Long-distance Natural Gas Pipeline Research Articles

Experimental and numerical study on natural gas explosion evolution in open space under different initial conditions

The vapor cloud explosion in open space are greatly affected by the initial conditions of gas cloud and the surrounding environment, while in the gas compressor station, these factors are ubiquitous. While the researches of external influencing factors like the obstacle and initial turbulence effect on natural gas explosion in open space are rare. In this paper, a series of natural gas explosion experiments were conducted and a long-distance natural gas pipeline compressor station was taking as an example to simulate the natural gas leakage and explosion in the typical location. Results showed that the greater the initial turbulence, the greater the peak overpressure of gas explosion. When the initial wind speed is 5 m/s, the peak overpressure can promote 73.4 % higher than that without initial turbulence. However, the overpressure doesn't linearly increase with the increasing of initial wind speed. What's more, the flame speed showed the same law with the overpressure, and the effect of concentration on overpressure is lower than that of initial turbulence and obstacle density. The explosion damaging range in the condenser area is larger than that in the separator area, and the maximum overpressure can reach about 21 kPa and the temperature can reach above 2280K, which provides an important basis for the safety prevention and personnel protection in natural gas compressor station.

Research on Strain of Unequal Wall Thickness Pipeline of the X80 Pipeline under Lateral Load

X80 steel is a material with high strength and good toughness, which is widely used in long-distance natural gas pipelines. Pipelines will have different wall thicknesses, depending on the safety level requirements of different regions. Two sections of pipes with different wall thickness form unequal wall thickness of pipeline (UWTP) that is joined together by welding. UWTP pass through some geohazard areas, such as landslides. The frequency of landslides is extremely high in mountainous areas, which can seriously affect the safe operation of UWTP. In this paper, a model of a 12.8 mm wall pipe section and a 15.6 mm wall pipe section are linked by girth welds. The strain between the pipe section and the weld was quantitatively analyzed. The results show that the strain at the girth weld in the 3 o’clock direction of the pipe increases sharply. The strain in the 9 o’clock direction of the pipe is generally lower than the strain in the 3 o’clock direction. The strain value of the 12.8mm wall thickness pipe section is generally greater than the strain value of the 15.6mm wall thickness pipe section.

Evaluation of disaster-bearing capacity for natural gas pipeline under third-party damage based on optimized probabilistic neural network

Third-party damage has become a significant factor leading to pipeline failures and leaks, resulting in severe ecological damage and human casualties. Traditional safety risk analysis methods in the past have focused on severing the causal chain of accidents, while neglecting the unique characteristics of different pipeline segments and environmental factors on their ability to bearing disasters. This paper presents a framework for evaluating the disaster-bearing capacity of natural gas pipeline third-party damage based on probabilistic neural networks. A comprehensive disaster-bearing capacity index system for evaluating third-party damage to natural gas pipelines has been constructed by analyzing the causal factors and potential consequences of third-party damage risk incidents. Next, the cluster analysis and indicator weighting information is used for achieving the comprehensive disaster-bearing capacity assessment. Finally, the data samples are constructed with the index levels and comprehensive disaster-bearing capacity levels of each evaluation unit. An optimization algorithm, Particle Swarm Optimization (PSO), is utilized to improve the parameter selection process of the Probabilistic Neural Network (PNN) model, in order to evaluate the disaster-bearing level of each unit. A typical long-distance natural gas pipeline in Zhejiang Province was selected as the case study, and a total of 200 research units were obtained through pipeline analysis. Furthermore, 14 indicator data were obtained by leveraging multiple sources of data surrounding the pipeline. With the utilization of cluster analysis, it was determined that Gaussian mixed model clustering method ultimately identified a total of 5 different levels of disaster-bearing capacity. The optimal smoothing factor can be accurate from 0.5 to 0.588 by using the PSO-PNN model, and the final accuracy rate is improved from 88% to 98%, which is obviously the introduction of PSO optimization algorithm in the PNN model can improve the accuracy of the model. This represents a significant improvement in accuracy when compared to traditional PNN models. The proposed evaluation method can provide scientific basis for the prevention and control of third-party damage in oil and gas pipelines and pipeline planning.

Multi-parameter distributed fiber optic sensing using double-Brillouin peak fiber in Brillouin optical time domain analysis.

In this paper, we demonstrate a multi-parameter fiber sensing system based on stimulated Brillouin scattering in a double-Brillouin peak specialty fiber with enhanced Brillouin gain response. The amplitude level of the second Brillouin gain peak, which originated from the higher-order acoustic modes, has been improved with an approximately similar amplitude level to the first Brillouin gain peak from the fundamental acoustic mode. Compared to other multi-Brillouin peak fibers presented in the literature, the proposed fiber significantly reduces the measured Brillouin frequency shift error, thus improving strain and temperature accuracies. By utilizing the sensitivity values of the strain and temperature associated with each Brillouin gain spectrum (BGS) peak, a successful discriminative measurement of strain and temperature is performed with an accuracy of ±13 μɛ, and ±0.5 °C, respectively. The proposed double-Brillouin peak fiber appears to be a possible alternative to other multi-BGS peak fibers, for instance, large effective area fiber and dispersion compensating fibers, which are inherently accompanied by large measurement errors due to the weak Brillouin gain values originating from the higher-order acoustic modes. The demonstrated results show different strain and temperature coefficients of 47 kHz/µɛ, 1.15 MHz/°C for peak 1 and 51 kHz/µɛ, 1.37 MHz/°C for peak 2. Moreover, the enhanced BGS peak gains having nearly the same amplitude levels enable the discriminative measurement of strain and temperature. Such fibers in Brillouin interrogation eliminate the need for complex monitoring setups and reduce measurement errors. We recommend that for long-distance natural gas pipeline monitoring, where discriminative strain and temperature measurement is crucial, the proposed double-Brillouin peak fiber can be highly beneficial.

Function Optimization of Self-shutoff Protection System for -Valve Chambers of Long-distance Natural Gas Pipelines

The rate of pressure drop set value of shut-off valve in gas pipeline is uncertain to a certain extent, and the function of self-shutoff protection may disable under some leakage conditions. A gas pipeline leakage model is established using simulation software, to simulate the leakage, flow rate reduction, and crossover, and obtain the pressure changes in upstream and downstream shut-off valve chambers under different working conditions[1]-[3]. The rate of pressure drop is calculated by using the rate of pressure drop algorithm adopted by Line Guard 2300 system. Simulation results indicate that the gas transmission volume has little influence on the rate of pressure drop, and the leakage diameter has great influence on the rate of pressure drop, showing a positive correlation. When the pipeline runs in parallel, it is necessary to avoid opening the crossover valve under large pressure difference. Finally, the recommended rate of pressure drop threshold at the trunk line shut-off valve chamber is given, and the leakage condition of 1/2 diameter at 32km upstream can be detected under this recommended value.The simulation software is first applied in multinational pipelines, which can effectively protect pipeline defect points. Reduced methane cold venting, greatly improving the contribution to achieving emission reduction goals.

Using the meteorological early warning model to improve the prediction accuracy of water damage geological disasters around pipelines in mountainous areas

This paper focuses on the threat of water damage geological disasters brought by the complex terrain along the long-distance natural gas pipeline. The role of rainfall factors in the occurrence of such disasters has been fully considered, a meteorological early warning model for water damage geological disasters in mountainous areas based on slope units has been constructed to improve the prediction accuracy of such disasters and timely early warning and forecasting. An actual natural gas pipeline in a typical mountainous area of Zhejiang Province is taken as an example. The hydrology-curvature combined analysis method is chosen to divide the slope units, and the SHALSTAB model is used to fit the slope soil environment to calculate the stability level. Finally, the stability level is coupled with rainfall data to calculate the early warning index for water damage geological disasters in the study area. The results show that compared with the separate SHALSTAB model, the early warning results coupled with rainfall are more effective in predicting water damage geological disasters. The early warning results are compared with the actual disaster points, among the nine actual disaster points, most of the slope units around seven disaster points are in the state of needing early warning, the early warning accuracy rate reaches 77.8 %. The proposed early warning model can carry out targeted deployment in advance according to the divided slope units, and the prediction accuracy of geological disasters induced by heavy rainfall weather is significantly higher and more suitable for the actual location of the disaster point, which can provide a basis for accurate disaster prevention in the research area and areas with similar geological environments.

Heat Transfer Model of Natural Gas Pipeline Based on Data Feature Extraction and First Principle Models

The rapid development of natural gas pipelines has highlighted the need to utilize SCADA (supervisory control and data acquisition) system data. In this paper, a heat transfer model of a natural gas pipeline based on data feature extraction and first principle models, which makes full use of the measured temperatures at each end of the pipeline, is proposed. Three methods, the NARX neural network (nonlinear autoregressive neural network with exogenous inputs), time series decomposition, and system identification, were used to model the changes of gas temperatures of the pipeline. The NARX neural network method uses a cyclic neural network to directly model the relationship of temperature between the start and the end of the pipeline. The measured temperature series at the pipeline inlet and outlet were decomposed into trend items, fluctuation items, and noise items based on the time series decomposition method. Then the three items were fitted separately and combined to form a new temperature prediction series. The system identification method constructed the first-order and second-order transfer function to model the temperature. The simulation of the three data-driven models was compared with those of the physics-based simulation models. The results showed that the data-driven model has great advantages over the physics-based simulation models in both accuracy and efficiency. The proposed models are more suitable for applications such as online simulation and state observation of long-distance natural gas pipelines.

Numerical Simulation of Mechanical Behavior of Gas Pipeline in High and Steep Slope

Long-distance natural gas pipelines can often pass through the common slope safely. However, when pipelines inevitably pass through high and steep slopes(HSS) for some reasons, it is difficult for engineers to predict the stress state of pipelines. Therefore, in order to investigate the safety of natural gas pipelines in HSS areas, the finite element simulation calculation model of the pipeline in HSS was established. The predicted numerical model shows that the maximum Von Mises stress and axial strain of the pipeline in the HSS area appear at the lower elbow of the pipeline, which should be paid more attention to in the risk assessment; The stress and deformation of the pipeline is mainly related with the wall thickness and internal pressure, appropriately increasing the wall thickness and reducing the internal pressure can improve the safety of HSS pipelines.

Research on explosion characteristics and consequences of compressor room in compressor station of long-distance natural gas pipeline

As the core place in the compressor station, the compressor room has the possibility of gas leakage and explosion during its operation. In this paper, an equal proportional physical model is established based on FLCAS software, the effects of different stoichiometric ratios on the explosion temperature, flame propagation velocity and overpressure in the compressor room are investigated. The results show that when the stoichiometric ratio is in the range of 0.8–1.4, the indoor temperature peak, flame propagation velocity and peak overpressure generated by the explosion in the compressor room all increase first and then decrease with the increase of the stoichiometric ratio. The outdoor temperature peak and the flame propagation velocity increase with the increase of the stoichiometric ratio in the range of 0.8–1.4, and the flame acceleration during the flame propagation process can effectively promote the increase of the explosion overpressure inside the flame surface. In addition, in order to avoid more serious consequences in the event of an explosion in the compressor room, a fire sprinkler system should be laid between the adjacent compressor room doors, and the doors of the adjacent compressor rooms should be installed in staggered positions to prevent the occurrence of secondary danger.

Management and Safety Control of Long-distance Natural Gas Pipeline Construction Project

Management and Safety Control of Long-distance Natural Gas Pipeline Construction Project

Exploration on Centralized Monitoring and Management Operation of Long-distance Natural Gas Pipeline

Exploration on Centralized Monitoring and Management Operation of Long-distance Natural Gas Pipeline

Self-adapting anti-surge intelligence control and numerical simulation of centrifugal compressors based on RBF neural network

Anti-surge control of centrifugal compressors is an essential issue for the operation of long-distance natural gas pipeline systems. A suitable controller can make a centrifugal compressor runs smoothly and stably and improve the economy. This work presents a new intelligence control strategy with self-adapting ability. The strategy includes the proportional integral (PI) control self-tuned by radial basis function neural network (RBF-NN), recycle trip control, special derivative control, surge line correction, and asymmetric output of the controller. A hybrid numerical simulation platform is built to validate the anti-surge strategy, and a real centrifugal compressor is simulated. The results show that the strategy makes the anti-surge valve respond quickly, decreases the surge control line’s margin and backflow rate, and improves the economy. In the controller, the special derivative control can make the anti-surge valve open earlier and effectively reduce the fluctuating of inlet flow rate. Aiming at the problem that the gradient descent method is more sensitive to the initial value when solving RBF-NN, a hybrid algorithm of k-means, recursive least square, and gradient descent (KRG algorithm) is proposed. It is successfully applied in the anti-surge controller. Even if the given RBF-NN initial parameters are not good enough, the KRG algorithm illustrates good learning stability and increases the adaptive ability of RBF-NN.

Techno-economic assessment of low-carbon hydrogen export from Western Canada to Eastern Canada, the USA, the Asia-Pacific, and Europe

The use of low-carbon hydrogen is being considered to help decarbonize several jurisdictions around the world. There may be opportunities for energy-exporting countries to supply energy-importing countries with a secure source of low-carbon hydrogen. The study objective is to assess the delivered cost of gaseous hydrogen export from Canada (a fossil-resource rich country) to the Asia-Pacific, Europe, and inland destinations in North America. There is a data gap on the feasibility of inter-continental export of hydrogen from an energy-producing jurisdiction to energy-consuming jurisdictions. This study is aimed at addressing this gap and includes an assessment of opportunities across the Pacific Ocean and the Atlantic Ocean, based on fundamental engineering-based models. Techno-economics were used to determine the delivered cost of hydrogen to these destinations. The modelling considers energy, material, and capacity-sizing requirements for a five-stage supply chain comprising hydrogen production with carbon capture and storage, hydrogen pipeline transportation, liquefaction, shipping, and regasification at the destinations. The results show that the delivered cost of hydrogen to inland destinations in North America is between CAD$4.81/kg and CAD$6.03/kg, to the Asia-Pacific from CAD$6.65/kg to CAD$6.99/kg, and at least CAD$8.14/kg for exports to Europe. Delivering hydrogen by blending in existing long-distance natural gas pipelines reduced the delivered cost to inland destinations by 17%. Exporting ammonia to the Asia-Pacific provides cost savings of 28% compared to shipping liquified hydrogen. The developed information may be helpful to policymakers in government and the industry in making informed decisions about international trade of low-carbon hydrogen in both energy-exporting and energy-importing jurisdictions, globally.

Study on influencing factors and monitoring cycle of wall thickness at key locations of natural gas station

In recent years, the safe and stable operation of natural gas pipeline has become the focus of the whole society. Long distance natural gas pipelines are mostly large-diameter and high pressure pipelines, so their safe operation is particularly critical. In the high-pressure natural gas pipeline transportation industry, the wall thickness of key points (elbows and tees) will be thinned due to long-term erosion of gas, resulting in serious consequences. Therefore, its wall thickness monitoring is a key work of long-distance natural gas pipeline operation units. At present, most of them adopt off-line monitoring, but the standardized monitoring cycle cannot be effectively determined, and there are no relevant standards in the industry. The author uses fluent simulation software to establish the model, and then modifies the model combined with the field data. Then, the model is used to analyze the influencing factors of key points (elbow and TEE) one by one, and select more important influencing factors to formulate the monitoring cycle of different points. The monitoring cycle can provide reference for the daily work of on-site operators, and then ensure the safe and stable operation of long-distance natural gas pipeline.

Research on Explosion Characteristics and Consequences of Compressor Room in Compressor Station of Long-Distance Natural Gas Pipeline

Research on Explosion Characteristics and Consequences of Compressor Room in Compressor Station of Long-Distance Natural Gas Pipeline

Environmental analysis for the selection of long-distance natural gas pipeline routes using MACBETH

PurposeReliable operation of natural gas pipeline (NGP) is a critical factor in Iran’s economic development. NGP projects go through different ecosystems and considerably affect the environment. Environmental analysis is an essential step toward sustainable development. Tackling the challenges, this paper aims to develop a framework to systematically assess the environmental impact of NGPs.Design/methodology/approachThis study proposes a comprehensive framework for environmental impact analysis of NGPs using Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH). MACBETH protocol is used to calculate the overall environmental scores of projects.FindingsThe results indicate that the impact of implementing NGPs on protected areas is of the highest priority, while the impact on vegetation covers is of least priority for assessing the environmental impact of NGP.Practical implicationsThe practicality and validity of the model in the case of three candidate routes for the Polkale-Neizar project in Iran are examined. According to the results, the third alternative is selected based on its non-interference in protected areas and less environmental impacts. The proposed model can be modified and applied to perform environment appraisal of other linear projects such as energy, road and railway networks.Originality/valueThis model addresses a range of environmental impacts of implementing NGPs at two levels, with the second level being non-additive. The novelty of this study translates into considering the qualitative and quantitative features of each evaluation criterion applied to linear projects simultaneously using a multi-criteria value measurement.

Fe/SiO2 Composite Coated Optical Fiber for Corrosion Monitoring

It is important to monitor and locate internal corrosion over the long-distance natural gas pipelines in real time before catastrophic failures to ensure safe, secure, and reliable transportation of natural gas and reduce the environmental impact from methane emission. Optical fiber based sensors provide many advantageous features, especially the distributed sensing over a long distance and the inertness in the presence of flammable gas, among others. To take advantage of these features, corrosion proxy sensing materials are a key enabling component for an optical fiber corrosion sensor. We have previously demonstrated a distributed optical fiber corrosion sensor, and reported early results on Fe/SiO2 composite coating. To further improve the sensing performance, detailed studies were performed to investigate the Fe/SiO2 composite coating. The Fe/SiO2 composite layers are coated onto the optical fiber using sol-gel and electroless plating methods, respectively, with controlled morphologies. The coating is characterized with SEM and XPS. Tested in corrosive solutions at room temperature, optical responses are measured for corrosion monitoring. The light transmission increases as Fe dissolves away due to the decrease in light absorption of the metallic layer. Different morphologies are compared to optimize sensing performance of the Fe/SiO2 composite coated optical fiber corrosion sensor.

Application and Research of Engineering Economic Evaluation Based on Multi-objective Intelligent Grey Target Decision System

With the development of the times, enterprises and investors have more detailed requirements for engineering projects. Based on this, the application of engineering economic evaluation in engineering projects is becoming more and more important. This paper mainly aims at the engineering economic evaluation, uses AHP to screen the index weight that affects the project, and combines with the multi-objective grey target decision model to establish the relevant intelligent decision system. This paper mainly takes the long-distance natural gas pipeline laying project as an example and uses the multi-objective grey target decision model to evaluate its engineering economic evaluation. At the same time, the feasibility of the model and the accuracy and effectiveness of its evaluation of engineering economic indicators are explored.

Fault diagnosis of gas turbines with thermodynamic analysis restraining the interference of boundary conditions based on STN

Gas turbines are widely used in natural gas-fired power generation and long-distance natural gas pipelines. The complexity and diversity of boundary conditions usually have a great influence on the measurement parameters, which makes them difficult to reflect the actual health status of gas turbines and leads to lower diagnostic accuracy. In the gas path analysis of gas turbines, traditional mechanism and data-driven methods are difficult to consider the interference of boundary conditions. A novel fault diagnostic method deriving from the spatial transformer network (STN) is proposed to restrain the influences of boundary conditions on fault diagnostic results. It can realize fault detection with higher accuracy by converting different boundary conditions to a designed one.The established STN is then combined with the typical small deviation (SD) theory and a classification network to complete the gas path analyses.The proposed two methods are verified and compared with traditional methodsthrough simulation experiments and field data. Compared with the traditional SD method, the fault detection accuracy is increased by 2.92% in the STN-SD method, and the STN-MLP method improves the diagnostic accuracy by 5.24%. The proposed two methods also have good performance in the field data analysis and realize fast fault detection and early warning.This work provides a reliable way to detect faults subjecting tothe influence of complex boundary conditions and provides reference and support for the fault diagnosis of other thermodynamic systems.

Energy metering for the urban gas system: A case study in China

With the continued downturn in global crude oil prices, the natural gas market shows a rapid growth trend. The coordination of natural gas trade is becoming more and more important, and many organizations have put forward natural gas energy metering the schemes. Nowadays, the energy metering schemes for long-distance natural gas pipelines have been approaching maturity, but the energy metering scheme between urban gas gate stations and urban gas users has not yet been proposed. Therefore, this paper takes two different types of cities in China for instance to verify the rationality of urban gas energy metering, and proposes a specific plan for urban gas energy metering. Taking Beijing (China) and Dali (Yunnan Province, China) urban gas systems as examples, by comparing the energy metering method with traditional volumetric metering method, it can be obtained that the use of volumetric metering method in Beijing and Dali will lead to different degrees of extra economic losses to the natural gas companies, and the extra economic losses in winter are the biggest. For some cities with high temperature in summer, the use of volumetric metering will lead extra economic losses in winter and extra economic benefits in summer. Therefore, it is fairer to use the urban gas energy metering method. Furthermore, the method of establishing an urban gas energy metering system and the method of building an Internet plus-based management system are proposed in this paper.