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This study explores techniques for managing class imbalance in predictive modeling to forecast water pipe failures using XGBoost and logistic regression. Given the significant challenges posed by water pipeline failures—such as service disruptions, costly repairs, and environmental hazards—there is a pressing need for effective predictive models. Using a dataset from 2015 to 2022 that includes features like pipe age, material, diameter, and maintenance history, the study applies methods such as random oversampling and undersampling to improve model performance. Results show that XGBoost outperforms logistic regression in recall (0.795 vs. 0.683), a critical metric for managing water infrastructure. Although logistic regression has slightly better precision (0.695), XGBoost demonstrates superior overall performance with higher Matthews correlation coefficient (MCC) and F1 score, effectively balancing precision and recall. This research is essential as it addresses the need for robust predictive models to anticipate and mitigate water pipeline failures. By offering a comprehensive framework for managing large-scale datasets and showcasing how accurate predictions can reduce maintenance costs and water wastage, this study contributes to more efficient and sustainable water infrastructure management. [ABSTRACT FROM AUTHOR]

Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations. [ABSTRACT FROM AUTHOR]

Pipeline networks are crucial components of modern infrastructure, and ensuring their reliable operation is essential for sustainable development. The percussion-based methods are considered promising for detecting pipeline faults due to their avoidance of constant-contact sensors and ease of implementation. However, the majority of existing percussion-based methods suffer from limitations such as the requirement for manual feature extraction, as well as subpar noise resilience and adaptability. This paper introduces a one-dimensional convolutional bidirectional long short-term memory network with wide first-layer kernels for the classification of percussion-induced acoustic signals, thus achieving automatic identification of pipeline leakage and water deposit conditions. This approach directly extracts features from audio signals using wide first-layer convolutional kernels, eliminating the need for manual feature extraction. Additionally, it employs bidirectional long short-term memory to effectively capture long-term signal dependencies from both past and future contexts. To validate the effectiveness of the method, two case studies were conducted on three groups of pipes. The results show that the proposed method demonstrates superior noise resistance and adaptability compared to other methods, and it also exhibits strong applicability to other percussion signal datasets. Additionally, the impact of different first convolutional kernel sizes on the noise resistance and adaptive performance of the model was investigated, which provides robust guidance for the effective processing of percussion-induced acoustic signals. [ABSTRACT FROM AUTHOR]

Steel jacking pipes are potentially prone to buckling instability, a phenomenon that has received limited attention in hard rock formations. This study reports on the field monitoring of a water pipeline project in Zhongshan City, where the circumferential and hoop strains of steel pipe segments jacked in hard rocks were recorded. The buckling deformation observed during steel pipe jacking, as well as the critical buckling load, was analyzed with the aid of numerical simulations using finite element software. The initial defect for the post-buckling analysis of the steel pipe was selected as the first-order buckling mode. Field monitoring revealed that the loading conditions experienced by the steel pipe segments during the jacking process are complex, leading to significant deformation. Throughout the monitoring process, axial stress at each measurement point underwent tensile-compressive transitions. Numerical results showed the actual critical buckling load increases with wall thickness at a constant length-to-diameter ratio, which is significant for short pipes. For pipes with the same wall thickness and outer diameter, the actual critical buckling load of long pipes is significantly lower than that of short pipes. Additionally, initial defects were found to significantly reduce the actual critical buckling load of the steel pipe. Furthermore, the actual critical buckling load of long pipes is much lower than their yield load, whereas, for short pipes, the critical buckling load is limited by their yield load. Measures for managing buckling deformation of steel pipes in situ were also reported. The findings on critical buckling load and the countermeasures for managing buckling in situ would be valuable for the design and construction stages of similar projects employing pipe-jacking technology in hard rock formations. [ABSTRACT FROM AUTHOR]

Air exchange in pressurized water pipelines is an essential but complex aspect of pipeline modeling and operation. Implementing effective air management strategies can yield numerous benefits, enhancing the system's energy efficiency, reliability, and safety. This paper comprehensively evaluates an irregular profile pipeline filling procedure involving air-release through an air valve. The analysis includes real-time data tests and numerical simulations using Computational Fluid Dynamics (CFD). A Digital Twin model was proposed and applied to filling maneuvers in water installations. In particular, this research considers an often-overlooked aspect, such as filling a pipe with an irregular profile rather than a simple straight pipe. CFD simulations have proven to capture the main features of the transient event, which are suitable for tracking the air-water interface, the unsteady water flow, and the evolution of the trapped air pocket. Thus, they provide thorough and reliable information for real-time operational processes in the industry, focusing on the filling pressure and geometry of the air-valve hydraulic system. Additionally, this study provides details regarding the application of an efficient Digital Twin CFD approach, demonstrating its feasibility in optimizing the filling procedure in pipes with irregular profiles. [ABSTRACT FROM AUTHOR]

Pipeline leakage, which leads to water wastage, financial losses, and contamination, is a significant challenge in urban water supply networks. Leak detection and prediction is urgent to secure the safety of the water supply system. Relaying on deep learning artificial neural networks and a specific optimization algorithm, an intelligential detection approach in identifying the pipeline leaks is proposed. A hydraulic model is initially constructed on the simplified Net2 benchmark pipe network. The District Metering Area (DMA) algorithm and the Cuckoo Search (CS) algorithm are integrated as the DMA-CS algorithm, which is employed for the hydraulic model optimization. Attributing to the suspected leak area identification and the exact leak location, the DMA-CS algorithm possess higher accuracy for pipeline leakage (97.43%) than that of the DMA algorithm (92.67%). The identification pattern of leakage nodes is correlated to the maximum number of leakage points set with the participation of the DMA-CS algorithm, which provide a more accurate pathway for identifying and predicting the specific pipeline leaks. [ABSTRACT FROM AUTHOR]

This article focuses on water security in Mykolaiv, a city of 0.5 million inhabitants in southern Ukraine, in the situation of scarcity of usable water resources caused by climate change and military operations. This problem arose after the Dnipro-Mykolaiv water pipeline was destroyed in April 2022 as a result of military operations and the supply of drinking water to the city was cut off. To ensure that the city's population has constant access to sufficient water of acceptable quality, a search for alternative water sources and a climate risk assessment were carried out for the new municipal water supply system from the Southern Bug River. The possible change in flow and its intra-annual distribution under the influence of climate change was modeled using the WaterGAP2 hydrological model and climate projections under the SSP1-2.6 and SSP5-P8.5 scenarios. It was found that under the SSP1-2.6 scenario, the reduction in river flow will be insignificant (up to a maximum of 14% in the far future) and there will be no restrictions on the city's water supply from this section of the river in the near (2021-2050) and far (2051-2080) period. The maximum water withdrawal for municipal water supply and the minimum environmental flow will reach their maximum value only in August (56% of the projected flow), which is not critical. Under the SSP5-8.5 scenario, in the long-term perspective of 2051-2080, the largest decrease in runoff will occur from May to October, and the water withdrawal will increase to 40-79% of the projected flow. The use of the research results not only in water management, but also in municipal administration, and their dissemination in territorial communities will contribute to the successful adaptation of socioeconomic and environmental processes in the region and can bring successful benefits not only to the economy, but also to communities. [ABSTRACT FROM AUTHOR]

Damages caused by possible earthquake scenarios are predicted by earthquake engineers. To determine the performance of water distribution systems after an earthquake scenario, there is a need for network reliability analysis. While performing earthquake hazard analysis, defining the seismic vulnerability model, and estimating the probability of pipeline failure, the study discusses the effects of various earthquake scenarios on pipeline reliability. The innovation of the study is the inclusion of the results of the Probabilistic Seismic Hazard Analysis (PSHA) in the reliability analysis and the investigation of the seismic performance of the pipelines according to various probabilistic methods. The results emphasize the use of Monte Carlo method in estimating the reliability of lifelines, and the need to consider two or more focal earthquakes in estimating the vulnerability of water distribution systems. [ABSTRACT FROM AUTHOR]

The safety assessment and control of large-diameter pipelines under tunnel blasting at ultrasmall clear distances is a significant problem faced in construction. However, there has been no reference case for the quantitative comparison of the disturbance degree of surrounding rock by using two blasting schemes of non-electric detonator design and electronic detonator design under a similar total blasting charge consumption. In this study, the blasting test was carried out based on the engineering background of drilling and blasting methods to excavate the tunnel under the water pipeline at a close distance. The peak particle velocity (PPV), stress, and deformation responses of the pipeline under the two construction methods of non-electric and electronic detonators were comparatively analyzed. The PPV can be remarkably reduced by 64.2% using the hole-by-hole initiation of the electronic detonators. For the large-diameter pipeline, the PPV on the blasting side was much larger than that on the opposite side because the blasting seismic wave propagated a longer distance and attenuated more rapidly, owing to its greater cavity vibration reduction effect. The PPV of the electronic detonators decayed more slowly than that of the non-electric detonators. The cumulative damage caused by consecutive hole-by-hole blasting using electronic detonators was less than that caused by simultaneous multi-hole initiation using non-electric detonators, with a reduction of about 50.5%. When the nearest peripheral holes away from the pipeline are detonated, the cumulative damage variable D and damage range increase rapidly. The PPV, dynamic tensile strength, and cumulative damage variables were used to evaluate the safety of the pipelines. [ABSTRACT FROM AUTHOR]

This study utilizes Computational Fluid Dynamics (CFD) to generate pressure and flow rate values for the analysis of flow characteristics and the diagnosis of leaks in inclined pipelines. The Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) solver in OpenFOAM software was modified to incorporate the effect of pipe orientation angle. Subsequently, the SIMPLE solver was employed to simulate the flow of water through the pipe. Leakage rates were observed to vary in magnitude with respect to leak position and pipe orientation angle, except that leaks close to the flow inlet and pipes with a greater inclination were associated with higher leakage rates. A mathematical leak model is proposed based on non- dimensional flow variables and pipe orientation angle. To generate sufficient pressure values and leakage rates, the CFD simulation was performed 70 times. These values were then incorporated into the mathematical model for the leak location to be predicted. The proposed method is applicable to the detection of leakages of varying sizes in pipelines with different orientations. Therefore, knowing the pipe orientation angle and measurements of inlet flow rate, outlet flow rate, and pressure drop, the model can be used to precisely locate leaks in a pipeline. [ABSTRACT FROM AUTHOR]

The efficient management of urban water distribution networks is crucial for public health and urban development. One of the major challenges is the quick and accurate detection of leaks, which can lead to water loss, infrastructure damage, and environmental hazards. Many existing leak detection methods are ineffective, especially in complex and aging pipeline networks. If these limitations are not overcome, it can result in a chain of infrastructure failures, exacerbating damage, increasing repair costs, and causing water shortages and public health risks. The leak issue is further complicated by increasing urban water demand, climate change, and population growth. Therefore, there is an urgent need for intelligent systems that can overcome the limitations of traditional methodologies and leverage sophisticated data analysis and machine learning technologies. In this study, we propose a reliable and advanced method for detecting leaks in water pipes using a framework based on Long Short-Term Memory (LSTM) networks combined with autoencoders. The framework is designed to manage the temporal dimension of time-series data and is enhanced with ensemble learning techniques, making it sensitive to subtle signals indicating leaks while robustly dealing with noise signals. Through the integration of signal processing and pattern recognition, the machine learning-based model addresses the leak detection problem, providing an intelligent system that enhances environmental protection and resource management. The proposed approach greatly enhances the accuracy and precision of leak detection, making essential contributions in the field and offering promising prospects for the future of sustainable water management strategies. [ABSTRACT FROM AUTHOR]

Introduction: Internal erosion triggered by water pipeline leaks seriously threatens the stability of the urban ground. Hangzhou, a city in Zhejiang Province, China, is facing critical challenges due to urban ground collapse (UGC) caused by internal erosion. However, there is a lack of research on the prevention of UGC by improving the internal erodibility of underground soil. Addressing this issue is of utmost importance to ensure the city's stability and safety. This paper proposes to improve the internal erodibility of typical sandy silt soils with chemical stabilisers. Methods: The effects of three chemical stabilisers, lignosulphonate (LS), lime (LI), and lignin fibre (LF), on the critical shear stress (rc) and erosion coefficient (kd) of sandy silt soils were investigated, which from Hangzhou, Zhejiang, China, by the hole erosion test (HET) at different mixing amounts and at different conservation times. Results: The findings indicate that LF mainly improves the erosion resistance of sandy silt by increasing rc, and the maximum increase is 2.38 times; LI mainly improves the erosion resistance by decreasing kd, and the maximum decrease is 2.18 times. After adding LS, rc and kd did not change significantly. The scanning electron microscope (SEM) test revealed that the inclusion of LF led to the formation of larger agglomerates in the sandy silt soil. The microstructure of sandy silt soil remained dispersed even after adding LS. Various chemical stabilisers used to improve sandy silt soils exhibited distinct erosion mechanisms. Sandy silt soils improved with LF exfoliated into agglomerates, displaying high resistance to erosion. On the other hand, the sandy silt treated with LF still lacks a protective layer and shows minimal improvements in its ability to withstand erosion. In contrast, the LS-amended sandy silt remains stripped with individual soil particles with insignificant changes in erosion resistance. Discussion: This study can provide a conceptual framework for choosing foundation treatment techniques in future urban development projects. [ABSTRACT FROM AUTHOR]

Water leakages are assessed with an extended period simulation (traditional analysis) in water distribution networks. However, when rapid manoeuvres regulate valves, the conventional analysis proves unsuitable for representing the water volume of leaks. Under these circumstances, the Rigid Water Column Model can be utilised to accurately compute the quantity of water volume leaks. This method has been applied to single and parallel pipelines to predict water leakages, considering the opening and closure manoeuvres of regulating valves. This research develops governing equations using the Rigid Column Model to predict water volume leaks in a general scheme of series pipelines, accounting for the opening and closure manoeuvres in regulating valves. The practical application involves two branches of a series pipeline with internal pipe diameters of 0.45 and 0.25 m and pipe lengths of 1200 and 1400 m, respectively. The results of this practical application demonstrate the accuracy of the Rigid Column Model and its relevance in real-world scenarios. For instance, the model shows that traditional analysis can overestimate water volume leaks by approximately 72% when a closure manoeuvre regulates valves for 200 s and by about 28% for 30 s, highlighting the need for a more accurate method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Converting surplus electricity into hydrogen is considered a promising way for accommodating large-scale wind or solar power. However, it is expensive to establish a new-built hydrogen network or storage facilities at the current stage. Hydrogen-enriched compressed natural gas (HCNG), a mixture of natural gas and hydrogen, can be an alternative approach to consuming surplus renewable energy in the short-medium term. This paper investigates the feasibility of establishing an electricity-gas-hydrogen coupled energy system by modeling the HCNG network, power grid, and hydrogen electrolyzer in Ireland with consideration of pipeline characteristics. The economic analysis based on the planning results of the coupled system is presented in detail. When the hydrogen injection ratio reaches 20% at the HCNG stations, the system operating cost and carbon emission can be reduced by 24.2% and 6.4%, and 100% wind can be consumed. • A detailed modeling method for HCNG pipeline pressure drop and line pack is proposed. • An EGH-IES planning model encompassing entire HCNG supply chain is established. • A case study is conducted based on the real energy system in Ireland. [ABSTRACT FROM AUTHOR]

The importance of the buried pipelines lies in two main topics: the first is related to the very long length of these pipes, and therefore protecting them is expensive. The second topic is related to environmental pollution due to leaching, which is considered one of the main pollutants of groundwater. The research reviews the effects of geosynthetic reinforcement and its effect on buried pipelines subjected to different loading conditions to reduce the stresses on them and thus prevent leakage. The loads covered in this literature are the following: static load, dynamic load, permanent ground deformation, accidental damage, uplift pressure, explosion, lateral loading, and abrasive shear loading. The research focused on the use of synthetic ground reinforcements to protect these pipes. Available experimental and numerical investigations indicate the potential of using geosynthetics to reduce the effects of external loads on buried pipelines. The investigated studies proved that the protection of buried pipes with different types of geosynthetics is a successful method and decreased the stresses transformed to buried pipes. Most of the studies (45%) dealt with buried pipes subjected to static loading. The conventional geosynthetic material used in the protection of buried pipes is geogrid (38%). [ABSTRACT FROM AUTHOR]

Infrastructure deterioration is a threat to developed countries, emphasizing the need for effective management techniques. In particular, the leakage of aged domestic sewer pipeline is a major health issue, yet there is a lack of markers to identify domestic leakage. We studied the pollution in urban waters resulting from domestic sewage leakage into storm drainages. We monitored caffeine, fragrance substances and polycyclic aromatic hydrocarbons (PAHs) in the storm discharge points in five urban districts having separate sewer systems aged from 10 to over 40 years. Results show that caffeine and fragrance concentrations tended to increase with sewer system age. For instance, caffeine concentrations in the areas of sewer systems over 40 years old were at least two orders of magnitude higher than in 10-year-old sewer systems, and were as high as 1–10% of domestic sewage, strongly suggesting the leakage of domestic sewer pipelines. PAHs exhibited consistent patterns across the districts. Overall, we observe that sewer leaking processes can be distinguished by analyzing the levels of organic pollutants. [ABSTRACT FROM AUTHOR]

A probabilistic approach that considers the entire lifecycle cost of the water pipeline, accounting for deterioration rate, failure consequences, cost of rehabilitation, accuracy and cost of inspection/condition assessment, cost of emergency repair versus planned intervention and cost of total pipe replacement was introduced in an earlier paper. The approach allows us to combine expert-opinion (semi-informative assessment) with hard field data. New hard field data (e.g., failure events, inspection/condition assessment results) continually become available throughout the life of the pipeline. This incoming data stream can be incorporated into the analysis to provide robust, well-informed and reproducible assessment of deterioration rate and remaining life. The framework was implemented in an MS-Excel-based decision support tool, referred to as pipeline inspection decision analyzer (PIDA). This paper demonstrates the practical application of the proposed framework in the real world through comprehensive case studies, data for which were obtained from collaborating Canadian and US water utilities and pipeline owners. As is always the case in reality, most pipeline owners did not have all the required data to carry out a fully informed analysis. We illustrate how one might deal with missing data, how PIDA may be used to arrive at well-supported, rational decisions on when to deploy inspection and condition assessment, what techniques/technologies to select among competing ones and when it is time to stop assessing the pipeline condition and plan for replacement. Sensitivity analyses are also conducted to explore how various assumptions, necessitated by uncertainty, may impact analysis results. [ABSTRACT FROM AUTHOR]

This study assessed the vulnerability of groundwater resources to the failure of the urban fuel distribution network under an earthquake. A case study of the Tehran, Iran, gas distribution network and the Tehran–Karaj Plain aquifer was conducted. To assess the seismic vulnerability of buried fuel pipelines in Tehran based on the fuel distribution network components, three possible earthquake scenarios were studied. To assess damage to the pipeline, a comprehensive model was developed using machine learning (ML). This model can assess and predict damage to a fuel pipeline and its type (i.e., leakage or full breakage). Moreover, aquifer contamination was assessed using the DRASTIC model. It was found that the ML-based pipeline seismic vulnerability assessment model had good performance in predicting seismic damage to the fuel distribution network, with a RMS error (RMSE) and a correlation coefficient (R) of 0.004 and 0.99, respectively. The results showed that the presented model had an acceptable efficiency in assessing the probability of seismic vulnerability of the buried pipeline and analyzing the pollution of the aquifer based on different earthquake scenarios. The developed groundwater seismic vulnerability assessment model can be used for further analysis in future research. Practical Applications: Earthquakes are one of the most important natural disasters, and have caused widespread financial, human, and environmental losses in different regions of the world, especially in seismic areas. The existence of faults and the possible deterioration of buried pipes makes earthquake crisis and its serious damage to humans and the environment more severe. One of the most important threats in this situation is the contamination of underground water with hydrocarbon substances due to leakage from the fuel transmission network. In this research, to evaluate the pollution of the aquifer due to the damage to the fuel transmission network, we developed a model using the machine learning method to analyze the vulnerability of the buried pipeline. The DRASTIC model also was used to evaluate aquifer pollution. To evaluate the presented model, the fuel transmission network and aquifer of Tehran, Iran, were studied. The results indicated acceptable performance of the proposed model for assessing the seismic vulnerability of groundwater. The presented model can be used for other areas. [ABSTRACT FROM AUTHOR]

Grabens, or valleys formed during extensional tectonic events, are common but rarely observed during formation. In November 2023, inelastic surface deformation formed abruptly along Iceland's plate boundary in Grindavík. We documented graben formation in real‐time through satellite mapping (InSAR), seismicity, GNSS data, repeated lidar surveys, and field mapping. Five normal faults and ∼12 fissures ruptured the surface delineating two grabens separated by a horst, a context not present in other contemporary case studies. The graben normal faults slipped rapidly (over hours) and maximum surface motions coincided with the occurrence of turbulent seismic swarms in both space and time. Although 3 eruptions took place ∼15 km northeast of Grindavík from 2021 to 2023, attributed to magma intrusions (i.e., dikes), none of these also formed grabens. Thus, the Grindavík grabens shows evidence for tectonic origins. Real‐time monitoring of these phenomena provide insight into graben formation on Earth and potentially on other planets. Plain Language Summary: Valleys known as grabens, typically caused by extensional tectonic events, are a common geological feature, yet their formation is rarely observed. In November 2023, such two grabens suddenly emerged along the boundary between tectonic plates in the town of Grindavík, Iceland. The grabens were shaped by tectonic activity expressed by a swarm of earthquakes and associated ground deformation and resulted in normal faults rupturing the surface and cutting through houses, linear infrastructure including water pipelines and roads within Grindavík. We document the grabens and horst in real time using satellite mapping (InSAR), geodetic GPS data, repeated drone surveys, field mapping, and seismic recordings from a local seismic network. The combination of these data provide unprecedented level of precision in characterizing surface and sub‐surface deformations, especially when maximum surface motions correlate with a turbulent seismic activity in both space and time. Critically, following the formation of the grabens, a series of intensive through short‐lived eruptions happened in December 2023, January 2024, February 2024, March, and May 2024 within the northernmost portion of the grabens. Our observations provide valuable insights into the natural laboratory of Iceland and contribute to the understanding of plate tectonics both on Earth and other planets. Key Points: The 2023 seismic swarm and extension lead to a graben forming that coincides in time and space along Iceland's plate boundaryDuring 2021 to December 2023 only one tectonic graben formed, although 4 eruptions have taken placeThe graben in Grindavík, Iceland is wider at the surface than most recently documented grabens (∼4,500 m vs. <1,000 m) [ABSTRACT FROM AUTHOR]

The pressure characteristics of long-distance water pipelines during hydraulic transient processes are crucial for ensuring the safe, stable, and long-term operation of water transfer projects. This paper establishes a one-dimensional mathematical model based on sections of the Yinjiangjihuai long-distance water diversion project in China. The water supply requirements of the pipelines are categorized into two replenishment modes as follows: gravity supply and pump-pressurized water supply. The opening and closing strategies of the water pipelines under different flow conditions are simulated and analyzed to explore the hydraulic transient processes under various water supply modes. The transient variations of key hydraulic parameters during valve closure are clarified. Simulation results indicate that the water pipeline design is reasonable, meeting the water supply demands at relatively low Manning values and that it has the capability for long-term supply. Due to the excessive head provided by the pumps, pump-pressurized water supply and gravity supply modes cannot operate simultaneously. Under gravity supply mode, the minimum pressure in the downstream pipeline is relatively higher overall, while the maximum pressure in the upstream pipeline is relatively lower overall. In the pump-pressurized water supply mode, the safety and stability of the water supply can be ensured by adjusting the closing time of individual pumps and the interval time between adjacent pumps. The research findings provide technical guidance and scientific basis for the construction of national water networks and water transfer projects. [ABSTRACT FROM AUTHOR]

Urban water systems worldwide are confronted with the dual challenges of dwindling water resources and deteriorating infrastructure, emphasising the critical need to minimise water losses from leakage. Conventional methods for leak and burst detection often prove inadequate, leading to prolonged leak durations and heightened maintenance costs. This study investigates the efficacy of logic- and machine learning-based approaches in early leak detection and precise location identification within water distribution networks. By integrating hardware and software technologies, including sensor technology, data analysis, and study on the logic-based and machine learning algorithms, innovative solutions are proposed to optimise water distribution efficiency and minimise losses. In this research, we focus on a case study area in the Sunbury region of Victoria, Australia, evaluating a pumping main equipped with Supervisory Control and Data Acquisition (SCADA) sensor technology. We extract hydraulic characteristics from SCADA data and develop logic-based algorithms for leak and burst detection, alongside state-of-the-art machine learning techniques. These methodologies are applied to historical data initially and will be subsequently extended to live data, enabling the real-time detection of leaks and bursts. The findings underscore the complementary nature of logic-based and machine learning approaches. While logic-based algorithms excel in capturing straightforward anomalies based on predefined conditions, they may struggle with complex or evolving patterns. Machine learning algorithms enhance detection by learning from historical data, adapting to changing conditions, and capturing intricate patterns and outliers. The comparative analysis of machine learning models highlights the superiority of the local outlier factor (LOF) in anomaly detection, leading to its selection as the final model. Furthermore, a web-based platform has been developed for leak and burst detection using a selected machine learning model. The success of machine learning models over traditional logic-based approaches underscores the effectiveness of data-driven, probabilistic methods in handling complex data patterns and variations. Leveraging statistical and probabilistic techniques, machine learning models offer adaptability and superior performance in scenarios with intricate or dynamic relationships between variables. The findings demonstrate that the proposed methodology can significantly enhance the early detection of leaks and bursts, thereby minimising water loss and associated economic costs. The implications of this study are profound for the scientific community and stakeholders, as it provides a scalable and efficient solution for water pipeline monitoring. Implementing this approach can lead to more proactive maintenance strategies, ultimately contributing to the sustainability and resilience of urban water infrastructure systems. [ABSTRACT FROM AUTHOR]

In the operation of water distribution networks in cities, leakage from pipes always causes problems for human health and for the environment. Leakage openings in pipes may exist in different shapes. Circular holes are common in corroded and punched pipes. In the leakage studies, the area of these openings is usually assumed to be fixed and the leakage exponent is about 0.5. In this study, an analytical equation has been presented with two purposes. First, Examining the changes in the leak area and leakage exponent of circular holes. Second, providing an equation that contains more parameters than the general leakage equations. By using such an equation, the accuracy of leakage estimation is increased due to the direct involvement of the effective parameters. Also, for the possibility of modeling different leakage equations, including the present equation, a new hydraulic analysis model has been developed. This model tries to improve leakage modeling by including more capabilities than the existing hydraulic analysis models. Results showed that the leak area in circular holes is not fixed and changes due to different parameters. Comparison of the present equation and the orifice equation showed a significant difference which confirms that the orifice equation cannot be always used for circular leaks. In the study of leakage exponent, it was found that for polyethylene pipes, the leakage exponent is higher than value of 0.5 mentioned in the other studies and it can take different values depending on the leakage position in the network. Increasing the hole diameter did not affect the leakage exponent, but increased the leakage coefficient. On the other hand, for steel pipes, the leakage coefficient was fixed and the exponent remained around 0.5. Finally, the results showed the usefulness of the developed hydraulic analysis model for implementing the scenarios defined in this study. [ABSTRACT FROM AUTHOR]

Welding residual stress will increase the risk of stress corrosion cracking of welded joints in service. It is crucial to study the distribution of welding residual stress in welded joints. In order to study the mechanical property and microstructure of the joint, a two-dimensional model is established based on the actual morphology. The results show that the maximum residual stress occurs in the welded metal. The Mises stress is 355 MPa, and the circumferential stress is 362 MPa. After welding, the outer surface maximum circumferential residual stress is 388 MPa, and the maximum axial residual stress is 357 MPa, which is in good agreement with the simulation results. The microhardness distribution appears as base metal > heat-affected zone > welded metal. The distribution of maximum shear strength is similar to the microhardness. The main phase composition consists of proeutectoid ferrite, acicular ferrite, massive ferrite, and a small amount of granular carbide precipitates. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes' condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks. [ABSTRACT FROM AUTHOR]

The decline of biodiversity is a key topic in public discussions around the globe. These debates have triggered massive efforts to increase protected areas and to safeguard the corridors connecting them. The wildlife corridors dealt with in this article are mainly thought to facilitate the mobility of elephants and some other large herbivores (for example, zebra and buffalo). Wildlife corridors are not only essential for species connectivity but also an integral part of the booming ecotourism in north-eastern Namibia's conservation landscapes. Coexistence infrastructure is meant to contribute to economic development and local incomes. Conservancies — community-based conservation organisations in the Namibian context — gazette corridors and market wildlife abundance to ecotourists, potential investors in tourism and commercial hunters. The coexistence of humans and wildlife is challenging, though. Human-wildlife interactions frequently result in damage, and often conservationist environmental infrastructuring runs against the aims of farmers to expand their fields for commercial crop production and to gain pastures for growing cattle herds. It also runs against other governmentally endorsed infrastructuring that brings tarred roads, water pipelines and boreholes. This article analyses contested wildlife corridors as part of a larger conservationist project in the western parts of Namibia's Zambezi Region. [ABSTRACT FROM AUTHOR]

The separate sewer system has led to severe river pollution because of domestic sewage infiltrations and initial rainfall pollution. Therefore, interception wells (IWs) are installed to divert sewage to the wastewater treatment plant but similarly contribute to overflow-induced river pollution on rainy days. The aim of the present study is to propose a control strategy for the regulation of IWs' overflow based on the online monitoring data, control measures, and software simulation. The results indicate that during light rain, overflow from the IWs is minimal, requiring no control measures. However during heavy rainfall, the overflow of sewage leads to an increase in the river's concentration of NH3-N from 0.25 to 3.04 mg/L. Finally, Simulations demonstrate a reduction in river NH3-N levels from 2.27 to 1.33 mg/L after implementation. The results indicated the substantial effectiveness of measures in mitigating the pollution originating from IWs' overflows during rainfall events. [ABSTRACT FROM AUTHOR]

Entrapped air pockets in water pipelines play a significant role in influencing transient over-pressures during filling procedures. Several research is focused on highlighting the attenuation of pressure peaks in pipes with single air pockets. This research studies the air-water interaction during rapid water filling processes in an irregular pipeline and air pockets in different branches, and how the trapped air can attenuate the over-pressure peaks. A three-dimensional computational fluid dynamics (CFD) model was developed, and numerical results of the model were validated through experimental measurements. For a given initial air pocket condition upstream of the high point, the maximum air pocket over-pressure was 11% to 32% lower when the descending pipe segment initially contains air compared to when it contains water. In sum, it was found that entrapped air pockets at high points of water pipelines can help mitigate transient over-pressures considering specific initial hydraulic conditions prior to filling operations. [ABSTRACT FROM AUTHOR]

Intermittent water supply systems are prone to air entrapments during the pipe filling phase. This work aims to analyse and discuss the numerical results obtained by applying the recently developed AirSWMM model, an extension of SWMM incorporating air phase, to a laboratory network. Experimental data consisting of pressure-head at multiple locations and video recordings of air entrapments are collected in a single loop network with a high point, for different pipe-filling conditions, system layouts and node elevations. Experimental tests have shown that the air entrapment occurred not only at the high point but also throughout the pipe network, creating air pockets with elongated shapes and larger volumes than for single pipes. AirSWWM model with air-entrapment formation, growth and transport is tested in the pipe network, and results are compared with measurements. AirSWWM model can correctly locate large air pockets but underestimates their volume. [ABSTRACT FROM AUTHOR]

In order to reduce the power of methane explosion in natural gas pipelines and effectively improve the explosion suppression efficiency of a single explosion suppressant, we carry out the explosion suppression of HFC‐227ea/carbon dioxide mixed gas as well as mixed gas/ultrafine water mist through a self‐built methane explosion suppression experimental platform. Based on the changes in parameters such as explosion overpressure, flame propagation velocity, and flame propagation structure, the coupling mechanism of methane explosion suppression between mixed gases and between mixed gases and ultrafine water mist is revealed, which provides scientific support for promoting the development of methane explosion suppression technology. The experimental results show that when the mixed gas HFC‐227ea/carbon dioxide and ultrafine water mist synergistically suppresses methane explosion, the addition of the mixed gas can effectively improve the suppression effect of ultrafine water mist on methane explosion. [ABSTRACT FROM AUTHOR]

Detecting human impact on freshwater ecosystems is problematic without rigorous assessment of temporal changes. Assessments of mining impacts are further complicated by the strong influence of local catchment geology on surface waters even in unmined environments. Such influence cannot be effectively considered by using broad-scale reference frameworks based on regionalization and stream types. Using the BACI (Before-After Control-Impact) design, we examined the impact of mining discharges on freshwater algae and macroinvertebrate communities resulting from the rerouting of treated wastewaters through a pipeline to larger water bodies in Northern and North-Eastern Finland. Impacted sites and control sites were sampled 1 to 2 years before and 1 to 3 years after the pipelines became operational. Stream diatom communities recovered from past loadings upstream of the pipeline (which was no longer impacted by wastewaters) after rerouting of the wastewaters, while no changes downstream from the pipeline were detected. Upstream from the pipeline, diatom species richness increased and changes in relative abundances of the most common diatom taxa as well as in the overall community composition were observed. The effects of the pipeline were less evident for stream macroinvertebrate communities. There was an indication that regional reference conditions used in national biomonitoring may not represent diatom communities in areas with a strong geochemical background influence. Lake profundal macroinvertebrate communities were impacted by past loadings before the construction of the pipeline, and the influence of the pipeline was observed only as changes in the abundances of a few individual species such as phantom midges (which increased in abundance in response to discharges directed through the pipeline). Our results highlight the variable influence of mining discharges on aquatic communities. Statistically strong monitoring programmes, such as BACI designs, are clearly needed to detect these influences. [ABSTRACT FROM AUTHOR]

Maintenance-Renewal Works (MRWs) are among the most complicated planning operations of water companies and usually involve a group of experts. However, experts are often hesitant in their decision making as they often need to rely on unreliable quantitative operational data, which prompts doubts about the effectiveness of their decisions. This problem can be addressed by using linguistic (qualitative) values instead of imprecise numerical data. Hence, this study develops a qualitative-risk-based model to plan the MRW of six Iranian networks comprising pipes with unreliable operational data. The study also investigates the effectiveness of group decisions on planning pipe MRW. The results indicate that planning with imprecise numerical operational data can be improved by using a qualitative-risk-based model. Additionally, it is found that group decisions do not significantly change the pipe priorities, although they have a decisive effect on determining the pipe maintenance-renewal strategies. Furthermore, increasing the number of criteria is found to lead to more accurate results within the developed model, although increasing the number of decision-makers has no decisive effect on the results. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the journal Processes titled "Process Monitoring and Fault Diagnosis." The issue explores the application of data analytic techniques to enhance stable operation and safety in chemical processes and related industries. The collection of research papers covers various topics, including process fault detection, bearing fault diagnosis, remaining useful life prediction, and more. The papers introduce cutting-edge methodologies and demonstrate their reliability through validation. The issue aims to foster communication and the development of advanced process monitoring techniques. [Extracted from the article]

ABSTRACT Protection devices can be used to protect a water transmission system in a hydraulic transient state, such as the Air Chamber, which can dampen both positive and negative pressure waves. This study proposes an optimal sizing of air chambers through genetic algorithms NSGA-II and NSGA-III combined with air valves in the pipeline. A real-life transmission system located in Brasilia-Brazil was simulated and analyzed. The results indicate the effectiveness of both algorithms in seeking optimal solutions and show the influence of guaranteeing safe minimum pressures in decision-making. We generate a Pareto front and highlight the best solutions.

Buried PVC water pipeline is prone to deformation due to the influence of unfavorable factors such as external load and soil collapse. Once the deformation exceeds the critical threshold, serious consequences such as leakage and pipeline burst may occur. In response to the crucial issue of monitoring PVC pipeline deformation, the feasibility of utilizing FBG (fiber Bragg grating) sensing technology to monitor the deformation of acrylate polymer blended with poly resin (ABR) pipe subjected to external pressure and soil collapse is explored in this study. To assess the monitoring performance of FBG on the ABR pipe's surface, an analysis method for package failure and pasted failure of FBG is introduced, along with the calculation formula for strain attenuation based on the Goodman model and the method for calculating the minimum adhesion length. A total of 20 ABR pipes with two cross‐sectional forms and different calibers are arranged with external pressure tests or soil collapse tests in this investigation. In the two tests, the circumferential strain measured by FBG is used to analyze the deformation of the ABR pipe and the bending strength. To validate the precision of FBG, a comparison between the strain curve measured by the strain gauge and that measured by the FBG sensors is conducted. The results of the two tests indicate that the deformation of the ABR pipe can be well monitored and the method can be applied to the field applications. [ABSTRACT FROM AUTHOR]

Due to the rising costs of transportation and the more advanced treatment needed to meet the water demands of the urban population, the costs of potable water tend to increase as cities expand. For some water uses, potable water is not required, such as concrete mixing industries. Previous studies have proven the viability of using reused water in concrete production. In Caju, Rio de Janeiro, four large concrete mixing plants (CMPs) are located close to the Alegria Wastewater Treatment Plant. This study focused on assessing the technical and financial feasibility of reusing these effluents as an alternative source of water for the four CMPs. The alternatives were potable and reused water via two supply methods, water tank trucks and pipelines. All costs were analyzed and projected into the future with the market cost of capital. After comparing the costs, the use of reclaimed water proved to be highly feasible, especially when a using pipeline to supply the CMPs. The present costs for the reclaimed water supply were calculated to be USD 0.99 per m3 for the pipeline alternative and the other alternatives varied in being 5 to 7 times more costly. This water reuse project using pipelines to transport reclaimed water to concrete mixing plants provides a feasible, sustainable alternative water supply in water stressed regions such as Rio de Janeiro. [ABSTRACT FROM AUTHOR]

Investigating the mechanism of sudden water inrush and mudflow in mountain tunnels is crucial for implementing preventive measures. Tunnel excavation through a fault or fractured zone can easily trigger sudden water inrush or mudflow. In this paper, the coupled lattice Boltzmann method (LBM) and discrete element method (DEM) were employed to reproduce the process of water and mud inrush in mountain tunnels. The failure of tunnel mud burst and water inrush involves a fluid–solid coupling process. A two-dimensional Boltzmann method for fluids and DEM for particles were utilized, with the coupled LBM-DEM boundary adopting the immersed moving boundary method. For simulating the water inrush process, a numerical model was established to replicate the flow of water particles within karst pipelines, featuring dimensions of 7 cm length, 4 cm width, and consisting of 100 particles. Particles are transported through water flow to the outlet of karst pipelines under hydraulic gradient loading. When the hydraulic gradient exceeds 6, the Darcy velocity gradually tends to be constant. As for simulating the mud inrush process, a numerical model was developed with dimensions of 5 cm length and 4 cm height, incorporating 720 randomly generated particles. The results demonstrated the successful reproduction of the evolution process encompassing three consecutive stages of tunnel mud-burst failure: initiation, acceleration, and stabilization. The occurrence of mud inrush disasters is attributed to combined action involving disaster-causing geotechnical materials, groundwater pressure, and tunnel excavation. [ABSTRACT FROM AUTHOR]

Infrastructure facilities that serve the city as a whole and should be considered as a whole should be built in an orderly and planned manner, just as cities are. Infrastructure facilities become obsolete over time. Aging infrastructure facilities may become unserviceable over time. When the need for maintenance and repair arises, it is mandatory to renew or replace infrastructure facilities. In this case, necessary maintenance/repair and renovation works should be completed as soon as possible. These infrastructure facilities may not be transferred to maps in the digital environment and may often be managed with person-oriented information, not institutional. There is a problem for decision makers, namely, that the construction, maintenance, repair and governance of infrastructure facilities cannot be carried out systematically, on time and effectively. The only way to provide such a service is through the combined use of today's informatics, Geographical Information System (GIS) and Global Navigation Satellite System (GNSS) technologies, unlike the classical methods of the past. The aim of the study is to effectively manage the scarce resource of drinking water and its facilities, which are an important component of infrastructure facilities, with a method that uses current mapping technologies and informatics facilities. Especially after Infrastructure for Spatial Information (INSPIRE) and the transformation of Land Administration Domain Model (LADM) to the International Organization for Standardization (ISO) standard, Turkish National Geographic Information System (TNGIS) studies and many academic studies carried out in Türkiye have been modelled with Unified Modelling Language (UML) diagrams in accordance with LADM. Similarly, within the scope of this study, UML diagrams were prepared, and then a GIS database was established. Thanks to field workers, chiefs, engineers and others working on water pipelines, all necessary data, classic, as-built and digital, were gathered. These were collected in different ways in order to conduct spatial and non-spatial analysis in the study area of Trabzon. The most important result from the study is that the entire drinking water infrastructure of Trabzon has been transferred to the system in a structure that allows spatial queries, ensuring that damage detection on water components, maintenance and repair processes are carried out in the shortest time and at the lowest cost. The investigation and application of a sensor-integrated GIS-aided system, making it possible to control and monitor the use of lost and illegal water to be controlled as well as inform consumers who will be affected by possible maintenance and repair, is recommended. [ABSTRACT FROM AUTHOR]

The development of new hydro turbines or the optimization of traditional hydro turbines is one of the research directions that scholars have been interested in to broaden the source of hydropower and improve energy efficiency. In our previous work, a Francis turbine was used in the water supply systems of high-rise buildings to properly control water pressure inside the pipeline and recover excess water energy. In this paper, an optimization study of the volute for the sectional shape, design method, inlet parameters, outlet width, and tongue was conducted using numerical simulations to improve the hydro turbine performance. The simulated results show that a circular section could better enhance the flow velocity inside the volute and make the flow velocity distribution more uniform at the volute outlet, and the equal mean velocity method is a more suitable volute design method in this special condition. The results of range analysis show that the water head reduction increases significantly with the increase in the inlet height, and both inlet height and outlet width have a significant effect on the efficiency. In addition, in the tongue optimization, a larger tilt angle corresponds to smaller output power and water head reduction; a larger stretch length in the limited angle range corresponds to larger output power and lower efficiency. Ultimately, the output power of the hydro turbine was increased by 18.65% and the efficiency by 2.1% through the volute optimization. [ABSTRACT FROM AUTHOR]

The aim of the present study was to assess the drinking water quality in the selected urban areas of Lahore and to comprehend the public health status by addressing the basic drinking water quality parameters. Total 50 tap water samples were collected from groundwater in the two selected areas of district Lahore i.e., Gulshan-e-Ravi (site 1) and Samanabad (site 2). Water samples were analyzed in the laboratory to elucidate physico-chemical parameters including pH, turbidity, temperature, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), total hardness, magnesium hardness, and calcium hardness. These physico-chemical parameters were used to examine the Water Quality Index (WQI) and Synthetic Pollution Index (SPI) in order to characterize the water quality. Results of th selected physico-chemical parameters were compared with World Health Organization (WHO) guidelines to determine the quality of drinking water. A GIS-based approach was used for mapping water quality, WQI, and SPI. Results of the present study revealed that the average value of temperature, pH, and DO of both study sites were within the WHO guidelines of 23.5 °C, 7.7, and 6.9 mg/L, respectively. The TDS level of site 1 was 192.56 mg/L (within WHO guidelines) and whereas, in site 2 it was found 612.84 mg/L (higher than WHO guidelines), respectively. Calcium hardness of site 1 and site 2 was observed within the range from 25.04 to 65.732 mg/L but, magnesium hardness values were higher than WHO guidelines. The major reason for poor water quality is old, worn-out water supply pipelines and improper waste disposal in the selected areas. The average WQI was found as 59.66 for site 1 and 77.30 for site 2. Results showed that the quality of the water was classified as "poor" for site 1 and "very poor " for site 2. There is a need to address the problem of poor water quality and also raise the public awareness about the quality of drinking water and its associated health impacts. [ABSTRACT FROM AUTHOR]

This short communication is based on a workshop on hydrogen network modeling in macro-energy system models discussing the whole hydrogen value chain: production, transmission, storage, and use, as well as the related issues of demand flexibility, alternative fuels of biological origin, and the integration with district heating. It was organized by the Danish research network ENERforsk with leading modelers from academia, industry, and transmission system operators. The workshop collected (1) lessons learned, (2) best practices, and (3) potential next steps. We conclude that no-regret pathways need to consider evolving hydrogen regulation while balancing social aspects with interests driven by green industrial policy. Important and uncertain issues include the repurposing of natural gas networks, considering hydrogen pipeline standards and existing contracts, or the disposal of brine water. As more demand sectors and carbonaceous fuels are included in the models, carbon management, sustainable biomass, and carbon networks become more important. Collecting and incorporating lessons learned, best practices, and potential next steps will help the modeling community and policymakers to develop sound policies. [ABSTRACT FROM AUTHOR]

The node pressure and flow rate along the shale gas flow process are analyzed according to the characteristics of the shale gas flow pipe network, and the non-leaking and leaking processes of the shale gas flow pipe network are modeled separately. The changes in pressure over time along each pipe segment in the network provide new ideas for identifying leaking pipe sections. This paper uses the logarithmic value of pressure as the basis for judging whether the flow pipe network is leaking or not, according to the process of varying flow parameters resulting in the regularity of leakage. A graph of the change in pressure of the pipe section after the leak compared to the pressure of the non-leaking section of pipe over time can be plotted, accurately identifying the specific section of pipe with the leak. The accuracy of this novel method is verified by the leakage section and statistical data of the shale gas pipeline network in situ used in this paper. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study on data preprocessing and modeling for predicting corrosion in water pipelines of a steel industrial plant. The use case is a cooling circuit consisting of both direct and indirect cooling. In the direct cooling circuit, water comes into direct contact with the product, whereas in the indirect one, it does not. In this study, advanced machine learning techniques, such as extreme gradient boosting and deep neural networks, have been employed for two distinct applications. Firstly, a virtual sensor was created to estimate the corrosion rate based on influencing process variables, such as pH and temperature. Secondly, a predictive tool was designed to foresee the future evolution of the corrosion rate, considering past values of both influencing variables and the corrosion rate. The results show that the most suitable algorithm for the virtual sensor approach is the dense neural network, with MAPE values of (25 ± 4)% and (11 ± 4)% for the direct and indirect circuits, respectively. In contrast, different results are obtained for the two circuits when following the predictive tool approach. For the primary circuit, the convolutional neural network yields the best results, with MAPE = 4% on the testing set, whereas for the secondary circuit, the LSTM recurrent network shows the highest prediction accuracy, with MAPE = 9%. In general, models employing temporal windows have emerged as more suitable for corrosion prediction, with model performance significantly improving with a larger dataset. [ABSTRACT FROM AUTHOR]

A biofilm is a layer of microbes that have aggregated to form a colony. The colony attaches to a surface with a slime layer which protects the microorganisms, promoting their growth and survival. Biofilms occur in various environments such as soils, sediments, wastewater, water pipelines, water purifying systems, cooling water systems, medical devices, archaeological monuments, marine vessels, and hospitals. Biofilms may induce adverse effects such as fostering drug-resistant strains. Here, we review biofilms with focus on their formation, occurrence in water systems, impact, microbial interactions, and characterization methods. Communication includes cell-to-cell interactions by quorum sensing, interactions mediated by flagella, gene, and signaling molecules, and interactions mediated by extracellular polymeric substances. Characterization methods comprise surface-enhanced Raman scattering spectroscopy, confocal laser scanning microscopy, scanning electron microscopy, fluorescence microscopy, sensors, and metagenomics analysis. [ABSTRACT FROM AUTHOR]

In the context of the Internet of Things, there is a growing demand for real-time monitoring of water distribution systems (WDS). Among the various leak detection methods, acoustic leak detection is considered to be a suitable method. However, existing methods are not very effective in environments with high daytime ambient noise. To address this issue, this paper conducted on-site data collection experiments and designed a monitoring system that combines traditional nighttime monitoring with daytime monitoring, combining water company pipeline inspections and repair work. A large number of daytime audio samples were collected. In this paper, the logarithmic spectrogram (log spectrogram) was used to represent the features of the leak signal. By comparing the features of the signal during day and night, noisy and quiet environments, and leak and normal signals, we identified the interfering frames that required noise reduction, and applied frame-level noise reduction processing to the signal. Based on this, a log PS-ResNet18 model was developed to identify leaks, and its performance was compared with other classification models [including traditional nighttime detection methods, random forests, XGBoost, and convolutional neural network (CNN)]. The results showed that the log PS-ResNet18 model had the best performance, with an all-day accuracy rate of 99.4% and a daytime accuracy rate of 99.3%. In addition, by conducting ablation experiments to explore the role and contribution of the log PS-ResNet18 and noise reduction methods in the model, the results showed that the log spectrogram and noise reduction methods increased the all-day accuracy rate by 18.8% and 23.2%, respectively, and by 24.7% when used together. In another practical application, the log PS-ResNet18 model achieved an all-day detection accuracy rate of 99.6%. This study demonstrated the applicability of the log spectrogram and CNN combination in daytime leak detection, overcoming research limitations in the field. This research presents the log PS-ResNet18 framework, which combines deep learning models and denoised logarithmic spectrograms to improve leak detection in water supply pipelines under daytime environmental noise. The research focuses on field data collection and analysis of cast iron pipes with different diameters in Hangzhou (HZ). The model was tested on cast iron pipes in Lishui (LS) and proved to be effective. The proposed method is highly versatile and can be applied to different regions and pipe materials after sufficient sample collection and model training validation. The research recommends a comprehensive leak monitoring solution that involves initial intelligent detection using front-end noise meters and secondary identification of suspicious audio signals using the log PS-ResNet18 model in the cloud. This enables water utility operators to respond quickly to pipeline leaks, leading to more efficient water resource conservation and improved water supply service quality. [ABSTRACT FROM AUTHOR]