Search Results (978)

Clean hydrogen is a key aspect of carbon neutrality, necessitating robust methods for monitoring hydrogen concentration in critical infrastructures like pipelines or power plants. While semiconducting metal oxides such as In₂O₃ can monitor gas concentrations down to the ppm range, they often exhibit cross-sensitivity to other gases like H₂O. In this study, we investigated whether cyclic optical illumination of a gas-sensitive In₂O₃ layer creates identifiable changes in a gas sensor’s electronic resistance that can be linked to H₂ and H₂O concentrations via machine learning. We exposed nanostructured In₂O₃ with a large surface area of 95 m² g⁻¹ to H₂ concentrations (0–800 ppm) and relative humidity (0–70%) under cyclic activation utilizing blue light. The sensors were tested for 20 classes of gas combinations. A support vector machine achieved classification rates up to 92.0%, with reliable reproducibility (88.2 ± 2.7%) across five individual sensors using 10-fold cross-validation. Our findings suggest that cyclic optical activation can be used as a tool to classify H₂ and H₂O concentrations. Full article

Unsteady gas-dynamic phenomena in pipelines of complex configuration are widespread in heat exchange and power equipment. Therefore, studying the heat transfer level of pulsating air flows in round and triangular pipes with different turbulence intensities is a relevant and significant task for the development of science and technology. The studies were conducted on a laboratory stand based on the thermal anemometry method and an automated system for collecting and processing experimental data. Rectilinear round and triangular pipes with identical cross-sectional areas were used in the work. Flow pulsations from 3 to 15.8 Hz were generated by means of a rotating flap. The turbulence intensity (TI) of the pulsating flows varied from 0.03 to 0.15 by installing stationary flat turbulators. The working medium was air with a temperature of 22 ± 1 °C moving at a speed from 5 to 75 m/s. It was established that the presence of gas-dynamic unsteadiness leads to an increase in the TI by 47–72% in a round pipe and by 36–86% in a triangular pipe. The presence of gas-dynamic unsteadiness causes a heat transfer intensification in a round pipe by 26–35.5% and by 24–36% in a triangular pipe. It was shown that a significant increase in the TI of pulsating flows leads to an increase in the heat transfer coefficient by 11–16% in a round pipe and a decrease in the heat transfer coefficient by 7–24% in a triangular pipe. The obtained results can be used in the design of heat exchangers and gas exchange systems in power machines, as well as in the creation of devices and apparatuses of pulse action. Full article

The existing natural gas transportation pipelines can withstand a hydrogen content of 0 to 50%, but further research is still needed on the pathways of NO and CO production under moderate or intense low oxygen dilution (MILD) combustion within this range of hydrogen blending. In this paper, we present a computational fluid dynamics (CFD) simulation of hydrogen-doped jet flame combustion in a jet in a hot coflow (JHC) burner. We conducted an in-depth study of the mechanisms by which NO and CO are produced at different locations within hydrogen-doped flames. Additionally, we established a chemical reaction network (CRN) model specifically for the JHC burner and calculated the detailed influence of hydrogen content on the mechanisms of NO and CO formation. The findings indicate that an increase in hydrogen content leads to an expansion of the main NO production region and a contraction of the main NO consumption region within the jet flame. This phenomenon is accompanied by a decline in the sub-reaction rates associated with both the prompt route and NO-reburning pathway via CH_i=0–3 radicals, alongside an increase in N₂O and thermal NO production rates. Consequently, this results in an overall enhancement of NO production and a reduction in NO consumption. In the context of MILD combustion, CO production primarily arises from the reduction of CO₂ through the reaction CH₂(S) + CO₂ ⇔ CO + CH₂O, the introduction of hydrogen into the system exerts an inhibitory effect on this reduction reaction while simultaneously enhancing the CO oxidation reaction, OH + CO ⇔ H + CO₂, this dual influence ultimately results in a reduction of CO production. Full article

A subway station’s operation is susceptible to accidents when there is a high-pressure gas pipeline overlaying it, and analyzing the correlations between the safety influencing factors (SIFs) in this operating situation can provide paths to reduce safety accidents. Thus, this paper investigated the coupling correlations between the SIFs. We firstly identified the SIFs during subway station operation under a high-pressure pipeline (SSOUHP) based on a literature review and discussion with experts. Then, the analytic hierarchy process (AHP) and coupling degree analysis (CDA) were combined to assess the coupling correlations between the SIFs, and Y subway station was selected to test the proposed hybrid coupling analysis approach. Research results show that (a) 23 second-level SIFs were identified and these SIFs can be summed up into five first-level SIFs, namely, human-related SIFs, pipeline-related SIFs, station-related SIFs, environment-related SIFs, and management-related SIFs; (b) the proposed hybrid approach can be used to evaluate the coupling correlations between SIFs; (c) of the coupling situations during Y subway station’s operation, the internal coupling correlations among environment-related SIFs, the coupling correlations between pipe-related SIFs and environment-related SIFs, and the coupling correlations among human-related SIFs, pipe-related SIFs, and environment-related SIFs are all greater than 1, and the coordination degree is 0.778, 0.781, and 0.783, respectively, which is a high security risk; (d) the overall coupling degree among all SIFs during Y subway station’s operation is 0.995 and the coordination degree is 0.809, which is a low safety risk. The research can enrich knowledge in the safety evaluation area, and provide a reference for onsite safety management. The results are basically consistent with the conclusion of the enterprise report, which verifies the scientificity and validity of the evaluation method. Full article

When water pipelines undergo scenarios such as valve closure or leakage, they often operate in a gas-liquid two-phase flow state, which can easily cause abnormal pressure fluctuations, exacerbating the destructiveness of water hammer and affecting the safe operation of the pipeline. To study the problem of abnormal fluctuations in complex water pipelines, this paper establishes a transient flow model for gas-containing pipelines, considering unsteady friction, and solves it using the discrete gas cavity model (DGCM). It also studies the influence of factors such as valve closing time, initial flow rate, gas content rate, leakage location, and leakage amount on the end-of-valve pressure. Furthermore, it locates the leakage position using a genetic algorithm-backpropagation neural network (GA-BP neural network). The results show that increasing the valve closing time, increasing the gas content rate, decreasing the initial flow rate, and increasing the leakage amount all reduce the pressure peak inside the pipeline. The model constructed using the GA-BP neural network effectively predicts the leakage location with a mean absolute percentage error (MAPE) of 9.26%. The research results provide a reference for studies related to the safety protection of water conveyance projects. Full article

Underwater methane (CH₄) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH₄ detection mission, it is necessary to study the effect of hydrogen sulfide (H₂S) in leaking CH₄ gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH₄ sensor arrays. In the process of detecting CH₄, the accuracy decreases when H₂S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n log_n) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98). Full article

The erosion of surface pipelines induced by proppant flowback during shale gas production is significant. The surface pipelines in a shale gas field in the Sichuan Basin experienced perforation failures after only five months of service. To investigate the erosion features of L360N, coatings, and ceramics and optimize the selection of two protective materials, a gas–solid two-phase flow jet erosion experimental device was used to explore the erosion resistance of L360N, coatings, and ceramics under different impact velocities (15 m/s, 20 m/s, and 30 m/s). An energy dispersive spectroscope, a scanning electron microscope, and a laser confocal microscope were employed to analyze erosion morphologies. With the increase in flow velocity, the erosion depth and erosion rate of L360N, coating, and ceramic increased and peaked under an impact velocity of 30 m/s. The maximum erosion rate and maximum erosion depth of L360N were, respectively, 0.0350 mg/g and 37.5365 µm. Its primary material removal mechanism was the plowing of solid particles, and microcracks were distributed on the material surface under high flow velocities. The maximum erosion rate and maximum erosion depth of the coating were, respectively, 0.0217 mg/g and 18.9964 µm. The detachment of matrix caused by plowing is the main material removal mechanism. The maximum erosion rate and maximum erosion depth of ceramics were, respectively, 0.0108 mg/g and 12.4856 µm. The erosion mechanisms were micro-cutting and plowing. Under different particle impact velocities, different erosion morphologies were observed, but the primary erosion mechanism was the same. The erosion resistance of the ceramics was higher than that of the coatings. Therefore, ceramic lining materials could be used to protect the easily eroded parts, such as pipeline bends and tees, and reduce the failure rate by more than 93%. The study provided the data and theoretical basis for the theoretical study on oil and gas pipeline erosion and pipeline material selection. Full article

To comprehensively understand the explosion risk in underground energy transportation tunnels, this study employed computational fluid dynamics technology and finite element simulation to numerically analyze the potential impact of an accidental explosion for a specific oil and gas pipeline in China and the potential damage risk to nearby buildings. Furthermore, the study investigated the effects of tunnel inner diameter (d = 4.25 m, 6.5 m), tunnel length (L = 4 km, 8 km, 16 km), and soil depth (primarily L_soil = 20 m, 30 m, 40 m) on explosion dynamics and on structural response characteristics. The findings indicated that as the tunnel length and inner diameter increased, the maximum explosion overpressure gradually rose and the peak arrival time was delayed, especially when d = 4.25 m; with the increase in L, the maximum explosion overpressure rapidly increased from 1.03 MPa to 2.12 MPa. However, when d = 6.5 m, the maximum explosion overpressure increased significantly by 72.8% from 1.25 MPa. Evidently, compared to the change in tunnel inner diameter, tunnel length has a more significant effect on the increase in explosion risk. According to the principle of maximum explosion risk, based on the peak explosion overpressure of 2.16 MPa under various conditions and the TNT equivalent calculation formula, the TNT explosion equivalent of a single section of the tunnel was determined to be 1.52 kg. This theoretical result is further supported by the AUTODYN 15.0 software simulation result of 2.39 MPa (error < 10%). As the soil depth increased, the distance between the building and the explosion source also increased. Consequently, the vibration peak acceleration and velocity gradually decreased, and the peak arrival time was delayed. In comparison to a soil depth of 10 m, the vibration acceleration at soil depths of 20 m and 30 m decreased by 81.3% and 91.7%, respectively. When the soil depth was 10 m, the building was at critical risk of vibration damage. Full article

In this study, a one-dimensional mathematical model based on rigid theory is developed to evaluate the maximum water filling flow rate and filling time of closed pipeline water supply systems during rapid-filling processes. Polynomial fitting is utilized for prediction, and numerical simulation results are analyzed to understand the variations in maximum water filling flow rate, filling time, and pressure with respect to opening valve time, air valve area, filling head, and segmented filling pipe length. The findings highlight the significant impact of the filling head on the maximum water filling flow rate, while the filling time is predominantly influenced by the gas discharge coefficient. Rapid changes occur only at the initial stage of rapid filling, reaching the maximum value with a very high acceleration (around t = 4 s). It is observed that pressure fluctuations in the gas–liquid two-phase flow inside the pipeline lead to velocity differences and periodic changes in gas pressure opposite to the filling head. When the gas discharge coefficient reaches approximately 0.3, pressure variation within the water supply system diminishes, and the time and flow rate required for pipeline filling become independent of the discharge coefficient. This study suggests the use of a segmented filling approach to ensure the effectiveness and stability of pipeline filling. Full article

Energy is crucial to the development of human civilization. Energy infrastructure, such as oil and gas pipelines, power generation systems, and storage facilities, provide core support for the exploitation and utilization of various types of energy. Thus, energy infrastructure is vital to the economic sustainable development of a country. This paper provides the motivations and a brief introduction to the Special Issue entitled “Frontiers in Construction Technology of Advanced Energy Infrastructure”, which aims to present advanced technologies and theories for energy infrastructure. The primary challenges in the current construction technology of energy infrastructure are described. Furthermore, the focus of current research in this field addressed in this Special Issue is presented. A comparison of the articles included or considered for inclusion in this Special Issue with other available literature on this topic is performed, which proves the prospects and relevance of this Special Issue. Finally, perspectives on future directions of energy utilization and energy infrastructure construction are provided. Full article

This study explores a novel approach utilizing acoustic emission (AE) signaling technology for pipeline leakage detection and analysis. Pipeline leaks are a significant concern in the liquids and gases industries, prompting the development of innovative detection methods. Unlike conventional methods, which often require contact and visual inspection with the pipeline surface, the proposed time-series-based deep learning approach offers real-time detection with higher safety and efficiency. In this study, we propose an automatic detection system of pipeline leakage for efficient transportation of liquid (water) and gas across the city, considering the smart city approach. We propose an AE-based framework combined with time-series deep learning algorithms to detect pipeline leaks through time-series features. The time-series AE signal detection module is designed to capture subtle changes in the AE signal state caused by leaks. Sequential deep learning models, including long short-term memory (LSTM), bi-directional LSTM (Bi-LSTM), and gated recurrent units (GRUs), are used to classify the AE response into normal and leakage detection from minor seepage, moderate leakage, and major ruptures in the pipeline. Three AE sensors are installed at different configurations on a pipeline, and data are acquired at 1 MHz sample/sec, which is decimated to 4K sample/second for efficiently utilizing the memory constraints of a remote system. The performance of these models is evaluated using metrics, namely accuracy, precision, recall, F1 score, and convergence, demonstrating classification accuracies of up to 99.78%. An accuracy comparison shows that BiLSTM performed better mostly with all hyperparameter settings. This research contributes to the advancement of pipeline leakage detection technology, offering improved accuracy and reliability in identifying and addressing pipeline integrity issues. Full article

Research on the deformation characteristics and failure modes of buried pipelines under local suspension conditions caused by groundwater loss in coal mining subsidence areas is conducive to grasping the failure evolution law of pipelines and providing technical support for the precise maintenance of gathering and transportation projects and the coordinated mining of gas and coal resources. First, a test system for monitoring the deformation of pipelines under loading was designed, which mainly includes pipeline load application devices, end fixing and stress monitoring devices, pipeline end brackets, and stress–strain monitoring devices. Then, a typical geological hazard faced by oil and gas pipelines in the gas–coal overlap area—local suspension—was used as the engineering background to simulate the field conditions of a 48 mm diameter gas pipeline with a localized uniform load. At the same time, deformation, top–bottom strain, end forces, and damage patterns of the pipeline were monitored and analyzed. The results show that the strain at the top and bottom of the pipeline increased as the load increased. In this case, the top was under pressure, and the bottom was under tension, and the conditions at the top and bottom were opposite.. For the same load, the strain tended to increase gradually from the end to the middle of the pipeline, and at the top, it increased significantly more than at the bottom. The tensile force carried by the end of the pipeline increased as the applied load increased, and the two were positively correlated by a quadratic function. The overall deformation of the pipeline evolved from a flat-bottom shape to a funnel and then to a triangular shape as the uniform load increased. In addition, plastic damage occurred when the pipeline deformed into a triangular shape. The results of the investigation clarify for the first time the mathematical relationship between local loads and ultimate forces on pipelines and analyze the evolution of pipeline failure, providing a reference for pipeline field maintenance. Based on this, the maximum deformation of and the most vulnerable position in natural gas pipelines passing through a mining subsidence area can be preliminarily judged, and then the corresponding remedial and protection measures can be taken, which has a certain guiding role for the protection of natural gas pipelines. Full article

A pipeline network is the most efficient and rapid way to transmit natural gas from source to destination. The smooth operation of natural gas pipeline control stations depends on electrical equipment such as data loggers, control systems, surveillance, and communication devices. Besides having a reliable and consistent power source, such control stations must also have cost-effective and intelligent monitoring and control systems. Distributed processes are monitored and controlled using supervisory control and data acquisition (SCADA) technology. This paper presents an Internet of Things (IoT)-based, open-source SCADA architecture designed to monitor a Hybrid Power System (HPS) at a remote natural gas pipeline control station, addressing the limitations of existing proprietary and non-configurable SCADA architectures. The proposed system comprises voltage and current sensors acting as Field Instrumentation Devices for required data collection, an ESP32-WROOM-32E microcontroller that functions as the Remote Terminal Unit (RTU) for processing sensor data, a Blynk IoT-based cloud server functioning as the Master Terminal Unit (MTU) for historical data storage and human–machine interactions (HMI), and a GSM SIM800L module and a local WiFi router for data communication between the RTU and MTU. Considering the remote locations of such control stations and the potential lack of 3G, 4G, or Wi-Fi networks, two configurations that use the GSM SIM800L and a local Wi-Fi router are proposed for hardware integration. The proposed system exhibited a low power consumption of 3.9 W and incurred an overall cost of 40.1 CAD, making it an extremely cost-effective solution for remote natural gas pipeline control stations. Full article

The speed control of a pipeline inspection gauge (PIG) directly affects the quality of the comprehensive inspection of submarine pipelines. However, the mechanism of the gas flow behavior in a pipeline under the influence of a pig speed control valve is not well understood. In this study, the driving differential pressure of a pig was modeled based on the building block method and numerical simulations. For the first time, the influence of the pressure and flow rate of the gas in a pipeline on the torque of the speed control valve opening process was studied. The results show that when the opening angle of the speed control valve increased from 4.5° to 22°, the gas differential pressure reduced from 1325 to 73 kPa, realizing a 94.5% pressure reduction. In addition, the torque of the bypass valve increased from 7.7 to 2470 Nm during the closing process. The pressure and flow rate increases were directly correlated with increased torque. The established experimental system for torque measurement confirmed the numerical analysis results. By clarifying the law of torque variation, this study provides theoretical guidance for the structural design and control scheme of a pig speed control unit. Full article

Accurately determining if the sample parameters from a natural gas pipeline’s sampling system reflect the fluid characteristics of the main pipe has been a significant industry concern for many years. In this paper, samples of natural gas in a horizontal pipeline are investigated. CFD is used in this work and the turbulence is considered in the simulation. Firstly, the critical diameter for particles affected by gravity within such pipeline is determined. And then, the effects of the operation pressure and velocity of sampling branches on sample parameters, and the influence of particle density on these sample parameters, are analyzed. Finally, four different structures of sample branches for natural gas in a horizontal pipeline are compared. It is found that 100 μm is the critical diameter at which particles are affected by gravity; the operating pressure of the sampling branch has a significant impact on the particle mass concentration. The particle density has little impact on the sampling system. Overall, the design of the sampling branches does not cause significant sampling errors. This study provides guidance for optimal sampling in existing natural gas pipelines and enables effective monitoring of particle impurity content and properties in natural gas. Full article