Search Results (60)

Profile control is widely employed to improve oil recovery in fractured-vuggy carbonate reservoirs. However, the limitation of current experimental evaluation methods restricts their practical guidance for field applications. In this study, urea-formaldehyde resin gel (URG) is studied using SEM, rheological analysis, FTIR, and Raman spectroscopy. Typical structural models of fractured-vuggy reservoirs are fabricated by 3D printing technology. The distribution patterns of the URG in different fractured-vuggy models are also investigated by using online NMR analysis and core slice characterization. Results show that URG exhibits a kind of 3D mesh structure with a size of 10 μm after gelation at 140 °C. The storage modulus (G′) and loss modulus (G″) of the URG gel are 387.51 Pa and 131.48 Pa, respectively. Chemical composition analysis reveals that URG is mainly composed of amide groups and sulfonate groups, showing excellent thermal stability and salt tolerance. Furthermore, after injecting URG into three types of typical models, URG displays a longitudinally decreasing distribution pattern from the injection side to the outlet side, accompanied by transverse accumulation phenomenon along the fracture walls in the slab fracture model. In the fractured-vuggy model, the gel shows continuous longitudinal distribution and uniform transverse distribution characteristics. In the beaded-vug train model, the gel’s distribution morphology gradually transforms from a “pipeline-filling” pattern at the injection side to a “conduit-dominant” pattern toward the outlet side, with a stepped distribution in the transverse direction. The breakthrough pressures during subsequent water flooding are as follows: beaded-vug train model (11.6 MPa) > fractured-vuggy model (8.1 MPa) > slab fracture model (5.9 MPa). Field application results show that the water cut is reduced from 85% to 30%, with a total incremental oil production of 2416 tons. This study conducts experimental investigations on the distribution patterns of URG in simulated fractured-vuggy models, thereby establishing a novel technical evaluation method for profile control in actual fractured-vuggy carbonate reservoirs. Full article

This study constructed an integrated underwater pipeline monitoring system, which combines pipeline posture sensing modules and pipeline leakage detection modules. The proposed system can achieve the real-time monitoring of pipeline posture and the comprehensive assessment of pipeline damage. By deploying pipeline posture sensing and leakage detection modules in array configurations along an underwater pipeline, information related to pipeline posture and flow variations is continuously collected. An array of inertial sensor nodes that form the pipeline posture sensing system is used for real-time pipeline posture monitoring. The system measures underwater motion signals and obtains bending and buckling postures using posture algorithms. Pipeline leakage is evaluated using flow and water temperature data from Hall sensors deployed at each node, assessing pipeline health while estimating the location and area of pipeline damage based on the flow values along the nodes. The human–machine interface designed in this study for underwater pipelines supports automated monitoring and alert functions, so as to provide early warnings for pipeline postures and the analysis of damage locations before water supply abnormalities occur in the pipelines. Underwater experiments validated that this system can precisely capture real-time postures and damage locations of pipelines using sensing modules. By taking flow changes at these locations into consideration, the damage area with an error margin was estimated. In the experiments, the damage areas were 8.04 cm² to 25.96 cm², the estimated results were close to the actual area trends (R² = 0.9425), and the area error was within 5.16 cm² (with an error percentage ranging from −20% to 26%). The findings of this study contribute to the management efficiency of underwater pipelines, enabling more timely maintenance while effectively reducing the risk of water supply interruption due to pipeline damage. Full article

Research on prestressed concrete cylinder pipes (PCCPs) has focused primarily on their failure mechanisms, monitoring methods, and the effectiveness of repairs. However, gaps in the study of damage risks associated with PCCPs remain. Based on existing relevant research, this study focused on analysing the uncertainties in the material production and manufacturing processes of PCCPs to assess their damage risk. The research employs onsite test data about the compressive strength of C55 concrete and the real prestressing force exerted on prestressed steel wires, utilising the measured compressive strength of the concrete core in PCCPs alongside the actual prestressing force applied to the steel wires. An inverse cloud generator was employed to obtain the expected value Ex, entropy En, and hyperentropy He of the characteristic numbers. These values are then combined with the forward cloud model in cloud theory to train random parameters. By combining cloud theory with the Monte Carlo method, a risk analysis model for PCCP pipelines was established. Using internal water pressure monitoring data from the Qiliqiao Reservoir to the Xiayi Water Supply Line in the South-to-North Water Diversion Project, along with relevant PCCP pipeline data, the failure probability of the PCCP pipeline was calculated. The reliability index of this pipeline section under 0.6 MPa loading was found to be 4.49, demonstrating the reliability of the PCCP pipeline in this section of the water supply line. Full article

Urban water supply pipelines play a critical role in ensuring the continuous delivery of water, and their failure during earthquakes can result in significant societal disruptions. This study proposes a seismic damage prediction method for urban buried water supply pipelines affected by seismic wave propagation, grounded in empirical data from past earthquake events. The method integrates key influencing factors, including pipeline material, diameter, joint type, age, and soil corrosivity. To enhance its practical applicability and address the challenge of quantifying soil corrosivity, a simplified classification approach is introduced. The proposed model is validated using observed pipeline damage data from the 2008 Wenchuan earthquake, with predicted results showing relatively good agreement with actual failure patterns, thereby demonstrating the model’s reliability for seismic risk assessment. Furthermore, the model is applied to assess potential earthquake-induced damage to buried pipelines in the city center of Ganzhou, and the corresponding results are presented. The findings support earthquake risk mitigation and the protection of urban infrastructure, while also providing valuable guidance for the replacement of aging pipelines and the enhancement of urban disaster resilience. Full article

Water distribution is no arguably the most important factor in modern times, and water leak breaks are typically a consequence of failures in water distribution networks. But pipeline leakage breaks have become one of the most frequent consequences affecting the operation of water distribution networks (WDNs) and monitoring their health is often complicated. This paper proposes a leakage break diagnosis method based on an LSTM-FCN neural network model from high-frequency pressure data. Data preprocessing is used to avoid the influence of noise and information redundancy, and the LSTM module and the FCN module are used to extract and concatenate different leakage break features. The leakage break feature is sent to a dense classifier to obtain the predicted result. Two sample sets, steady state and water consumption, were obtained to verify the performance of the proposed leakage break diagnosis method. Three other models, LSTM, FCN, and ANN, were compared using the sample sets. The proposed LSTM-FCN model achieved an overall accuracy of 85% for leakage break detection, illustrating that the model could effectively learn the leakage break features in high-frequency time-series data and had a high accuracy for leakage break detection and leakage break degree prediction of new samples in WDNs. Meanwhile, the proposed method also had good adaptability to the variations in water consumption in actual WDNs. Full article

Urban centralized heating systems, as a crucial component of the energy transition, face new challenges in terms of reliable and balanced operation, energy-saving performance, and optimized control. Based on the accurate quantification of user heat load, an operational optimization method for secondary heating networks is proposed. By accurately analyzing the actual heating demands of different users according to building characteristics and climatic conditions and integrating the hydraulic and thermal modeling of a pipeline network, a Particle Swarm Optimization (PSO) algorithm is employed to optimize the valve opening degrees of users and the secondary side, achieving the optimal operating state of the secondary network that matches user load and obtaining the optimal valve regulation strategy. The results of a case analysis show that, after optimization, the overall variance of return water temperature for heat users decreased by 12.16%, and the electricity consumption of the secondary network circulation pump was reduced by 16.46%, demonstrating the effectiveness and practicality of the proposed optimization method. On the basis of ensuring hydraulic balance in the heating system, the method meets the individual heating demands of users, effectively improves user thermal comfort, and reduces energy consumption, addressing the issues of excessive and uneven heat supply. Full article

Evaluating the performance of sponge city practices under actual conditions is essential for managing urban stormwater. Existing studies in urban stormwater management have rarely employed numerical simulations to model hydrological processes under actual Three-Dimensional (3D) conditions. In this study, a numerical computational model is developed to simulate the hydrological processes and reveal the temporal and spatial variation of runoff in relation to impervious surfaces and concave herbaceous fields. The applicability of the 3D modules was evaluated using the Chicago rain pattern formula under three recurrence periods: precipitation within one, five, and ten years. The results indicate that the thickness and slope of planting soil are the most sensitive factors regarding sponge city performance, with comprehensive factors of 0.754 and 0.461. The optimal structural parameters of the concave herbaceous field were obtained as follows: aquifer height, 200 mm; planting soil thickness, 600 mm; planting soil slope, 1.5%; planting soil porosity, 0.45; overflow pipeline porosity, 0.3. The flood peak reduction rate, delay rate, and total runoff control rate were the best in a recurrence period of 5a, with 88.93%, 51.11%, and 78.76%, respectively. This study offers technical and conformed methodological support for simulating water quantity processes in sponge cities, and for the control of waterlogging and the recycling of runoff. Full article

Accurate water hammer mitigation simulation is crucial for designing and protecting pipeline systems. This study draws on the principles of the Muskingum method to develop an improved discrete vaporous cavity model (DVCM) that enhances computational accuracy. The key improvements include significantly reducing numerical dissipation by optimizing the Courant number (C_n) and adjusting the friction coefficient (f) to balance numerical and physical dissipation. Specifically, the predictive accuracy of the node water head was improved by 69.93%, and the accuracy of the liquid–column separation time was enhanced by 77.21%. These enhancements were achieved by proposing an equivalent treatment method for numerical and physical dissipation, ensuring that the model’s total dissipation matches actual physical conditions. The validation process involved simulating the liquid column separation process using data from the Simpson experiment. The results demonstrated a high degree of consistency with the experimental data, confirming the effectiveness of the proposed method. Full article

An ultrafiltration (UF) installation was used to separate the actual wastewater from a car wash. Following these studies, the plant was washed several times; however, severe membrane fouling was observed during the filtration of sterile deionised (DI) water. As a result, the permeate flux decreased by more than 50% after 5 h of the UF process. The source of the fouling was the release of deposits, particularly bacteria, from the surfaces of plant elements such as pipes and pumps. The paper presents the effectiveness of biofilm removal from the surface of the equipment during a cyclically repeated washing process. Chemical washing was carried out using acid solutions and alkaline cleaning solutions containing NaOH (pH = 11.5–12). After installation cleaning, the filtration tests were carried out using DI water as a feed. It was determined how biofouling, which develops under these conditions, reduces permeate flux. Despite 3 h of installation washing, there was a 50% reduction in flux after 10 h of UF. Repeating the installation wash (4 h) resulted in a similar decrease in flux after 4 days of UF. Stabilisation of the flux at a level of 500 LMH was achieved after an additional 5 h of washing, including application of hot (323–333 K) alkaline cleaning solutions. The number of bacteria in the biofilm collected from the surface of the membranes, the pump inlet and the surface of the polyvinyl chloride (PVC) hoses forming the pipeline was also investigated. Despite repeated chemical cleaning, the number of bacteria on the pump and hose surfaces was 50–100 CFU/cm². Studies were carried out to determine which bacterial species survived the chemical cleaning of the installation. Gram-positive and Gram-negative bacteria were determined, and taxonomic characteristics of the isolated bacteria were identified. Full article

Current design techniques for water installations are based on pressure-independent consumption. However, certain types of consumption depend on pressure, most notably water leakages, which occur in all water distribution systems. All water installations are prone to water leakages. To mitigate this issue during the design stage of water pipelines, manuals and local regulations recommend a percentage of water losses for sizing pipelines and using them with pressure-independent consumption. This research develops a practical procedure for sizing single water pipelines by considering the effect of pressure-dependent consumption, as in actual pipelines. The findings of this research offer water utilities a new perspective on pipeline design, which is essential for developing new tools to create digital twins. A new methodology for designing pipe diameters is developed in this research. A single pipeline, 2000 m long, is used for the analysis with an emitter coefficient of 0.00829 m³/s/m^0.5. The proposed methodology focuses on calculating energy losses to maintain the required minimum pressure in the system. A sensitivity analysis is conducted on key parameters such as the emitter coefficient, absolute roughness, and the resistance coefficient of a regulating valve. The results of the proposed methodology are compared with the current design (using pressure-independent consumption), revealing differences of up to 28% in calculating water losses. Full article

The underground pipeline is a critical component of urban water supply and drainage infrastructure. However, the absence of accurate pipe information frequently leads to construction delays and cost overruns, adversely impacting urban management and economic development. To address these challenges, the digital management of underground pipelines has become essential. Despite its importance, research on the structural analysis and reconstruction of underground pipelines remains limited, primarily due to the complexity of underground environments and the technical constraints of LiDAR technology. This study proposes a framework for reconstructing underground pipelines based on unstructured point cloud data, aiming to accurately identify and reconstruct pipe structures from complex scenes. The Random Sample Consensus (RANSAC) algorithm, enhanced with parameter-adaptive adjustments and subset-independent fitting strategies, is employed to fit centerline segments from the set of center points. These segments were used to reconstruct topological connections, and a Building Information Model (BIM) of the underground pipeline was generated based on the structural analysis. Experiments on actual underground scenes evaluated the method using recall rate, radius error, and deviation between point clouds and models. Results showed an 88.8% recall rate, an average relative radius error below 3%, and a deviation of 3.79 cm, demonstrating the framework’s accuracy. This research provides crucial support for pipeline management and planning in smart city development. Full article

This paper investigates air–water interactions during a controlled filling process of an actual water pipeline using a two-dimensional Computational Fluid Dynamics (CFD) model. The main objectives are to understand the dynamic interaction of these fluids through water inflow patterns, pressure pulses, and air-pocket dynamics based on contours. This study uses an existing cast iron pipeline 485 m in length, a nominal diameter of 400 mm, and an air valve with a nominal diameter of 50 mm. The methodology of this CFD model includes the Partial Volume of Fluid (pVoF) method for air–water interface tracking, a turbulence model, mesh sensitivity and numerical validation with pressure and velocity measurements. Results highlight the gradual pressurization of pipelines and air pocket behavior at critical points and show the thermodynamic interaction concerning heat transfer between gas and liquid. This study advances the application of CFD in actual water pipelines, offering a novel approach to air pocket management. Full article

With the increasing demand for oil and gas, the depth of some vertical gas wells can reach 6000 m. At this time, the downhole fluid is in a state of high temperature and pressure, and interpretation of the production logging output profile faces the problem of inaccurate production calculations and difficulty judging the water-producing layer. The drift-flux model is usually used to calculate the gas–water two-phase flow. The drift-flux model is widely used to describe the two-phase flow in pipelines and wells because of its accuracy and simplicity. The constitutive correlations used in drift-flux models, which specify the relative motion between phases, have been extensively studied. However, most of the correlations are only extended by laboratory data of small pipe diameters at standard temperature and pressure and do not apply to high-temperature and high-pressure large-diameter gas wells. Therefore, we improved the distribution coefficient and drift velocity of drift-flux correlations in this study for high-temperature and high-pressure gas wells with large pipe diameters. Therefore, this study improved the distribution coefficient and drift velocity of the drift-flux correlations for high-temperature and high-pressure gas wells with large pipe diameters. In practical application, the coincidence rates of gas production and water production calculated by the new drift-flux model were 12.68% and 19.39%, respectively. For high-temperature and high-pressure deep wells, the measurement errors of production logging instruments are significant, and surface laboratory pipelines are challenging to configure and equip with actual high-temperature and high-pressure conditions. Therefore, this study used the method of numerical simulation to study the flow characteristics of the two phases of high-temperature and high-pressure gas and water to provide a basis for identifying the water layer. Combined with the proposed drift-flux correlations and the new method of determining the water-producing layer, a new method of production profile interpretation of high-temperature and high-pressure gas wells is obtained. Full article

In this study, an innovative leak detection model based on Convolutional Graph Neural Networks (CGNNs) is proposed to enhance response speed during pipeline bursts and to improve detection accuracy. By integrating node features into pipe segment features, the model effectively combines CGNN with water distribution networks, achieving leak detection at the pipe segment level. Optimizing the receptive field and convolutional layers ensures high detection performance even with sparse monitoring device density. Applied to two representative water distribution networks in City H, China, the model was trained on synthetic leak data generated by EPANET simulations and validated using real-world leak events. The experimental results show that the model achieves 90.28% accuracy in high-density monitoring areas, and over 85% accuracy within three pipe segments of actual leaks in low-density areas (10%–20%). The impact of feature engineering on model performance is also analyzed and strategies are suggested for optimizing monitoring point placement, further improving detection efficiency. This research provides valuable technical support for the intelligent management of water distribution networks under resource-limited conditions. Full article

Analyzing the mechanisms of soil instability in tunnels due to sudden water ingress is essential for construction safety. This kind of problem belongs to the category of seepage deformation, mostly due to the near tunnel range of water pipeline blowing cracks and heavy rainfall flooding rainwater into the tunnel. Distinguished from general infiltration behavior, the relevant problems have the characteristics of rapid occurrence and short action time. This study develops a 3D fluid–solid coupling model for soil deformation in tunnels with water ingress, grounded in Biot’s theory and Darcy’s law while considering water level variations within the tunnel. The governing equations are discretized in space and time, and the model’s accuracy is validated through comparison with actual measurements from a Zhengzhou subway project. The study analyzes pore pressure, stress-deformation responses, and surface settlement patterns in surrounding soil and rock mass under soil–water coupling. The findings show that (1) the tunnel cavern, as a seepage source, has minimal impact on the lateral settlement trough width, while seepage mainly affects the vertical deformation of surrounding rock; (2) pressure dissipation exhibits hysteresis in clay strata; (3) water ingress increases soil saturation and decreases effective stress, resulting in persistent surface settlement until drainage. There is a minimal discrepancy between model-calculated and measured settlements. Full article