Long-distance Pipeline Research Articles

Efficient and Robust Temperature Field Simulation of Long-Distance Crude Oil Pipeline Based on Bayesian Neural Network and PDE

Efficient and Robust Temperature Field Simulation of Long-Distance Crude Oil Pipeline Based on Bayesian Neural Network and PDE

A Novel Deep Offline-to-Online Transfer Learning Framework for Pipeline Leakage Detection With Small Samples

In this article, a two-stage deep offline-to-online transfer learning framework (DOTLF) is proposed for long-distance pipeline leakage detection (PLD). At the offline training stage, a feature transfer-based long short-term memory network with regularization information (TL-LSTM-Ri) is developed where a maximum mean discrepancy regularization term is employed to extract domain-invariant features and an adjacent-bias-corrected regularization term is introduced to extract early fault features from pipeline samples under different scenarios. At the online detection stage, the trained TL-LSTM-Ri is employed for motion prediction, so as to monitor the operating condition of the pipeline in real time. To demonstrate its application potential, the DOTLF is successfully applied to handle the PLD problem on the long-distance oil–gas pipeline data. Experimental results demonstrate the effectiveness of the proposed DOTLF for real-time PLD under real-world scenarios.

The Development of Empirical Correlations to Understand the Frictional Behavior of Aqueous Biomass Slurry Flows in Vertical Pipes

Highlights The frictional pressure drop correlation of agricultural residue-water slurry flows in vertical pipes is developed. Multiple linear regression with the backward elimination method was used in RStudio to obtain the optimal model. Some regression coefficients differ for different types of biomass feedstocks. The predicted pressure drops agree well with the experimental data within a 95% CI. Empirical models for the onset velocity of drag reduction of different particle sizes of biomass are proposed. Abstract. Large-scale biofuel production at levels equivalent to conventional oil refineries using long-distance pipeline hydro-transport of biomass can be a cleaner alternative to fossil fuels when it comes to economics and traffic congestion associated with the overland transportation of biomass. The transport of aqueous slurries of several saturated mass concentrations (5%-40%) and four particle sizes (from <3.2-19.2 mm) of two types of agricultural residue biomass (ARB) feedstock (corn stover and wheat straw) was studied through a vertical test section of a 29 m long, 50 mm diameter closed circuit pipeline facility, and frictional pressure drops were recorded at different flow rates (0.5-4.3 m s-1). A framework was developed in RStudio (4.0.5) to analyze the experimentally obtained frictional pressure drops of biomass slurries through a multiple linear regression approach using a backward elimination method and Akaike information criterion. An empirical model was proposed to predict slurry frictional pressure drop in terms of slurry velocity, slurry solid mass concentration, particle aspect ratio, and feedstock type. The model satisfactorily predicted the frictional pressure drops of both feedstocks of biomass-water slurry flows through pipes within a 95% confidence interval. The correlations introduced for onset velocities of drag reduction in terms of slurry solid mass concentrations seemed helpful to interpret the transition points of the corresponding slurries in vertical upward flows through pipes. The empirical correlation developed in this research could help select biomass slurry pumps and pipe dimensions when designing a typical long distance pipeline network for biofuel production at the commercial level. Keywords: Agricultural biomass wastes, Frictional loss prediction, Numerical model, Onset velocity correlation, Regression coefficients, Upward pipe flow.

Pipeline Risk Assessment Using GIS

Long-distance energy pipelines are subject to risks of repeated hazards and posing pipeline safety problems. Hazards that may attack the pipelines are environmental and human activities. In this study, the risks of hazards on pipeline were assessed using Geographic Information System (GIS) as research on pipeline risk assessment using GIS is quite limited. Satellites help to monitor pipelines from space. The study spatially analyzes the risks that a pipeline encounters and the Kurdistan oil pipeline from Taq Taq oil field to Peshkhabur was used as a case study. Six criteria including distance to cities and villages, rivers, roads, slopes, and temperature in cold and hot weather were considered. Weight is given to each criterion; a maximum of 37.5% for human activities and a minimum weight of 12.5% for slope. The calculations were carried out spatially rather than through statistical operations. Three sets of maps were obtained for each criterion with different units. Then the maps were overlayed to represent a single map and the units were standardized using Fuzzy membership. The results show the risk level of each criterion along the 270 km length of the Kurdistan national pipeline.

Thermo-hydraulic coupled analysis of long-distance district heating systems based on a fully-dynamic model

The long-distance district heating pipeline (LDHP) system is a key solution for transporting the renewable heat from the suburban to urban areas. In LDHP, thermal and hydraulic characteristics are coupled. Developing effective thermo-hydraulic co-simulation method is vital to enhance LDHP’s operation performance and to enhance its flexibility. As the pressure wave travels much faster than the hot water in the district heating (DH) pipeline, the research in this regard mainly focuses on pseudo-dynamic model, in which the calculation of thermal dynamics only adopts the static hydraulic conditions. In this paper, a novel fully-dynamic model considering both the hydraulic transients and thermal dynamics is developed. The model is solved using the method of characteristic (MOC). The optimal spatial and temporal step sizes for the thermal dynamic modeling are analyzed and studied. Next, we compared our proposed model with the conventional pseudo-dynamic model on a 20 km LDHP. Results show that the simulated temperature fluctuations of the two models are close to each other, but the predicted temperature arriving at the heat exchange station is up to 28 s earlier than the pseudo-dynamic model, indicating that hydraulic transients have some influence thermal dynamics. Moreover, the fully-dynamic model has capability to predict the temperature and flow rate transport of the system in both disturbance state and steady state, which is important for the rapid and accurate analysis of the operation of LDHP.

Energy Consumption Optimization Model of Large Parallel Natural Gas Pipeline Network: Using Compressors with Multiple Operating Modes

In long-distance parallel pipelines, compressor stations are built together, and connecting pipes and cut-off valves are arranged between pipelines, which makes it possible for different stations to operate jointly or independently. In order to reduce pipeline energy consumption, this paper considers the valve switch state, deeply analyzes the station operation mode, and establishes the optimal model of minimum energy consumption of a parallel pipeline. Taking the second and third parallel pipelines of China’s west-east gas transmission as an example, the phasor particle swarm optimization algorithm is used to solve the model. The results show that after optimization, the internal flow was redistributed and energy consumption was reduced by 15.54%.

Shake table test and numerical analysis of the seismic response of buried long-distance pipeline under longitudinal non-uniform excitation

To investigate the seismic response characteristics of buried pipelines under longitudinal non-uniform seismic excitation, a three-dimensional finite element overall analysis model is established on finite element analysis software based on the shaking table test of buried oil and gas pipelines under longitudinal non-uniform excitation. The calculated results are compared with the experimental analysis results to evaluate the correctness and reliability of the established model. The acceleration response, strain response, and displacement response of buried oil and gas pipelines and surrounding soil under longitudinal traveling wave excitation at different seismic intensities are compared and analyzed using finite element models to supplement the test conditions. The test and analysis results show that the longitudinal displacements at each measurement point under longitudinal non-uniform excitation follow the same pattern except for differences in displacement magnitude and the vibration pattern of the tube and soil when the peak input acceleration reaches 1.00 g. As shown by both experimental and numerical simulation results, the soil acceleration amplification coefficients along the soil height fluctuate between 0.5 and 1.5. The pipe acceleration time curves and Fourier spectrum exhibit the same simulated and experimental pipe acceleration waveforms, and they both show significant amplification in the low to medium frequency band of 5–20 Hz. The testing and numerical simulated pipeline axial strain peak curves are similar and in good agreement, indicating the high reliability of the experimental results.

Weldability evaluation of X80 sour line pipe using a combination of thermal simulation and actual girth welding

The weldability studies of API 5LX80 pipes developed for sour service are very recent and limited information about its heat-affected zone (HAZ) properties can be found. This paper presents a comprehensive evaluation of HAZ using both thermal simulation and the production of actual girth weld joints. The test methodology included microstructural analysis, Charpy impact test, hardness (HV10), microhardness (HV0.1), and sulfide stress cracking tests (SCC). The intercritical coarse grain HAZ presented impact toughness reduction from values above 300 J to less than 50 J at 0 °C when heat input is increased above 1.5 kJ/mm. It can be explained by grain coarsening and martensite-austenite (MA) formation as a ‘necklace’ structure at previous austenite grain boundaries. Hardness and microhardness values for both simulated and actual HAZ were below the maximum limit of 250HV usually specified by industry. Specimens submitted to the sulfide stress cracking (SSC) tests did not present any crack demonstrating that the welded joint is appropriate for sour environments. Finally, a maximum heat input of 1.5 kJ/mm is recommended for field welding. For higher heat inputs, a deeper evaluation of HAZ toughness should be done. The results contribute to supporting the application of this material as an alternative for long-distance high-pressure pipelines with H2S.

Application of Bispectrum Dimensionality Reduction Method in Ultrasonic Echo Signal Processing

Processing ultrasonic echo signals to obtain high-precision residual thickness information of the pipeline wall is the key to nondestructive testing of corrosion of a long-distance pipeline. The traditional power spectrum estimation method assumes that an analyzed echo signal is Gaussian, and the useful information is insufficiently extracted, which leads to errors in the processing results. In this paper, to solve this problem, the bispectrum, which requires the least amount of computation in higher-order spectral estimation, is proposed to process an echo signal with a non-minimum phase and non-Gaussian characteristics. The bispectrum is projected onto a one-dimensional frequency space using the dimensionality reduction method, and one-dimensional diagonal slices of the bispectrum are extracted to analyze the characteristics of the echo signal, which significantly improves the intuitiveness of data processing. The experimental results show that the bispectrum dimensionality reduction method has high accuracy in processing ultrasonic echo signals, and the relative error of the residua wall thickness is below 2%. A C-scan image displaying the shape, size, depth, and other characteristics of pipeline corrosion obtained by the proposed method is much better than that using the traditional power spectrum estimation method. Therefore, the proposed method is suitable for nondestructive testing of corrosion of long-distance pipelines.

Φ-OTDR Signal Identification Method Based on Multimodal Fusion.

Distributed fiber optic sensing (DFS) systems are an effective method for long-distance pipeline safety inspections. Highly accurate vibration signal identification is crucial to DFS. In this paper, we propose an end-to-end high-accuracy fiber optic vibration signal detection and identification algorithm by extracting features from the time domain and frequency domain by a one-dimensional convolutional neural network and two-dimensional convolutional neural network, respectively, and introducing a self-attentive mechanism to fuse the features of multiple modes. First, the raw signal is segmented and normalized according to the statistical characteristics of the vibration signal combined with the distribution of noise. Then, the one-dimensional sequence of vibration signal and its two-dimensional image generated by short-time Fourier transform are input to the one-dimensional convolutional neural network and two-dimensional neural network, respectively, for automatic feature extraction, and the features are combined by long and short-time memory. Finally, the multimodal features generated from the time and frequency domains are fused by a multilayer TransformerEncoder structure with a multiheaded self-attentive mechanism and fed into a multilayer perceptron for classification. Experiments were conducted on an urban field database with complex noise and achieved 98.54% accuracy, which demonstrates the effectiveness of the proposed algorithm.

Variation of microplastics and biofilm community characteristics along the long-distance raw water pipeline

The massive accumulation of microplastics (MPs) in aquatic environments and water treatment plants and their potential threat to human health have attracted widespread attention. The water quality indices, occurrence characteristics of MPs, and changes in the pipe wall biofilm structure along long-distance raw water pipelines in Jiangsu were studied, and the key factors influencing the variation in microbial community structure were revealed. The results demonstrated that the types of MPs detected in long-distance raw water pipelines were mainly polypropylene (PP), polyethylene (PE), polystyrene (PS), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The total abundance of MPs decreased significantly with an increase in the conveying distance, from 1570.8 n·L−1 at water intake to 377.0 n·L−1 at the end of the pipeline network. Small-scale MPs were the most abundant, maintaining the highest concentration of 300–700 n·L−1. The decrease along the pipeline was more obvious for MPs with larger densities and particle sizes. Physical sedimentation and biosorption by extracellular polymeric substances may be the means by which MPs are removed. The diversity of bacterial communities in the pipe wall biofilms changed significantly along the pipeline, but the predominant bacterial groups at each sampling point were similar at different taxonomic levels. RDA showed that the effects of DOC (41.6 %), CODCr (33.5 %), and MPs abundance (30.1 %) were comprehensive and were the top three key factors affecting the variation in the biofilm community characteristics along the pipeline.

Classification of damage types in liquid-filled buried pipes based on deep learning

In long-distance pipelines, this type of local damage can lead to different forms of damage. Ultrasound (UT)-guided wave technology can detect channel damage at a distance and reduce the workforce and material resources. Deep learning has the advantages of high efficiency and accuracy for pipeline damage classification and identification. This study proposes a classification method that combines UT-guided waves with deep residual neural networks. First, the time-series data of the defect echoes are encoded into different types of images using the glare angular field matrix. Then, the features of the generated images are extracted using ResNet. Finally, it is put into Faster-RCNN for training, validation and defect type recognition. Finite element models containing cracked, square and circular defects were built to verify the effectiveness of the method. The network models were trained for classification, testing and validation using pipes with broken defects. Finite element analysis results show that the network model classifies cracked, square and circular defects with different damage levels with accuracy, recall and F1-score indices close to 90%, and the experimental results show that the network model has an identification accuracy of approximately 90%. Furthermore, the results show that the Faster-RCNN-ResNet model is more accurate in identifying complex pipeline defect types than machine learning and other deep learning methods. The model shows good feasibility and effectiveness in classifying the damage types of long-transmission buried 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.

A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction

The accurate prediction of natural gas consumption plays a central role in long-distance pipeline system production and transportation planning, and it becomes even more important during present political situation. The existing prediction methods for natural gas consumption barely consider spatial correlations and domain knowledge. As a result, the study proposes a novel deep learning prediction method (knowledge-enhanced graph-based temporal-spatial network, abbreviated to KE-GB-TSN) for predicting natural gas consumption by integrating domain knowledge into association graph construction and capturing temporal-spatial features via a hybrid deep learning network. This study first applies the domain knowledge that analyses the operation technique of the natural gas pipeline network and combines the historical data to establish an association graph. Subsequently, the historical data and association graphs are input to a hybrid deep learning network to predict natural gas consumption. The comparative experiments are conducted by taking real-world cases of natural gas consumption as examples. At last, a sensitivity analysis of different components combination is carried out to exhibit the significance of each component in the proposed model. The results prove that the proposed model is capable of achieving more accurate and efficient predicted results compared to the advanced models, such as decision trees and gated recurrent units. The Mean Absolute Relative Errors and Root Mean Squared Relative Errors gotten by the proposed model are less than 0.11 and 0.14 in all cases, indicating an improvement compared to previous works. Additionally, it is also suggested that domain knowledge and temporal-spatial correlations are crucial for the excellent performance of the prediction model.

Comparison of maize stover and wheat straw slurry flow in vertical pipes

The scale-up of biorefineries to compete with fossil fuel production is limited by the high overland transportation cost of lignocellulosic biomass. Pipeline hydro-transport of agricultural or forest residue biomass to biorefineries could be a cost-effective and sustainable solution to this problem. The upward flow of chopped maize stover (also known as corn stover) aqueous slurries through a vertical pipe section of a 29 m long, 50 mm diameter in a closed pipeline loop was studied. The frictional pressure drops of maize stover slurries were measured at several particle sizes (from <3.2–19.2 mm), slurry solid concentrations (5–40% [mass]), and slurry velocities (0.5–4.3 m s −1 ). The results were analysed and compared with wheat straw. For specific concentrations and flow rates, particle size, shape, and flexibility are the factors that most reduced drag, which was highest (by 32%) for the largest particle size of maize stover. For velocities ≥2.5 m s −1 , maize stover suspensions (other than the 3.2 mm particle size) were more effective in reducing drag than wheat straw, whereas at lower velocities (≤2.0 m s −1 ), wheat straw had more influence (other than the 19.2 mm). The results for critical concentrations for maximum drag reduction, onset velocity, threshold concentration for minimum onset velocity, and their variations with respect to particle size, particle type, and slurry concentrations provide new insights that require further investigation in larger diameter pipes. The results here will be beneficial for the design and operation of long-distance pipeline hydro-transport of biomass. • Hydro-transport of ground maize stover was examined in a vertical pipe section. • Frictional behaviour of two feedstocks was compared at various flow conditions. • Particle size, shape, and fibre flexibility were dominant in drag reduction (DR). • Onset velocity of DR lowest for largest particle size of maize stover. • Critical concentration for the maximum DR of maize stover lower than wheat straw.

Numerical Method for System Level Simulation of Long-Distance Pneumatic Conveying Pipelines

Pneumatic conveying pipelines (PCPs) provide an effective manner for long-distance transport of capsules because of their advantages in high speed, superior safety, and full automation. For better development of PCPs, a system-level simulation tool is desired, but not yet available. In this work, a new 1D model describing systemic dynamics of airflow and capsule movement in PCPs is presented, and 3D simulation is proposed to obtain the characteristic coefficients in the 1D model. The complete model accounts for those phenomena that most profoundly affect the performance of PCPs, such as the 3D layout of the pipeline, the geometry of capsules, as well as the compressibility of air in a long pipeline. A finite volume method is also presented to numerically calculate the model equations, and thereby realize the successful system-level simulation of practical PCPs for the first time. Experimental data were used for validation. For a 550 m-long and small-diameter (27.86 mm) PCP, the errors of predicted conveying times were within 4.43%. For another 30 m-long and large-diameter (125.6 mm) PCP, the errors of predicted conveying time and maximum capsule velocity were within 1%. By enabling readily and accurate prediction of the conveying process, the method provides a feasible tool for the design and application of PCP systems.

A collision-free gallop-based triboelectric-piezoelectric hybrid nanogenerator

Energy harvesting technologies that convert fluid energy into usable electrical energy are of great significance, especially in long-distance pipeline systems. Here, in order to avoid the collision of conventional galloping triboelectric nanogenerators (GTENGs), and cause material damage or noise, a freestanding gallop-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed to reduce material wear and improve the reliability of GTENG. Two piezoelectric sheets are attached to the cantilever beam. The root-mean-square (RMS) and peak output power of the HG P-TENG are 68.9μW and 1.27 mW, respectively. To improve the harvesting efficiency, the fixed copper electrodes are segmented, and experiments indicate that this way of segmenting electrodes can improve theenergy harvesting efficiency. Finer electrodes can effectively increase the charging rate of capacitors. A self-powered thermohygrometer and light-emitting diodes (LEDs) are demonstrated in the wind tunnel. It demonstrates that the proposed hybrid nanogenerator will exhibit great potential in pipeline systems.

A dynamic fracture finite element model of the buried gas transmission pipeline combining soil constraints and gas decompression

A long-distance natural gas transmission pipeline is the primary solution for natural gas resource distribution. In fact, the longitudinal crack propagation of gas transmission pipelines has always been a concern of the natural gas industry. Because it will cause disastrous accidents once the ductile crack in the pipeline propagates rapidly. Most natural gas transmission pipelines are buried underground to improve the safety of pipeline operation as the backfill soil can absorb energy during the fracture process and restrain the displacements of the flaps. Fracture control is a fundamental requirement for the safe operation of underground pipelines. In this study, the dynamic fracture finite element model of the buried gas pipeline is developed to simulate the actual fracture process instead of the costly full-scale burst experiments. The finite element model incorporates different external soil constraints and internal gas decompression behaviors during pipe rupture in which soil constraints are represented by discrete soil springs, and a user-defined subroutine realizes the gas decompression behavior. The explicit dynamic analysis is employed to simulate the high-speed dynamic fracture process of the pipeline, and the crack propagation is simulated by using the cohesive zone model. Finally, the crack propagation velocity is calculated by this model, and the influence of different internal pressures on the fracture velocity is studied; the crack tip opening angle (CTOA) is predicted, and the effect of soil spring stiffness on CTOA is evaluated.

A finite difference-based approach for strain demand prediction of inelastic pipes subjected to permanent ground displacements

Permanent ground displacement triggered by geohazards constitutes a major threat to the integrity of long-distance pipelines. In this study, a novel and simple method is proposed to evaluate inelastic pipes’ behavior under ground movements considering soil-pipe interaction based on the finite difference method. The existing finite difference-based method previously proposed by the authors for strain analysis of buried pipelines subjected to ground movements excludes material nonlinearity in pipes, which limits its applicability in engineering practice. To remedy this situation, the method presented herein maintains the well-established concepts of the existing finite-difference-based method but also introduces the scheme to consider the inelastic material behavior of steel pipes. More specifically, the expressions of internal axial force and bending moment, required in the finite difference equations, are explicitly derived based on the actual stress distribution on the pipe cross-section. The proposed method is validated against the finite element method (one-dimensional beam model) in terms of the strain and deformation demands using two indicative case studies, referred to as symmetric and non-symmetric soil resistance conditions, respectively. The comparison between finite element analysis and the proposed method indicates good agreement. Additionally, the proposed method is compared with four existing analytical methods for pipes subjected to strike-slip fault displacement. The proposed method is a simple but general technique to analyze pipes’ response under a wide range of geohazards, and thus can be potentially used as an alternative method for preliminary design, safety prescreening, and reliability-based assessment of pipes against geohazards.

Groundwater as emergency water supply: case study of the 2016 Kumamoto Earthquake, Japan

Securing water supply is an extremely important issue following an earthquake. Recent earthquakes in Japan have prompted focus on the use of groundwater or disaster emergency wells (DEWs). Water supply networks are vulnerable to earthquakes because they comprise long-distance pipelines that are not always earthquake-resistant. Groundwater, however, can usually be found directly below an area where water is required and can serve as an alternative water source. Although previous studies discussed the importance of groundwater in relation to natural disasters, with special reference to drought, little attention has been given to the use of groundwater following earthquakes. In this study, two questionnaire surveys were conducted of DEW owners and welfare facilities for elderly people in Kumamoto (Japan), which was struck by an Mw 7.3 earthquake in 2016, to identify the advantages and disadvantages of using groundwater as an emergency water supply and ascertain policy issues to be resolved for making DEWs effective. Results showed that not only 30 DEWs but also at least 25 privately owned wells not registered as DEWs were open to the public in the early restoration stage, improving people’s access to water and decreasing the burden on the Kumamoto city government’s emergency water supply. However, it was revealed that groundwater might not always be potable owing to quality concerns. Additionally, only a limited number of welfare facilities used the available adjacent DEWs and DEW recognition level remains low. These findings indicate that improving information disclosure regarding emergency groundwater use is a policy issue to be resolved.