Urban Gas Pipeline Research Articles

A Method for Grading the Hidden Dangers of Urban Gas Polyethylene Pipelines Based on Improved PLC Methods

The classification of hidden dangers in urban gas pipelines plays a vital role in the smooth operation of urban gas pipelines and in solving the problem of hidden safety dangers in urban gas pipelines. In recent years, the number and proportion of polyethylene (PE) pipelines in urban gas pipelines are increasing day by day, but the current classification of hidden dangers in urban gas pipelines is still based on steel pipelines, and the classification method is highly subjective. Therefore, this paper proposes an improved PLC method that integrates the use of a risk matrix and compensation coefficient to solve the problem of grading the hidden dangers of PE pipelines of urban gas. The improved PLC method is based on the failure database of urban gas PE pipelines to obtain the vulnerability and severity of consequences when determining the initial level of hidden dangers, and the compensation coefficient is modified according to regional vulnerability, ease of rectification, condition around the pipeline, positioning technology, leak detection technology, and emergency ability, which can effectively reduce the subjectivity of hidden danger classification. Using the improved PLC method to classify urban gas pipelines for hidden dangers can provide pipeline operating companies with a basis for decision making in the process of hidden danger disposal and effectively reduce pipeline safety risks.

Economic analysis and investment in fuel industry considering risk management by analytical hierarchy process

Natural Gas production and distribution network plans are one of the most common ways to increase energy consumption efficiency. Due to the uncertainty of the economic parameters, the economic justification of this system is very difficult. In this research, the economic risk of investing in urban gas distribution systems has been done with the analytical hierarchy process (AHP). With the development and condensation of urban gas supply networks, accidents caused by gas leaks and other external factors have also increased. Therefore, in recent years, the issue of safety and risk analysis of urban gas networks has received special attention from responsible companies and other urban and safety experts. Gas distribution lines often pass in the vicinity of crowded areas and buildings, so any accident for these lines will lead to a lot of human and financial losses. In the present study, in order to improve the gas supply situation and reduce the risk of failure in Indonesia, urban gas pipelines have been studied to reduce the costs. In this paper, multi-criteria decision making method analysis is used to identify and evaluate the hazards of urban gas pipelines and the risk of occurrence of each hazard is calculated. There was a meaningful relationship based on economic-financial theories between economic factors and investment risk in the gas industry, which emphasizes the greater and more significant effect of exchange rate, failures and inflation rate variables in comparison with other research variables in the matter of controlling investment risk in the gas industry. The effects of changes in energy prices and the economic environment in explaining the behavior of investment risk in this industry have placed the next level of importance. The results showed that with the increase in energy prices, the economics of gas production and distribution risk management plans have improved and the regular trend of energy price increases can guarantee the profitability of fuel consumption optimization plans.

Brief Analysis of Technical Emphases and Matters Needing Attention of Urban Gas Pipeline Construction

Brief Analysis of Technical Emphases and Matters Needing Attention of Urban Gas Pipeline Construction

Discussion on Safety Hidden Dangers and Risk Control of Urban Gas Pipeline

Discussion on Safety Hidden Dangers and Risk Control of Urban Gas Pipeline

Study on Influencing Factors and Safety Management of Urban Gas Pipeline Project

Study on Influencing Factors and Safety Management of Urban Gas Pipeline Project

A new sensor fault diagnosis method for gas leakage monitoring based on the naive Bayes and probabilistic neural network classifier

Gas monitoring sensor is prone to failure and its fault type is difficult to identify due to harsh working condition. In this work, a new sensor fault diagnosis method for gas leakage monitoring has been proposed derived from the Naive Bayes Classifier (NBC) and Probabilistic Neural Network (PNN). Firstly, NBC is used to identify the abnormal safety monitoring data. Then PNN is employed for sensor fault classification. The feasibility and effectiveness of this method are verified by applying it to the urban gas pipeline leakage monitoring system. It is shown that the abnormal monitoring data can be online distinguished, and sensor fault type can be effectively recognized. The global accuracy of abnormal data identification and the global accuracy of sensor fault diagnosis can reach 85% and 95%, respectively. This work can provide a guideline to improve the reliability of the urban gas pipeline monitoring systems.

Emergency Treatment of Leakage of Urban Gas Pipeline

Emergency Treatment of Leakage of Urban Gas Pipeline

Risk assessment of buried gas pipelines based on improved cloud-variable weight theory

Various risk factors of urban gas pipelines will lead to leakage, significantly impacting the environment, assets, and life safety, thus making pipeline risk prevention and control crucial. However, existing methods cannot sufficiently model the uncertainty in the pipeline risk evaluation process. In addition, the calculation method of factor weights may lead to unrealistic results. In this study, variable weight theory and cloud theory are introduced. Then, a novel method of cloud-variable weight function is proposed to analyze the pipeline's risk level and critical risk factors by establishing a pipeline risk assessment index system. The proposed method fully considers the uncertainty in the evaluation process, resolves the contradiction of existing methods to model the fuzzy concepts accurately, optimizes the weight distribution, and obtains a more scientific and reasonable assessment result. A case study is conducted on a pipeline in Beijing City. The results illustrate that the proposed method is beneficial for helping pipeline operators determine the pipeline risk status and weak links in the pipeline system, thereby providing a basis for risk control and rehabilitation.

Application of Kent Muhlbauer Method to Risk Assessment of Urban Gas Pipelines

AbstractOil and gas revenues play an important role in the Iranian economy and are the main source of government spending and a major part of commodity exports. Therefore, safe transport of these p...

Importance of corrosion protection on steel materials in reducing carbon emissions: Carbon emission measurement throughout the life cycle of steel pipeline as an example

<p indent="0mm">This paper studies the calculation method of carbon emissions throughout the life cycle of steel materials covering all stages of manufacturing, transportation, installation, service, and recycling. Taking steel pipelines as an example, this paper explores the impact of corrosion protection on the life cycle carbon emissions and annual average carbon emissions of steel materials. A carbon emission calculation method for all links in the life cycle of engineering steel materials in corrosive environments has been established. In addition to “carbon emissions per unit GDP (carbon emission intensity),” another intensity index is proposed as “life cycle average annual carbon emissions (carbon emissions per unit time).” This intensity index can constrain the life cycle carbon footprint in the time dimension. It is the first to quantify the important role of corrosion protection in controlling carbon emissions from steel materials at home and abroad. Through. Using appropriate anticorrosion technology, steel pipelines can reduce emissions by more than 60% in typical chemical production environments, more than 83% in oil and gas field environments, more than 50% in long-distance pipelines, and more than 28% in urban gas pipeline networks. This study is important in developing low-carbon corrosion control methods and improving corrosion protection, which controls the life cycle carbon emissions and annual average carbon emissions of steel materials, thereby providing a new perspective for the corrosion protection design and engineering implementation of steel structures. Consequently, it provides a new methodology for reducing carbon emissions of steel materials.

Data-driven accident consequence assessment on urban gas pipeline network based on machine learning

The accidents in Urban Pipeline Network (UPN) may cause enormous economic loss and serious threats to society and environment. The daily operation and maintenance of UPN is usually associated with many aspects of data. How to take full advantage of these multi-source data in combination with advanced data mining techniques to assess the post-event risk of pipeline accidents is of great significance to management of resilient urban systems. This work first summarizes the factors affecting accident consequence of gas UPN and establishes the risk evaluation indicators. A traditional risk assessment model based on the Kent index method and the analytic hierarchy process is then employed to determine the relative risk value of each pipeline. To reduce the dependency on experts’ subjective judgements or calculation of probability events in a Bayes decision procedure, a data-driven model based on graph embedding and clustering algorithm is proposed. The Graph Convolutional Network (GCN) technique is used to extract the topological features of pipeline network as a complement to the common attribute features considering the top pipelines usually bear comparable level of risks. A case study on a real gas pipeline network consisting of more than 6500 pipelines verifies the effectiveness of the proposed model.

Risk Assessment of Urban Gas Pipeline Based on Different Unknown Measure Functions

Risk Assessment of Urban Gas Pipeline Based on Different Unknown Measure Functions

An Accurate and Efficient Fitness-For-Service Assessment Method of Pipes with Defects under Surface Load

With continued urbanization in China, the construction of urban gas pipelines is increasing, and the safety of gas pipelines are also increasingly affected by urban development and the increased scope of buildings and roads. Pipes with defects are more likely to fail under the surface loads. In this study, uniaxial tensile tests of high-density polyethylene (HDPE) pipes were carried out to obtain the real material parameters of pipe. A pipeline-soil interaction finite element model of HDPE pipeline with defects under surface load was established. The failure mechanism of the urban gas pipeline was studied and the influence of parameters such as internal pressure, defect position, defect depth on the mechanical behavior, and failure of pipelines were analyzed. A failure criterion for HDPE pipes with defects under surface load was proposed based on the limit-state curves obtained under different working conditions. Furthermore, an accurate and efficient fitness-for-service assessment procedure of pipes with defects under surface load was proposed. The results showed that maximum Mises stress of the pipeline gradually increased with increasing surface load and the position of maximum stress changed from the top and bottom of the pipe to the defect position and both sides of the pipe. Finally, when Mises stress of the HDPE pipe exceeds the yield limit, failure will occur. Internal pressure, defect location, and defect depth were found to influence the failure process and critical surface load of the pipeline. Safety evaluation curves of the gas pipeline with defects under surface load were obtained by calculating the critical failure load of the pipeline under various working conditions. Finally, a nonlinear fitting method was used to derive a formula for calculating the critical surface load under different defect parameters. The proposed method provides a useful reference for urban gas pipeline safety management.

Development of modularized in-pipe inspection robotic system: MRINSPECT VII+

AbstractThis paper presents a modularized autonomous pipeline inspection robot called MRINSPECT VII+, which we recently developed. MRINSPECT VII+ is aimed at inspect in-service urban gas pipelines with a diameter of 200 mm. The robot consists of five basic modules: driving, sensing, joint, and battery modules. For nondestructive testing (NDT), an NDT module can be added to the system. The driving module uses a multiaxial differential gear mechanism to provide traction forces to the robot. The sensor module recognizes the pipeline element using position-sensitive detector (PSD) sensors and a CCD camera. The control module contains a computing unit and manages the robot’s autonomous navigation. The battery module supplies power to the system. Each module is connected via backdrivable active joint modules, which provide flexibility while moving inside narrow pipelines. Additionally, the wireless communication module helps the system communicate with the ground station. We tested MRINSPECT VII+ in real pipeline environments and validated its feasibility successfully.

Application of Pipe Jacking Construction Technology in Urban Gas Pipeline Construction

Application of Pipe Jacking Construction Technology in Urban Gas Pipeline Construction

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.

Simulation Research on Acoustic Detection Technology of Buried PE Pipes

Polyethylene (PE) pipe has been widely used in gas transportation pipeline system because it overcomes the shortcomings of non-corrosion resistance of metal pipelines. However, the stiffness and strength of PE pipe are small, and it is easy to be destroyed in the third-party construction process. Moreover, PE pipe is not electrically or magnetically conductive, and it is unable to use the developed metal pipe detection method, which has brought great security risks. Urban gas pipeline accidents occur frequently, and the situation during the production is complex and severe. Therefore, it is of great significance to study how to effectively realize the detection of underground PE pipe. This paper verifies the feasibility of the acoustic method from the perspective of simulation. Firstly, it studies the influence of buried pipe depth on the received signal of geophone. Secondly, it studies the influence of buried pipe size on the received signal of PE geophone with a certain depth Finally, it studies the received signal of geophone when PE pipe is in mixed soil. The simulation results show that the method based on acoustic wave is suitable, the signal source emits a sweeping frequency single tone sine wave, which propagates to the target and is reflected. A string of geophones on the ground measure the velocity of the surface vibration. Given the propagation rate of wave in the material, time delay can be used between signal sent and received on the ground to obtain the estimated distance to the target.

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.

Research on Multipoint Leak Location of Gas Pipeline Based on Variational Mode Decomposition and Relative Entropy

Pipeline leak detection has always been a relatively difficult technical problem; especially in urban pipeline leak detection, there are still many problems to be solved. A multipoint leak detection and location method for urban gas pipelines based on variational mode decomposition and relative entropy was proposed. Firstly, the experiment pipeline system was built, and the original signal was collected by acoustic emission technology; then, a variational model method was used to decompose the signal to obtain multiple intrinsic mode function (IMF) components with different characteristic scales. According to the characteristics of relative entropy, each component was analyzed, the appropriate IMF component was selected, and the selected component was reconstructed to obtain the observation signal. The multipoint leakage location model of the urban gas pipeline was established. The number of source signals was estimated by singular value decomposition, and the leakage signals were separated; finally, the accurate location of leakage point was achieved by cross-correlation positioning. The results showed that the average relative error of the pipeline leak location results is 2.97%, and the leak location accuracy is significantly improved, achieving the purpose of precise location.

Study on the Safety Risk Prevention Technology for the Urban Gas Pipeline

Along with the continuous development of our society and economy, the process of urbanization has been pushed forward. As one of the indispensable links in urbanization construction, the gas pipeline has brought great convenience to the life of urban residents, while has some potential safety hazards and brings certain risks to the life, property and safety of urban residents. The management status of the urban gas pipeline and safety risk prevention measures are mainly analyzed in this paper.