Numerical simulation of a gas pipeline network using computational fluid dynamics simulators

This article describes numerical simulation of gas pipeline network operation using high-accuracy computational fluid dynamics (CFD) simulators of the modes of gas mixture transmission through long, multi-line pipeline systems (CFD-simulator). The approach used in CFD-simulators for modeling gas mixture transmission through long, branched, multi-section pipelines is based on tailoring the full system of fluid dynamics equations to conditions of unsteady, non-isothermal processes of the gas mixture flow. Identification, in a CFD-simulator, of safe parameters for gas transmission through compressor stations amounts to finding the interior points of admissible sets described by systems of nonlinear algebraic equalities and inequalities. Such systems of equalities and inequalities comprise a formal statement of technological, design, operational and other constraints to which operation of the network equipment is subject. To illustrate the practicability of the method of numerical simulation of a gas transmission network, we compare computation results and gas flow parameters measured on-site at the gas transmission enter-prise.

Development of an integrated dynamic model for supply security and resilience analysis of natural gas pipeline network systems

An integrated dynamic model of natural gas pipeline networks is developed in this paper.Components for gas supply,e.g.,pipelines,junctions,compressor stations,LNG terminals,regulation stations and gas storage facilities are included in the model.These components are firstly modeled with respect to their properties and functions and,then,integrated at the system level by Graph Theory.The model can be used for simulating the system response in different scenarios of operation,and evaluate the consequences from the perspectives of supply security and resilience.A case study is considered to evaluate the accuracy of the model by benchmarking its results against those from literature and the software Pipeline Studio.Finally,the model is applied on a relatively complex natural gas pipeline network and the results are analyzed in detail from the supply security and resilience points of view.The main contributions of the paper are:firstly,a novel model of a complex gas pipeline network is proposed as a dynamic state-space model at system level;a method,based on the dynamic model,is proposed to analyze the security and resilience of supply from a system perspective.

Study on Simulation Method of Pipeline Networks' Dynamic Characteristic in Hydraulic Manifold Block

In the design of Hydraulic Manifold Blocks (HMB), dynamic performance of inner pipeline networks usually should be evaluated. To meet the design requirements, dynamic characteristic simulation is often needed. Based on comprehensive study on the existing simulation methods, a new method combined of Power Bond Graph(PBG) and Computational Fluid Dynamic (CFD) is proposed. In this method, flow field of typical channels inside HMB is analyzed with CFD to obtain the local resistance coefficients. Then, with these coefficients, a new sectional lumped-parameter model including kinetic friction factor is developed using PBG. A typical HMB design example is given and the comparison between the simulation and the experimental results demonstrates the feasibility and effectiveness of the proposed method.

Research on Optimization Operation of Urban Gas Pipeline Network

The optimiz at ion operation of gas pipeline network is investigated in this paper. Based on th e theories of system optimization and the multi object decision, a mathematical model about the multi object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. A t the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The resul ts indicated that 2.13% energy consumption and 3.12% gas supply cost can be reduced through optimization operation.

Simulation of natural gas transmission pipeline network system performance

Simulation has proven to be an effective tool for analyzing pipeline network systems （PNS） in order to determine the design and operational variables which are essential for evaluating the performance of the system. This paper discusses the use of simulation for performance analysis of transmission PNS. A simulation model was developed for determining flow and pressure variables for different configuration of PNS. The mathematical formulation for the simulation model was derived based on the principles of energy conservation, mass balance, and compressor characteristics. For the determination of the pressure and flow variables, solution procedure was developed based on iterative Newton Raphson scheme and implemented using visual C＋＋6. Evaluations of the simulation model with the existing pipeline network system showed that the model enabled to determine the operational variables with less than ten iterations. The performances of the compressor working in the pipeline network system xvhich includes energy consumption, compression ratio and discharge pressure were evaluated to meet pressure requirements ranging from 4000-5000 kPa at various speed. Results of the analyses from the simulation indicated that the model could be used for performance analysis to assist decisions regarding the design and optimal operations of transmission PNS.

A two-stage optimization method for unmanned aerial vehicle inspection of an oil and gas pipeline network

Oil and gas pipeline networks are a key link in the coordinated development of oil and gas both upstream and downstream.To improve the reliability and safety of the oil and gas pipeline network, inspections are implemented to minimize the risk of leakage, spill and theft, as well as documenting actual incidents. In recent years, unmanned aerial vehicles have been recognized as a promising option for inspection due to their high efficiency. However, the integrated optimization of unmanned aerial vehicle inspection for oil and gas pipeline networks, including physical feasibility, the performance of mission, cooperation, real-time implementation and three-dimensional(3-D) space, is a strategic problem due to its large-scale,complexity as well as the need for efficiency. In this work, a novel mixed-integer nonlinear programming model is proposed that takes into account the constraints of the mission scenario and the safety performance of unmanned aerial vehicles. To minimize the total length of the inspection path, the model is solved by a two-stage solution method. Finally, a virtual pipeline network and a practical pipeline network are set as two examples to demonstrate the performance of the optimization schemes. Moreover, compared with the traditional genetic algorithm and simulated annealing algorithm, the self-adaptive genetic simulated annealing algorithm proposed in this paper provides strong stability.

Numerical forecasting surge in a piping of compressor shops of gas pipeline network

This paper presents a method of forecasting stable operation of gas compressor unit (GCU) centrifugal supercharger (CFS) installed on a piping of compressor shops servicing gas pipelines. The stability of superchargers operation is assessed in relation to the phenomenon of surge. Solution of this problem amounts to the development and numerical analysis of a set of ordinary differential equations. The set describes transmission of gas through a compressor shop as a fluid dynamics model with lumped parameters. The proposed method is oriented to wide application by specialists working in the gas industry. The practical application of this method can use all-purpose programming and mathematical software available to specialists of gas companies.

Spatial analysis for underground pipeline network information system

It is appropriate to establish underground pipeline network information system based on MapInfo software platform in many enterprises when taking account of the firm size and data amount. Since some functions of MapInfo in spatial analysis are not very strong relatively, it is difficult for MapInfo to fulfill some common functions about pipeline analysis such as spatial configuration, three-dimensional display, pipe exploding and so on. The thought and arithmetic to solve the above problems are approached based on respect theories of computer graphics and graph theory. A variety of function moduli have developed by means of senior computer languages and the system integration is realized.

Natural Gas Gathering and Transporting Pipeline Networks in Sichuan Province

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Computational Tools to Support Ethanol Pipeline Network Design Decisions

This paper considers the pipeline network design problem (PND) in ethanol transportation, with a view to providing robust and efficient computational tools to assist decision makers in evaluating the technical and economic feasibility of ethanol pipeline network designs. Such tools must be able to address major design decisions and technical characteristics, and estimate network construction and operation costs to any time horizon. The specific context in which the study was conducted was the ethanol industry in Sao Paulo. Five instances were constructed using pseudo-real data to test the methodologies developed.

Knowledge Based Pipeline Network Classification and Recognition Method of Maps

Map recognition is an essential data input means of Geographic Information System (GIS). How to solve the problems in the procedure, such as recognition of maps with crisscross pipeline networks, classification of buildings and roads, and processing of connected text, is a critical step for GIS keeping high-speed development. In this paper, a new recognition method of pipeline maps is presented, and some common patterns of pipeline connection and component labels are established. Through pattern matching, pipelines and component labels are recognized and peeled off from maps. After this approach, maps simply consist of buildings and roads, which are recognized and classified with fuzzy classification method. In addition, the Double Sides Scan (DSS) technique is also described, through which the effect of connected text can be eliminated.

An optimal flow rate allocation model of the oilfield treated oil pipeline network

Oilfield treated oil pipeline network is the link connecting the upstream oilfields and the downstream refineries.Due to the differences in operating costs and transportation fee between different pipelines and the fluctuation in the demand and sales prices of the treated oil,there is an optimal flow allocation plan for the pipeline network to make the oilfield company obtain the highest social and economic benefit.In this study,a mixed integer nonlinear programming(MINLP)model is developed to determine the optimal flow rate allocation plan of the large-scale and complex treated oil pipeline network,and both the social and economic benefits are considered simultaneously.The optimization objective is the multi-objective which includes the largest user satisfaction and the highest economic benefit.The model constraints include the oilfield production capacity,refinery demand,pipeline transmission capacity,flow,pressure,and temperature of the node and station,and the pipeline hydraulic and thermal calculations.Python 3.7 is utilized for the programming of the off-line calculation procedure and the MINLP model,and GUROBI 9.0.2 is served as the MINLP solver.Moreover,the model is applied to a real treated oil pipeline network located in China,and three optimization scenarios are analyzed.For social benefit,the values of the user satisfaction of each refinery and the total network are 1 before and after optimization for scenarios 1,2,and 3.For economic benefit,the annual revenue can be increased by 0.227,0.293,and 0.548 billion yuan after the optimization in scenario 1,2,and 3,respectively.

Stress corrosion cracking behavior of buried oil and gas pipeline steel under the coexistence of magnetic field and sulfate-reducing bacteria

Magnetic field and microorganisms are important factors influencing the stress corrosion cracking(SCC)of buried oil and gas pipelines. Once SCC occurs in buried pipelines, it will cause serious hazards to the soil environment. The SCC behavior of X80 pipeline steel under the magnetic field and sulfate-reducing bacteria(SRB) environment was investigated by immersion tests, electrochemical tests, and slow strain rate tensile(SSRT) tests. The results showed that the corrosion and SCC sensitivity of X80 steel decreased with increasing the magnetic field strength in the sterile environment. The SCC sensitivity was higher in the biotic environment inoculated with SRB, but it also decreased with increasing magnetic field strength, which was due to the magnetic field reduces microbial activity and promotes the formation of dense film layer. This work provided theoretical guidance on the prevention of SCC in pipeline steel under magnetic field and SRB coexistence.

SDH-FCOS:An Efficient Neural Network for Defect Detection in Urban Underground Pipelines

Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect detection in urban underground pipelines,this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector(FCOS),called spatial pyramid pooling-fast(SPPF)feature fusion and dual detection heads based on FCOS(SDH-FCOS)model.This study improved the feature fusion component of the model network based on FCOS,introduced an SPPF network structure behind the last output feature layer of the backbone network,fused the local and global features,added a top-down path to accelerate the circulation of shallowinformation,and enriched the semantic information acquired by shallow features.The ability of the model to detect objects with multiple morphologies was strengthened by introducing dual detection heads.The experimental results using an open dataset of underground pipes show that the proposed SDH-FCOS model can recognize underground pipe defects more accurately;the average accuracy was improved by 2.7% compared with the original FCOS model,reducing the leakage rate to a large extent and achieving real-time detection.Also,our model achieved a good trade-off between accuracy and speed compared with other mainstream methods.This proved the effectiveness of the proposed model.

The Spatial Optimization of Eastern China's Crude Oil Pipeline Network upon Cost Minimum

Eastern China＇s crude oil pipeline network is of the largest scale and freight volume in China.Here,we analyze 37 oil pipelines and one railway（38 oil flow channels）,20 oil fields with output of over a million tons of crude oil,and 32 refineries each of which refine over a million tons of crude oil.We construct a supply and demand balance sheet of oil sources and sinks by considering the transportation cost variance of variant pipeline diameters to determine the spatial optimization of Eastern China＇s pipeline network.In 2009,the optimal cost of this network was 34.5% lower than the total actual cost,suggesting that oil flow is overall inefficient and there is huge potential to improve flow efficiency.Within Eastern China,the oil flow of the Northeast network was relatively better than others,but the flow in Northern China is inefficient because all pipelines are underload or noload,and there were similar conditions in the Huanghuai region.We assumed no difference in pipeline transport speed,compared to rail or road transportation,thus transportation distance,rather than time,is the main influential factor under the definite transporting cost of variant pipeline diameters.

Fuzzy Reliability Analysis for Seabed Oil Gas Pipeline Networks Under Earthquakes

The seabed oil gas pipeline network is simplified to a network with stochastic edge weight by means of the fuzzy graphics theory. With the help of network analysis, fuzzy mathematics, and stochastic theory, the problem of reliability analysis for the seabed oil gas pipeline network under earthquakes is transformed into the calculation of the transitive closure of fuzzy matrix of the stochastic fuzzy network. In classical network reliability analysis, the node is supposed to be non invalidated; in this paper, this premise is modified by introducing a disposal method which has taken the possible invalidated node into account. A good result is obtained by use of the Monte Carlo simulation analysis.

Cost Minimization of Wireless Sensor Networks with Unlimited-lifetime Energy for Monitoring Oil Pipelines

Cyber-physical-system (CPS) has been widely used in both civil and military applications. Wireless sensor network (WSN) as the part and parcel of CPS faces energy problem because sensors are battery powered, which results in limited lifetime of the network. To address this energy problem, we take advantage of energy harvesting device (EHD) and study how to indefinitely prolong oil pipeline monitoring network lifetime by reasonable selecting EHD. Firstly, we propose a general strategy worst case-energy balance strategy (WC-EBS), which defines worst case energy consumption (WCEC) as the maximum energy sensor node could expend for oil pipeline monitoring WSN. When the energy collected by EHD is equal or greater than WCEC, network can have an unlimited lifetime. However, energy harvesting rate is proportional to the price of EHD, WC-EBS will cause high network cost. To reduce network cost, we present two optimization strategies, optimization workloadenergy balance strategy (OW-EBS ) and optimization first nodeenergy balance strategy (OF-EBS). The main idea of OW-EBS is to cut down WCEC by reducing critical node transmission workload; OF-EBS confirms critical node by optimizing each sensor node transmission range, then we get the optimal energy harvesting rate in OF-EBS. The experimental results demonstrate that OF-EBS can indefinitely extend network lifetime with lower cost than WC-EBS and OW-EBS, and energy harvesting rate P in each strategy satisfies POF-EBS ≤POW-EBS ≤PWC-EBS. © 2014 Chinese Association of Automation.

A Novel Parameter-Optimized Recurrent Attention Network for Pipeline Leakage Detection

Accurate detection of pipeline leakage is essential to maintain the safety of pipeline transportation.Recently,deep learning(DL)has emerged as a promising tool for pipeline leakage detection(PLD).However,most existing DL methods have difficulty in achieving good performance in identifying leakage types due to the complex time dynamics of pipeline data.On the other hand,the initial parameter selection in the detection model is generally random,which may lead to unstable recognition performance.For this reason,a hybrid DL framework referred to as parameter-optimized recurrent attention network(PRAN)is presented in this paper to improve the accuracy of PLD.First,a parameter-optimized long short-term memory(LSTM)network is introduced to extract effective and robust features,which exploits a particle swarm optimization(PSO)algorithm with cross-entropy fitness function to search for globally optimal parameters.With this framework,the learning representation capability of the model is improved and the convergence rate is accelerated.Moreover,an anomaly-attention mechanism(AM)is proposed to discover class discriminative information by weighting the hidden states,which contributes to amplifying the normalabnormal distinguishable discrepancy,further improving the accuracy of PLD.After that,the proposed PRAN not only implements the adaptive optimization of network parameters,but also enlarges the contribution of normal-abnormal discrepancy,thereby overcoming the drawbacks of instability and poor generalization.Finally,the experimental results demonstrate the effectiveness and superiority of the proposed PRAN for PLD.

The Study of Electromagnetic Stress Testing Method on Oil-Gas Pipelines Based on WT

This paper proposes an effective method for early diagnosis (stress concentrating) of the oil-gas pipeline. Based on the principle of electromagnetic induction Faraday, we have designed and realized the nondestructive testing system for stress concentration area of ferromagnetic materials by means of the research of metal materials inverse magnetostrictive effect mechanism. The system changes the influence degree of the stress in ferromagnetic materials’ magnetic conductance to the corresponding voltage array by using discrete wavelet analysis method to process the data, in which not only the measuring accuracy is improved, but also the stress concentration is more directly reflected. The experiments confirm that the electromagnetic stress testing method is feasible and valid.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.