Search Results (98)

Urban water distribution networks (WDNs) are increasingly vulnerable to diverse disruptions, including pipe leaks/bursts and cyber–physical failures. A critical step in a resilience-based approach against these disruptions is the rapid and reliable identification of failures and their types for the timely implementation of emergency or recovery actions. This study proposes a framework for sensor placement and multiple failure type classification in WDNs. It applies a wrapper-based feature selection (recursive feature elimination) with Random Forest (RF–RFE) to find the best sensor locations and employs an Autoencoder–Random Forest (AE–RF) framework for failure type identification. The framework was tested on the C-town WDN using the failure type scenarios of pipe leakage, cyberattacks, and physical attacks, which were generated using EPANET-CPA and WNTR models. The results showed a higher performance of the framework for single failure events, with accuracy of 0.99 for leakage, 0.98 for cyberattacks, and 0.95 for physical attacks, while the performance for multiple failure classification was lower, but still acceptable, with a performance accuracy of 0.90. The reduced performance was attributed to the model’s difficulty in distinguishing failure types when they produced hydraulically similar consequences. The proposed framework combining sensor placement and multiple failure identification will contribute to advance the existing data-driven approaches and to strengthen urban WDN resilience to conventional and cyber–physical disruptions. Full article

Functionally graded materials (FGMs) have the potential to revolutionize the oil and gas transportation sector, due to their increased strengths and efficiencies as pipelines. Conventional pipelines frequently face serious problems such as extreme weather, pressure changes, corrosion, and stress-induced pipe bursts. By analyzing the mechanical and thermal performance of FGM-based pipes under various operating conditions, this study investigates the possibility of using them as a more reliable substitute. In the current study, the post-buckling and nonlinear vibration behaviors of pipes composed of FGMs transporting heavy crude oil were examined using a Timoshenko beam framework. The material properties of the FGM pipe were observed to change gradually across the thickness, following a power-law distribution, and were influenced by temperature variations. In this regard, two types of FGM pipes are considered: one with a metal-rich inner surface and ceramic-rich outer surface, and the other with a reverse configuration featuring metal on the outside and ceramic on the inside. The nonlinear governing equations (NGEs) describing the system’s nonlinear dynamic response were formulated by considering nonlinear strain terms through the von Kármán assumptions and employing Hamilton’s principle. These equations were then discretized using Galerkin’s method to facilitate the analytical investigation. The Runge–Kutta method was employed to address the nonlinear vibration problem. It is concluded that, compared with pipelines made from conventional materials, those constructed with FGMs exhibit enhanced thermal resistance and improved mechanical strength. Full article

Urban subsurface pipeline bursts can induce catastrophic cascading effects, including ground collapse, infrastructure failure, and socioeconomic losses. However, stratum responses during the erosion cavity expansion phase and corresponding disaster mitigation strategies have rarely been researched. In this study, a numerical model validated through experimental tests was employed to investigate the effects of internal water pressures, burial depths, and different geotextile-based disaster mitigation strategies. It was revealed that a burial depth-dependent critical internal water pressure governed the erosion cavity expansion, and a predictive equation was derived based on the limit equilibrium theory. Higher internal water pressure accelerated the erosion cavity expansion and amplified the stratum stress within a range of twice the diameter D. Increased burial depth $d$ reduced peak ground heave but linearly expanded the heave zone range, concurrently elevating the overall stratum stress level and generating larger stress reduction zones (i.e., when $d/D$ = 3.0, the range of the stress reduction zone was 8.0D). All geotextile layout configurations exhibited different disaster mitigation effects (the peak ground heave was reduced by at least 15%). The semi-circular closely fitted configuration (SCCF) optimally restricted the expansion of the erosion cavity, reduced the stratum displacement (i.e., 39% reduction in the peak ground heave), and avoided stress concentration. Comprehensive analysis indicated that SCCF was suited for low-pressure pipelines in deformation-sensitive stratum and semi-circular configuration (SC) was suitable for deformation-insensitive pipeline sections. These findings provide actionable insights for tailoring mitigation strategies to specific operational risks. Full article

Leakages in water distribution networks pose a formidable challenge, often leading to substantial water wastage and escalating operational costs. Traditional methods for leak detection often fall short, particularly when dealing with complex or subtle data patterns. To address this, a comprehensive comparison of fourteen machine learning algorithms was conducted, with evaluation based on key performance metrics such as multi-class classification metrics, micro and macro averages, accuracy, precision, recall, and F1-score. The data, collected from an experimental site under leak, major leak, and no-leak scenarios, was used to perform multi-class classification. The results highlight the superiority of models such as Random Forest, K-Nearest Neighbours, and Decision Tree in detecting leaks with high accuracy and robustness. Multiple models effectively captured the nuances in the data and accurately predicted the presence of a leak, burst, or no leak, thus automating leak detection and contributing to water conservation efforts. This research demonstrates the practical benefits of applying machine learning models in water distribution systems, offering scalable solutions for real-time leak detection. Furthermore, it emphasises the role of machine learning in modernising infrastructure management, reducing water losses, and promoting the sustainability of water resources, while laying the groundwork for future advancements in predictive maintenance and resilience of water infrastructure. Full article

Enhancing the seismic resilience of urban water distribution networks (WDNs) requires the improvement of both earthquake resistance and rapid recovery capabilities within the system. This paper proposes a multi-objective method to enhance the seismic resilience of the WDNs, focusing on system restoration capabilities while comprehensively considering the hydraulic recovery index, maintenance time, and maintenance cost. The method utilizes a random simulation approach to generate various damage scenarios for the WDN, considering pipe leakage, pipe bursts, and variations in node flow resulting from changes in water pressure. It characterizes the functions of the WDN through hydraulic service satisfaction and quantifies system resilience using a performance response function. Additionally, it determines the optimal dispatch strategy for emergency repair teams and the optimal emergency repair sequence for earthquake-damaged networks using a genetic algorithm. Furthermore, a comprehensive computational platform has been developed to systematically analyze and optimize seismic resilience strategies for WDNs. The feasibility of the proposed method is demonstrated through an example involving the WDN in Xi’an City. The results indicate that the single-objective seismic resilience improvement method based on the hydraulic recovery index is the most effective for enhancing the seismic resilience of the WDN. In contrast, the multi-objective method proposed in this article reduces repair time by 17.9% and repair costs by 3.4%, while only resulting in a 0.2% decrease in the seismic resilience of the WDN. This method demonstrates the most favorable comprehensive restoration effect, and the success of our method in achieving a symmetrically balanced restoration outcome demonstrates its value. The proposed methodology and software can provide both theoretical frameworks and technical support for urban WDN administrators. Full article

Urban water distribution systems face growing challenges from energy inefficiencies caused by hydraulic anomalies, such as pipe aging, bursts, demand variability, and suboptimal pump and valve operations. This review systematically evaluates current technologies for energy-efficient management of WDNs under such conditions, structured around both basic and applied technologies. Basic technologies include real-time monitoring, data acquisition, and hydraulic modeling with CFD simulation. Applied technologies focus on demand forecasting, pressure management for energy optimization, and leakage anomaly detection. Case studies demonstrate the practical value of these approaches. Despite recent advances, challenges persist in data interoperability, real-time optimization complexity, scalability, and forecasting uncertainty. Future research should emphasize adaptive AI algorithms, integration of digital twin platforms with control systems, hybrid optimization frameworks, and renewable energy recovery technologies. This review provides a comprehensive foundation for the development of intelligent, energy-efficient, and resilient urban water distribution systems through integrated, data-driven management strategies. Full article

In order to improve the accuracy of pipe burst detection in water distribution networks (WDNs), a novel small sample diagnosis method (SSDM) based on the head loss ratio (HLR) method and deep transfer learning (DTL) method has been proposed. In this paper, the burst state was quickly detected through the limited data analysis of pressure monitoring points. The HLR method was introduced to enhance data features. DTL was introduced to improve the accuracy of small sample burst detection. The simulated data and real data were enhanced by HLR. Then, the model was trained and obtained through the DTL. The performance of the model was evaluated in both simulated and real scenarios. The results indicate that the leaked features can be improved by 350% by the HLR. The accuracy of SSDM reaches 99.56%. The SSDM has been successfully applied to the detection of real WDNs. The proposed method provides potential application value for detecting pipe bursts. Full article

Traditional centralized water systems are facing sustainability challenges due to climate and socioeconomic changes, extreme weather events, and aging infrastructure and their uncertainties. The energy sector has addressed similar challenges using the microgrid approach, which involves decentralized energy sources and their supply, improving system resilience and sustainable energy supply. This study investigated the resilience effects of water microgrids, which feature operational interactions between centralized and local systems for sustainable water supply. A lab-scale water distribution model was tested to demonstrate centralized, decentralized, and microgrid water systems under the disruption scenarios of pump shutdown, pump rate manipulation, and pipe leaks/bursts. The water microgrids integrate centralized and local systems’ operations, while the decentralized system operates independently. Then, functionality-based resilience and its attributes were evaluated for each disruption scenario. The results reveal that, overall, the microgrid configuration, with increased water supply redundancy and flexible operational adjustment based on system conditions, showed higher resilience, robustness, and recovery rate and a lower loss rate across disruption scenarios. The resilience effect of water microgrids was more evident with longer and more severe disruptions. Considering global challenges in water security under climate and socioeconomic changes, the findings suggest insights into a hybrid water system as a strategy to enhance resilience and water use efficiency and provide adaptive operations for sustainable water supply. Full article

Burst pressure is one of the critical strength parameters used in the design and operation of pressure vessels because it represents the maximum pressure that a vessel can withstand before failing. Historically, the Barlow formula was used as a design base for estimating burst pressure. However, it does not consider the plastic flow response for ductile steels and is applicable only to thin-walled cylinders (i.e., the diameter to thickness ratio D/t ≥ 20). A new multiaxial plastic yield theory was developed to consider the plastic flow response, and the associated theoretical (i.e., Zhu–Leis) solution of burst pressure was obtained and has gained extensive applications in the pipeline industry because it was validated by different full-scale burst test datasets for large-diameter, thin-walled pipelines in a variety of steel grades from Grade B to X120. The Zhu–Leis flow theory of plasticity was recently extended to thick-walled pressure vessels, and the associated exact flow solution of burst pressure was obtained and is applicable to both thin and thick-walled cylindrical shells. Many full-scale burst tests are available for thin-walled line pipes in the pipeline industry, but limited pressure burst tests exist for thick-walled vessels. To validate the newly developed exact solutions of burst pressure for thick-walled cylinders, this paper conducts a series of burst pressure tests on small-diameter, thick-walled pipes. In particular, six burst tests are carried out for three thick-walled pipes in Grade B carbon steel. These pipes have a nominal diameter of 2.375 inches (60.33 mm) and three nominal wall thicknesses of 0.154, 0.218, and 0.344 inches (3.91, 5.54, and 8.74 mm), leading to D/t = 15.4, 10.9, and 6.9, respectively. With the burst test data, comparisons show that the Zhu–Leis flow solution of burst pressure matches well the burst test data for thick-walled pipes. Thus, these burst tests validate the accuracy of the Zhu–Leis flow solution of burst pressure for thick-walled cylindrical vessels. Full article

High-frequency induction welding technology represents the development direction of the high-temperature corrosion protection technology for the heating surfaces of the boiler “four tubes”. However, when the high-frequency induction coil heats and remelts the coating on the tube’s outer wall, the tube’s inner wall is also heated, causing an iron oxide scale to form on the tube’s inner wall. When the remelting temperature rises and the temperature of the tube’s inner wall exceeds 580 °C, three layers of oxide films, FeO, Fe₃O₄, and Fe₂O₃ are arranged in sequence from the substrate surface of the tube’s inner wall to the outside, with a thickness ratio of approximately 1:10:100. From the XRD spectra of tube iron oxide scale, it can be seen that the oxidation of the tube. The skin is mainly composed of Fe₃O₄, with a certain amount of Fe₂O₃ and trace amounts of FeO. The iron in the diffraction peak originates from the metal matrix. However, when the remelting temperature continues to rise and the temperature of the tube’s inner wall exceeds 580 °C, the oxide film begins to thicken significantly, that is, the oxide film begins to transform into an oxide scale. Under the continuous action of high-temperature induction remelting, the reaction between iron and oxygen is accelerated, but because the oxygen ions of water slowly diffuse through two outer layers of oxide films, with a low oxygen concentration. Although the FeO film is thin, it has a loose structure and numerous lattice defects, is unstable and easy to decompose, and easily peels off from the tube’s inner wall. For a pipe wall thickness of 5 mm, if the thinning rate of the inner wall caused by detachment reaches 0.8 mm/year, it is highly likely to cause pipe burst accidents within 4–5 years. The influence of the iron oxide scale on the performance of the tube’s inner wall was evaluated by testing indexes, such as surface hardness and decarburization layer depth. Although the oxide scale reduces the surface hardness of the tube’s inner wall, the surface decarburization layer is very thin, so the effect on the mechanical properties of the tube’s substrate is limited. The technology of inhibiting the formation of the iron oxide scale in induction remelting is briefly introduced. During the high-frequency remelting process of water-cooled walls, as the tube bank moves forward relative to the high-frequency heating coil, nitrogen protection is used to suppress the formation of oxide scale, effectively eliminating the troubles caused by high-frequency induction remelting and achieving the goal of improving the service life of the tube bank. This technology of the nitrogen protection method is used to inhibit the formation of iron oxide scale, not only inhibiting the formation of the iron oxide scale on the tube inner wall and the back of the tube bundle, with remarkable experimental results and broad application prospects. Full article

Heated pipe flow is widely used in thermal engineering applications, but the presence of buoyancy force can cause intermittency, or multiple flow states at the same parameter values. Such changes in the flow lead to substantial changes in its heat transfer properties and thereby significant changes in the axial temperature gradient. We therefore introduce a model that features a time-dependent background axial temperature gradient, and consider two temperature boundary conditions—fixed temperature difference and fixed boundary heat flux. Direct numerical simulations (DNSs) are based on the pseudo-spectral framework, and good agreement is achieved between present numerical results and experimental results. The code extends Openpipeflow and is available at the website. The effect of the axially periodic domain on flow dynamics and heat transfer is examined, using pipes of length $L=5D$ and $L=25D$. Provided that the flow is fully turbulent, results show close agreement for the mean flow and temperature profiles, and only slight differences in root-mean-square fluctuations. When the flow shows spatial intermittency, heat transfer tends to be overestimated using a short pipe, as shear turbulence fills the domain. This is particularly important when shear turbulence starts to be suppressed at intermediate buoyancy numbers. Finally, at such intermediate buoyancy numbers, we confirm that the decay of localised shear turbulence in the heated pipe flow follows a memoryless process, similar to that in isothermal flow. While isothermal flow then laminarises, convective turbulence in the heated flow can intermittently trigger bursts of shear-like turbulence. Full article

With the rapid advancement of modern industries, pressure vessels and piping have become increasingly integral to sectors such as energy, petrochemicals, and process industries. To grasp the research and application status in the field of pressure vessel and piping safety, 670 publications in the Web of Science core database from 2008 to 2024 were taken as data samples in this paper. The knowledge mapping tools were used to carry out co-occurrence analysis, keyword burst detection, and co-citation analysis. The results show that the research in this field presents a multidisciplinary and cross-disciplinary state, involving multiple disciplines such as Nuclear Science and Technology, Engineering Mechanics, and Energy and Fuels. The “International Journal of Hydrogen Energy”, “International Journal of Pressure Vessels and Piping”, and “Nuclear Engineering and Design” are the primary publication outlets in this domain. The study identifies three major research hotspots: (1) the safety performance of pressure vessels and piping, (2) structural integrity, failure mechanisms, and stress analysis, and (3) numerical simulation and thermal–hydraulic analysis under various operating conditions. The current challenges can be summarized into three aspects: (1) addressing the safety risks brought by new technologies and materials, (2) promoting innovation and the application of detection and monitoring technologies, and (3) strengthening the building capacity for accident prevention and emergency management. Specific to China, the current challenges include the safety and management of aging equipment, the effective detection of circumferential weld cracks, the refinement of risk assessment models, and the advancement of smart technology applications. These findings offer valuable insights for advancing safety practices and guiding future research in this multidisciplinary field. 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

The microstructure and structure of a Super304H superheater steel pipe after 47,000 h were analyzed by metallographic microscope, scanning electron microscope (SEM), and EDS, and its mechanical properties were measured by hardness meter. The results show that the austenitic grains appear on the outer wall of Super304H steel pipe after service, while the SEM and metallographic microscope tests show that the outer wall particles are coarse. There is an obvious corrosion layer on the outer surface, and the thickness of the corrosion layer on the windward surface is significantly higher than that on the leeward surface. The inner surface is refined and the hardness of the material is significantly increased; the outer surface, the inner surface, and the center all grow abnormally. In this case, the room temperature tensile strength and impact performance of the rough crystal area of the outer wall of the Super304H steel pipe are reduced and fracture along the crystal. Supervision should be strengthened to eliminate the safety risks caused by the abnormal growth of the outer wall austenite grain. The results of crystal phase microscopy show that the main structure of the material still maintains the basic structure of austenitic steel, and particle aggregation mainly occurs in the sub-inner layer of the inner and outer surface. Compared with the lee surface, the middle body structure is basically the same, but whether the thickness of the corrosion layer on the inner surface or the outer surface increases, the deformation degree of the deformation layer is greater. The hardness measurement finds that the hardness of the corrosion layer is caused by the increase in Super304H steel surface stress. In case of pipe explosion accident, the highest chance of pipe explosion here should be closely observed. Full article

Vascular Ehler–Danlos disease (vEDS), a rare subtype of a rare disease, is a life-threatening disease, with an increased risk for spontaneous vascular or visceral rupture. These patients have fatal complications ranging from vascular aneurysms, dissection, and rupture of systemic vessels to frequent thromboembolic events, the common causes of death in these individuals with a shortened life span. In the present case, a 28-year-old male with history of shoulder dislocations and spontaneous colon perforation presented to the primary care clinic with right lower extremity swelling and pain. His history includes presentation to the emergency department with left lower leg swelling with compartment syndrome one year prior. A CT angiogram of lower extremities and abdomen revealed acute arterial extravasation of the left posterior tibial artery, indicating a ruptured aneurysm along with aneurysms of the splenic artery and left common iliac artery. He was treated with a saphenous vein graft, but was associated with post-operative complications that necessitated below-knee amputation. CT angiogram of his right leg revealed occlusion of the anterior tibial and peroneal arteries with aneurysms, and, ultimately, he was referred to a tertiary care center for aneurysm embolization. This case report emphasizes the frequent vascular complications encountered in vascular EDS patients, and thus advocates for close and regular monitoring for early referral and surgical management of their vascular anomalies. Finally, genetic counseling and screening of asymptomatic family members should be routinely implemented in these patients. Full article