gas metal arc welding were applied for preparation of the girth weld joints. Tensile, three point bending and hardness tests, furthermore microstructural investigations were performed both on base materials and girth welds of the pipeline sections. The testing results were analysed and compared with each other (base material vs. welded joints, without exposure vs. with exposure) and with limit values can be found in the literature. Conclusions were drawn on the behaviour of the investigated pipe material and its welded joints.

Assessing the reliability of natural gas pipeline system in the presence of corrosion using fuzzy fault tree

The corrosion encountered within natural gas pipelines can precipitate significant ramifications. Numerous internal and external factors contribute to incidents of gas leakage. A multitude of factors influencing pipeline failure underscore the imperative need for a safety system intricately linked to the operation process. The absence of this systematic process for detecting factors contributing to failure detrimentally impacts the efficiency of pipelines. In this context, this paper has devised a risk assessment and warning model utilizing multi-factor monitoring data, employing the fuzzy fault tree analysis (FFTA). The fuzzy fault tree is constructed to assess the impact of individual factors and parameters influencing corrosion on the reliability of the grid. Moreover, a performance diagram illustrating this mechanism is crafted, elucidating the system's reliability relationship based on each component's reliability. The findings showed that 14 basic and 10 intermediate events play a role in the corrosion of natural gas pipelines. The failure probability of the top event was identified to be 22%. Employing the proposed method, the system's reliability was estimated with lower and upper limits of [0.6825, 0.8859]. The obtained results demonstrate the effectiveness and efficiency of the proposed method in addressing the uncertainty inherent in the input data.

Risk Evaluation and Software Development of Urban Natural Gas Pipelines Based on Bayesian Networks

Based on the urban natural gas pipeline accident statistics and semi-quantitative risk evaluation index system, this paper applies Bayesian network to establish a network model between various types of risk factors and the risk of natural gas pipeline failure. The EM algorithm was used to learn from the statistical accident data to obtain the parameters of the model. Based on the principle of evidential reasoning in reverse, the probability of occurrence of all risk indicators can be obtained when the probability of occurrence of urban natural gas pipeline accidents is 100%, the index weight is obtained by normalizing the occurrence probability. On this basis, this paper develops an efficient urban natural gas pipeline integrity risk identification and management software. The software can realize the basic data management of urban natural gas pipeline system, pipeline relative risk value calculation, pipeline risk level calculation and other functions, and the results are visualized. Finally, the practicability and effectiveness of the model and software are verified by a case of natural gas pipeline evaluation in a block.

A methodology to determine target gas supply reliability of natural gas pipeline system based on cost-benefit analysis

In this study, a methodology to determine the target gas supply reliability of the natural gas pipeline system based on cost-benefit analysis is proposed. In the methodology, an optimization model is developed firstly, and the objective function is constructed to maximize the difference between the benefits and investment when improving system reliability. Secondly, the investment and the benefits of reduced unreliability cost due to the implementation of the reliability improvement measures are considered in the optimization model. Thirdly, the virtual age model is employed to quantify the impact of reliability improvement measures on the unit's reliability, and the gas supply reliability evaluation method of the natural gas pipeline system is developed. Finally, the optimization model used to determine the target gas supply reliability is solved by a heuristic genetic algorithm. Furthermore, a real natural gas pipeline system located in China is applied to confirm the feasibility of the methodology, and the target gas supply reliability is determined, with a value of 0.998608. At last, the effect of system operational age on the target gas supply reliability is investigated through sensitivity analysis. The results show that the target gas supply reliability decreases with the increase of the operational age, which is consistent with the engineering practice.

First direct observations of interplanetary shock impact angle effects on actual geomagnetically induced currents: The case of the Finnish natural gas pipeline system

The impact of interplanetary (IP) shocks on the Earth’s magnetosphere can greatly disturb the geomagnetic field and electric currents in the magnetosphere-ionosphere system. At high latitudes, the current systems most affected by the shocks are the auroral electrojet currents. These currents then generate ground geomagnetically induced currents that couple with and are highly detrimental to ground artificial conductors including power transmission lines, oil/gas pipelines, railways, and submarine cables. Recent research has shown that the shock impact angle, the angle the shock normal vector performs with the Sun-Earth line, plays a major role in controlling the subsequent geomagnetic activity. More specifically, due to more symmetric magnetospheric compressions, nearly frontal shocks are usually more geoeffective than highly inclined shocks. In this study, we utilize a subset (332 events) of a shock list with more than 600 events to investigate, for the first time, shock impact angle effects on the subsequent GICs right after shock impact (compression effects) and several minutes after shock impact (substorm-like effects). We use GIC recordings from the Finnish natural gas pipeline performed near the Mäntsälä compression station in southern Finland. We find that GIC peaks (> 5 A) occurring after shock impacts are mostly caused by nearly frontal shocks and occur in the post-noon/dusk magnetic local time sector. These GIC peaks are presumably triggered by partial ring current intensifications in the dusk sector. On the other hand, more intense GIC peaks (> 20 A) generally occur several minutes after shock impacts and are located around the magnetic midnight terminator. These GIC peaks are most likely caused by intense energetic particle injections from the magnetotail which frequently occur during substorms. The results of this work are relevant to studies aiming at predicting GICs following solar wind driving under different levels of asymmetric solar wind forcing.

Evaluation of rapid gas decompression (RGD) resistance of sealing materials for hydrogen-doped pipeline valves

Abstract With the rapid development of hydrogen-doped natural gas pipelines, the evaluation of the applicability of hydrogen to natural gas pipeline systems is bound to gradually involve all aspects of natural gas pipelines. Targeted at the non-metallic sealing materials for valves of hydrogen-doped natural gas pipelines, this paper, according to the ISO 23936-2 standard, carried out the rapid gas decompression (RGD) tests of hydrogenated nitrile butadiene rubber (HNBR), fluorine rubber 246 (FKM246) and fluorine rubber 26 (FKM26), and the damage level of cracking failure for the rubber materials in the course of rapid release of gaseous medium was obtained (DL). The mechanical properties and volumetric dissolution rate of the three rubber materials were tested before and after the high-pressure gas mixture treatment, which explains the reason for the cracking failure of the rubber materials during the RGD test. The study obtained the influence law of high-pressure gas mixture with different hydrogen volume fractions on the RGD resistance of HNBR, FKM246, and FKM26, and selected the material with the optimal RGD resistance as FKM26, which can be used as a reference for the selection of sealing materials for the valves of hydrogen-doped natural gas pipelines in engineering.

The atypical transport system: Natural gas pipeline system

The natural gas pipeline system (NGPS) is complex with a diverse network topology. This study elucidates the network characteristics of the NGPS, revealing that it shares commonalities with small-world networks, but with differences caused by its structural and operational characteristics. The combination of the low aggregation effect caused by branching structure and the offsetting effect caused by economic and geographical constraints results in a network with small world characteristics. NGPS has longer mean path than common small world network, but the aggregation factor is close to that of a standard small world network. With respect to its small-world characteristics and correlation with self-organized criticality (SOC), an in-depth study of the SOC characteristics of the NGPS was conducted utilizing a combination of traditional logarithm analysis and R/S analysis. The findings establish that there are atypical SOC characteristics, characterized by a weakened power law within a specific functional range, thereby encouraging the advancement of SCADA and other safety technologies. Because of the line-pack, which induces time lags in the NGPS, NGPS can prevent the cascade failures. The reasons for the periodicity and centrality of NGPS data are analyzed by the affecting components, with the R/S analysis verifying a weak positive correlation of the function data across different time series. The interlinking of the SOC and R/S analysis illustrates the connection between critical status, accident type, and operation index. The results prove the reasonability and importance of insurance measures, such as regular internal detection, higher grade steel pipes change and staff training et al., in a novel view of SOC. The future works in building accidents database and human factors study are proposed.

Modeling and optimization of steady flow of natural gas and hydrogen mixtures in pipeline networks

We extend the canonical problems of simulation and optimization of steady-state gas flows in pipeline networks with compressors to the transport of mixtures of highly heterogeneous gases injected throughout a network. Our study is motivated by proposed projects to blend hydrogen generated using clean energy into existing natural gas pipeline systems as part of efforts to reduce the reliance of energy systems on fossil fuels. Flow in a pipe is related to endpoint pressures by a basic Weymouth equation model, with an ideal gas equation of state, where the wave speed depends on the hydrogen concentration. At vertices, in addition to mass balance, we also consider mixing of incoming flows of varying hydrogen concentrations. The problems of interest are the heterogeneous gas flow simulation (HGFS), which determines system pressures and flows given fixed boundary conditions and compressor settings, as well as the heterogeneous gas flow optimization (HGFO), which extremizes an objective by determining optimal boundary conditions and compressor settings. We examine conditions for uniqueness of solutions to the HGFS, as well as compare and contrast mixed-integer and continuous nonlinear programming formulations for the HGFO. We develop computational methods to solve both problems, and examine their performance using four test networks of increasing complexity.

Risk modelling of hydrogen‐enriched natural gas on pipelines and gas‐electric coupled systems

AbstractThe use of natural gas pipeline networks to transmit hydrogen energy is an important form of hydrogen energy utilisation. The coupling of hydrogen‐enriched natural gas pipeline network and power grid involves the energy conversion of electricity‐hydrogen‐electricity, so the assessment is crucial because the system is complex, and the hazards to the system can be identified. This paper proposes a risk assessment method for gas‐electric coupling of hydrogen‐enriched natural gas pipeline networks and a three‐stage risk assessment model to assess the life cycle risk of natural gas pipelines; a material energy‐based risk transfer model considering gas‐electric coupling is proposed to describe the risk transfer process of hydrogen‐enriched natural gas between the gas network and the grid. By comparing and analysing the risk of natural gas blending ratio to the pipeline and the risk of pipeline pressure to the pipeline, the validity of the model is verified, which provides safety support for the connection of the natural gas pipeline system to the grid and ensures the efficient use of hydrogen energy.

A methodology to determine the target reliability of natural gas pipeline systems based on risk acceptance criteria of pipelines

The reliable operation of the natural gas pipeline system is directly related to natural gas supply security, and it is vital to determine the target reliability of the natural gas pipeline system when assessing whether the system is reliable. In this study, a methodology to determine the target reliability of natural gas pipeline system based on the risk acceptance criteria of pipelines is proposed, and the methodology consists of three parts. Firstly, the risk acceptance criteria of the natural gas pipelines are determined based on the existing standards. Secondly, the failure consequence model of natural gas pipelines considering the pipeline properties and surroundings is developed, and the corresponding allowable pipeline failure probabilities are calculated according to the risk theory. Finally, the evaluation model of the gas supply reliability for natural gas pipeline systems considering the unit’s failure and hydraulic characteristics is developed, and the target reliability of natural gas pipeline systems is calculated by employing the allowable pipeline failure probabilities. Furthermore, a real natural gas pipeline system is employed to determine its target reliability, and the target value is compared with the actual value of the gas supply reliability. Based on the compared results, the corresponding measure to improve the gas supply reliability is proposed.

Probabilistic simulation model of resilience assessment of natural gas pipeline systems

The study for the natural gas pipeline system (NGPS), particularly about the resilience evaluation, is still in its early stages. Resilience is a hot point in the most important aspects of system security assessment. An integrated simulation model is presented for assessing the gas supply of NGPS, incorporating the topological and operational circumstances. This model takes different forms of disruptions into consideration. Analysis is done on the properties of probabilistic disturbances. The novel ideas include the global resilience and temporal resilience as the indicators for evaluating resilience. By integrating the maximum flow algorithm and the shortest path algorithm with operational and structural parameters, the gas supply volume and routes were determined before and after system disturbances. Based on the theories of complex network and graph theory, researchers have moved the traditional viewpoint from the entire system to the affected regions. The use of simulation models in research can facilitate the development of pre-warning for natural gas supply systems (NGPS), including optimization of gas supply amount and supply routes arrangement, as well as formulation of pipeline maintenance strategies. In addition, simulation models can also support the rapid analysis of disturbance results, thus improving the accuracy of resilience evaluation for NGPS.

Resilience of Natural Gas Pipeline System: A Review and Outlook

A natural gas pipeline system (NGPS), as a crucial energy transportation network, exhibits intricate systemic characteristics. Both uncertain disturbances and complex characteristics result in higher requirement of supply safety. The investigation into NGPS resilience addresses the constraints of pipeline integrity and reliability, centering around the vulnerability, robustness, and recovery of an NGPS. Based on a literature review and practical engineering insights, the generalized concept of NGPS resilience is elucidated. The research methodologies of NGPS resilience are classified into three types: indicator construction method, process analysis method, and complex networks method. The practical applications of NGPS resilience research are analyzed, which are based on NGPS operation safety, information safety, and market safety. The ongoing applications and detailed measures are also concluded, which can guide the researchers and engineers from NGPS resilience.

A resilience evaluation method of natural gas pipeline system based on uncertainty analysis

The natural gas pipeline system (NGPS) is a complex network of units that is susceptible to potential random failures. Moreover, the environment in which the NGPS operates is characterized by complexity and uncertainty, including market volatility, natural disasters, and deliberate sabotage. While research on the NGPS has mainly focused on supply reliability through methods such as statistical analysis and random simulation, there is a lack of emphasis on the system's supply resilience, which encompasses its robustness and recovery abilities. To address the resilience of the NGPS under uncertainty, this study proposes a probabilistic analysis model that evaluates supply resilience based on failure mechanisms and reasonable data. The model takes into account the integrated evaluation indexes framework and analyzes the process of failure and recovery, using MCMC random process analysis and complex networks theory. The results indicate that both gas transportation capacity and user satisfaction should be considered in the evaluation and strategy analysis of NGPS resilience. Furthermore, the study of resilience can provide guidance for NGPS operation, pre-warning during the design and operational stages.

Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm.

The measured signals of internal leakage detection of the large-diameter pipeline ball valve in natural gas pipeline systems usually contain background noise, which will affect the accuracy of internal leakage detection and sound localization of internal leakage points due to the interference of noise. Aiming at this problem, this paper proposes an NWTD-WP feature extraction algorithm by combining the wavelet packet (WP) algorithm and the improved two-parameter threshold quantization function. The results show that the WP algorithm has a good feature extraction effect on the valve leakage signal, and the improved threshold quantization function can avoid the defects of the traditional soft threshold function and hard threshold function, such as discontinuity and the pseudo-Gibbs phenomenon, when reconstructing the signal. The NWTD-WP algorithm is effective in extracting the features of the measured signals with low signal/noise ratio. The denoise effect is much better than that of the traditional soft and hard threshold quantization functions. It proved that the NWTD-WP algorithm can be used for studying the existing safety valve leakage vibration signals in the laboratory and the internal leakage signals of the scaled-down model of the large-diameter pipeline's ball valve.

Nested physics-informed neural network for analysis of transient flows in natural gas pipelines

Natural gas pipeline systems are commonly designed under the assumption of constant supply and demand flow conditions. This is while gas flows are transient because of the compression stations, presence of gas storage facilities and fluctuating supply and consumer demands. Analyzing such transient flows substantially benefits design, control, and monitoring of natural gas pipeline systems. The nonlinear partial differential equations describing the physics of transient flows in pipelines are solved using conventional methods, which are computationally demanding especially for uncertainty quantification purposes where many simulations are required. In this study, we propose an alternative physics-informed neural network (PINN) framework for the transient analysis of pipeline networks that can perform transient flow analysis in natural gas pipelines that the original PINNs cannot solve due to the high complexity of the problem. We propose a nested structure for the PINNs with a loss model that greatly reduces the number of tasks in the emergent complex multi-task learning process. We also integrate an adaptive weights approach that tackles the imbalanced gradients caused by the extremely large coefficients in the equations of the natural gas pipeline problem. The proposed framework, for the first time, can produce accurate results for the complex natural gas pipeline network problem using PINNs. Furthermore, we investigate the parameterization of the nested PINNs as a surrogate model for the natural gas pipeline system. With merely 26% more training costs, the surrogate model can perform the transient flow analysis given thousands of realizations of parameters in a split millisecond, while the costs of performing the same simulations using conventional methods can be prohibitively expensive. This can greatly boost the efficiency of complex many-query analyses such as sensitivity analysis, uncertainty propagation and design optimization.

An improved solution to flow assurance in natural gas pipeline enabled by a novel self-regulated bypass pig prototype: An experimental and numerical study

Bypass pigging is an emerging strategy in effectively overcoming inherent issues of high pig speed and overflow of pigging-induced slug volume concomitantly caused by traditional pigging for natural gas pipelines, which is attracting wide attention for flow assurance in oil and gas industry. In view of most bypass pigs with simple bypass structures, the risk of pig stalling or pipeline blockage accidents can be encountered when suffering from increased resistance forces. Accordingly, a novel bypass pig prototype with a self-regulated module is proposed in this study as an improved solution to strengthening pigging safety, efficiency and flow assurance. A self-regulated, easily assembled bypass pig prototype was fabricated for experimental studies in a horizontal transparent gas pipeline system. The pressure mitigation and pig velocity characteristics were fully evaluated under varying bypass fractions. Specifically, when the bypass fraction increases from 0% to 3%, the average pig velocity can be reduced by 64.3–81.5% and pressure fluctuations are more stable. Besides, as an important structural parameter in affecting pig velocity and accuracy of dynamic pigging simulation, the pressure drop coefficient of gas through the bypass pig structure with an internal regulating valve was numerically studied. Compared to the common bypass pig with only a simple bypass port, the addition of the bypass regulating valve will notably increase the pressure drop coefficient. In particular, when the bypass fraction is increased to 7%, pressure drop coefficients for the bypass pig without or with an internal valve are 1.03 and 1.97, respectively, with the deviation of 90.9%. Finally, an optimal design scheme for bypass pigging operations was newly proposed to optimize bypass fractions in accordance with practical scenarios. This study can provide an effective pathway towards the implementation of self-regulated bypass pigging technology in substantially improving flow assurance of natural gas pipeline systems.

Measuring the destruction and recuperation of the natural gas pipeline system at Oregon's Critical Energy Infrastructure Hub.

Portland has become a hot spot for geological discussions over the last few years. The event that has everyone talking, and preparing for, is the Cascadia Subduction Zone earthquake. Cascadia is categorized as a catastrophic natural, seismic event, where the Juan De Fuca plate and the North American plate subduct off the Northwest coast, causing a violent response in the zone between the two plates. Geological history has shown us that every 200-300 years, a major seismic event occurs in this area of the Pacific; in current disaster discussions in the emergency management industry, where this author has resided for the last 6 years, it is not a matter of if, but a matter of when. The Cascadia event will cause a massive earthquake, affecting millions of lives and costing just as much if not more. Currently, there is no model that exists to equate for all of the following: damages to pipes, restoration, and disruption, and maximum thresholds for utility usage. The models and plans discussed in this paper will cast a needed spotlight for establishing a new model combining these elements and more. It is vital that efforts be made to calculate, beyond a base percentage rate of recovery, what Oregon and the region will lose and what it will take regain a "back to business" level of operations, economically, structurally, and environmentally. Many calls were placed with nonprofit energy stewards to determine these statistics, but no current information was available, or easy to attain, further emphasizing a need for real-time utility data.

Improvement of Regasification Process Efficiency for Floating Storage Regasification Unit

Natural gas plays a vital role in the economically and environmentally sustainable future of energy. Its reliable deliveries are required, especially nowadays, when the energy market is so volatile and unstable. The conversion of natural gas to its liquefied form (LNG) allows its transport in greater quantities. Affordability and reliability of clean energy is a key issue even for developed markets. Therefore, natural gas usage enables to implement green solutions into countries’ economies. However, the LNG-production process consumes a considerable amount of energy. This energy is stored in LNG as cold energy. After LNG unloading into storage tanks at receiving terminals, it is vaporised and compressed for transmission to a natural gas pipeline system. During the regasification process, the large part of the energy stored in LNG may be recovered and used for electricity generation, seawater desalination, cryogenic air separation, hydrogen liquefaction, material freezing, carbon dioxide capture, as well as for combined LNG cold energy utilization systems. Moreover, increased efficiency of LNG terminals may attract potential clients. In the presented paper, a mathematical model is performed to determine the influence of LNG composition and regasification process parameters on the quantity of released LNG cold energy in a large-scale floating storage and regasification units (FSRU)-type terminal “Independence” (Lithuania). Flow rate of LNG regasification, pressure, and boil-off gas recondensation have been considered. Possibilities to reduce the energy losses were investigated to find the ways to improve the regasification process efficiency for real FSRU. The results analysis revealed that potential of LNG cold energy at FSRU could vary from 20 to 25 MW. A utilisation of industrial and urban waste heat for the heat sink FSRU is recommended to increase the energy efficiency of the whole regasification process.

Developing and Implementing an AI-Based Leak Detection System in a Long-Distance Gas Pipeline

This research proposes an artificial intelligence (AI) detection model using convolutional neural networks (CNN) to automatically detect gas leaks in a long-distance pipeline. The change of gap pressure is collected when leakage occurs in the pipeline, and thereby the feature of gas leakage is extracted for building the CNN model. The gas leak patterns in the long-distance pipeline are analyzed. A pipeline detection model based on AI technology for automatically monitoring the leaks is proposed by extracting the feature of gas leakage. This model is tested by collecting gas pressure data from an existing natural gas pipeline system starting from Mailiao to Taoyuan in Taiwan. The testing result shows that the reduced model of leak detection can be used to detect the leaks from the upstream and downstream pipelines, and the AI-based pipeline leak detection system can obtain a satisfactory result.

Preserving Ukraine's Electric Grid During the Russian Invasion

In February 2022, the Russian Federation invaded Ukraine, a country with an interconnected electric grid.1 While most analysts have concentrated on the military dimensions of Russia's attack, the implications for energy infrastructure are both unprecedented and critically important. Russia has incentives to preserve reliable operation of Ukraine's electric grid. Both sides have shown restraint in attacking energy infrastructure. An apparent Russian objective is keeping hard‐to‐replace infrastructure intact, especially hydroelectric and nuclear plants. Ukraine's natural gas pipeline system depends on grid electricity for its centralized control. Russia profits from transmission of its natural gas through Ukraine's pipelines to Europe. All countries seek to avoid infrastructure accidents and human migrations that are disruptive to their own societies. Nonetheless, by export ban, naval blockade, and physical attack, Russia has disrupted fuel supplies for Ukraine's generating plants. Interconnected electric grids are vulnerable to cascading collapse after forced outages of generating plants, transmission system disruptions, and deliberate attacks. As winter approaches, fuel supplies for Ukraine's electric grid will be constrained and the possibility of grid collapse increases. If Ukraine's electric grid were to be inoperable for a prolonged period, the result could be widespread death by famine, disease, and, in winter, hypothermia. Nuclear reactor meltdowns and spent fuel pool fires could also result, with radiation release extending beyond Ukraine's borders. Millions of refugees would cross the borders of Poland, Russia, Belarus, and other regional neighbors. Ukraine should develop a robust plan for electric grid restoration, including asking the Ukrainian people for their assistance during emergencies. To this end, financial and other targeted support for Ukraine's electricity sector by European and other allies may be essential to reduce the prospect of long‐term grid collapse. Events in Ukraine have public policy lessons for all nations with electric grids vulnerable to cascading collapse and long‐term outage.