Water Supply Pipe Research Articles

Automatic Detection of Water Supply Pipe Defects Based on Underwater Image Enhancement and Improved YOLOX

Automatic Detection of Water Supply Pipe Defects Based on Underwater Image Enhancement and Improved YOLOX

Analyzing the effects of extreme cold waves on urban water supply network safety: A case study from 2020 to 2021

Urban water supply networks are crucial for the transportation of water resources. However, with the increasing frequency and severity of cold wave disasters linked to climate change, the impact on water supply systems has become a critical concern. These impacts include pipe failures, customer water outages, and challenges in meeting peak winter water demand. To address this, our study analyzes data from cold waves in Shanghai from late 2020 to early 2021. We statistically examined daily water supply volume, pressure, and pipe failures to detect abnormal changes. We also analyzed pipe failure rates based on different characteristics to identify which pipes are most vulnerable to cold wave damage. Understanding the winter cold wave's effects can help water companies prioritize maintenance on aging pipes before such events, reducing damage and improving service. This research adds to the understanding of climate change's impact on urban infrastructure and provides valuable insights for global water companies to optimize their maintenance strategies.

Research on Failure Pressure Prediction of Water Supply Pipe Based on GA-BP Neural Network

The water supply pipeline is regarded as the “lifeline” of the city. In recent years, pipeline accidents caused by aging and other factors are common and have caused large economic losses. Therefore, in order to avoid large economic losses, it is necessary to analyze the failure prediction of pipelines so that the pipelines that are going to fail can be replaced in a timely manner. In this paper, we propose a method for predicting the failure pressure of pipelines, i.e., a genetic algorithm was used to optimize the weights and thresholds of a BP neural network. The first step was to determine the topology of the neural network and the number of input and output variables. The second step was to optimize the weights and thresholds initially set for the back propagation neural network using a genetic algorithm. Finally, the optimized back-propagation neural network was used to simulate and predict pipeline failures. It was proved by examples that compared with the separate back propagation neural network model and the optimized and trained genetic algorithm-back propagation neural network, the model performed better in simulation prediction, and the prediction accuracy could reach up to 91%, whereas the unoptimized back propagation neural network model could only reach 85%. It is feasible to apply this model for fault prediction of pipelines.

LSTM-Autoencoder Based Detection of Time-Series Noise Signals for Water Supply and Sewer Pipe Leakages

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.

Optimization of water supply parameters for enhanced thermal uniformity in aquaculture ponds under varied working conditions: An experimental study

Aquaculture ponds are critical for the successful rearing of fish larvae, and achieving consistent temperature distribution within these systems is essential for optimal growth conditions. This study explores methods for precise temperature regulation on both the water and atmospheric sides of the pond ecosystem. Based on the original design, systematic changes were made to parameters such as water supply pipe layout, bend angles, perforation rates, and working conditions. Metrics including average temperature, average temperature difference, and extreme temperature difference were utilized to extensively discuss the impacts of these parameters. Through this, temperature distributions across five distinct water supply layouts were analyzed, and the impacts of four different bending angles and perforation rates were evaluated using optimized configurations. Our findings demonstrate that a water supply layout radius of 2000 mm, coupled with a 60° bending angle and a 25 % perforation rate, increased overall temperature uniformity in the pond by 5 %. Additionally, seasonal variations significantly impact temperature distribution in ponds, particularly with different extreme temperature differences observed in winter and summer. Compared to the transitional season and summer, the average temperature difference in the pond during winter decreased by 30 % and 45 %, respectively. It was further revealed that winter conditions naturally yield more uniform water-side temperatures, making seasonal fluctuations irrelevant in determining optimal perforation rates. After the implementation of a water agitator, the average extreme temperature difference decreased from 0.6 K to 0.52 K. In the shallow water layer, the water agitator reduced the extreme temperature difference in the pond by 26 %. The use of water agitators has enhanced thermal uniformity in ponds, thereby improving the growth environment for fish larvae and providing valuable insights for environmental management in aquaculture.

Optimization of water supply parameters for enhanced thermal uniformity in aquaculture ponds: An experimental study based on orthogonal experimental design

The temperature distribution in aquaculture ponds plays a crucial role in the rearing of fish larvae. To achieve a more uniform temperature distribution in the pond and alleviate the problem of thermal stratification, precise control of pond temperature is essential. A recirculating aquaculture pond was taken as the test object. Single-factor experiments and orthogonal experiments were conducted to comprehensively test the aquaculture pond's water supply pipe layout, bend angle, perforation rate, and environmental conditions. Three evaluation indicators were used to analyze the temperature distribution of the aquaculture pond under various water supply pipe structures, leading to the identification of optimal structural configurations. The optimal structure I, obtained from single-factor experiments, was determined to be 2.5 m, 50 %, and 60°, while the optimal structure II, derived from orthogonal experiments, was 1.25 m, 75 %, and 30°. Both optimized structures exhibited significant temperature fluctuations in the pond during the summer season. However, Structure II demonstrated the lowest average temperature difference in the winter season, indicating its superior adaptability during winter. Moreover, Structure II could provide higher temperatures for shallow areas with depths greater than 600 mm, making it more suitable for fish larvae cultivation. Additionally, local devices effectively decreased temperature variations by 17.5 % within the pond. Furthermore, energy consumption output was evaluated for different operational conditions. The results showed that Structure II had the lowest energy consumption output during the summer season. In contrast, during the winter season, the energy consumption output increased by approximately 12 %, indicating significant energy-saving potential in aquaculture ponds during winter.

Burst failure analysis of PVC-UH pipes with axial surface crack based on multiple methodologies

High-performance unplasticized polyvinyl chloride (PVC-UH) offers superior strength and performance compared to PVC, making it a common choice for municipal water supply pipelines. Cracks in PVC-UH pipes are challenging to prevent throughout the entire production and maintenance process. Precise and applicable failure assessment and residual bearing capacity calculation methodology are crucial for ensuring the safe operation and maintenance of PVC-UH municipal water supply pipes. To this end, this paper conducted material uniaxial tensile tests, fracture toughness tests, and pipe burst tests. The study determined the true stress–strain relationship, fracture toughness, burst pressure, and fracture morphology of PVC-UH pipes through testing. Failure pressures of cracked PVC-UH pipes were forecasted using different methodologies, and their accuracy and applicability were evaluated by comparing predicted values with the results of bursting tests. Two calculation methods for determining the failure pressure of pipelines with an axial outer surface crack are proposed based on plastic deformation, damage factor, and fracture mechanics theory. These proposed calculation methods are compared against current methods for determining the failure pressure of pipelines with crack defects, highlighting the higher accuracy of the methods introduced in this paper. The research results can serve as a reference for selecting failure assessment methods for PVC-UH pipelines. Additionally, the proposed calculation methods can accurately and rapidly predict the failure pressure of pipelines with identified axial surface crack sizes, providing technical support for engineering safety assessments of PVC-UH pipelines.

Identification of defects on the inner wall of water supply pipes based on the optimized residual network

ABSTRACT The urban water supply network is part of the infrastructure that sustains the economic and social functions of cities and regions. Timely inspection and maintenance of the network can effectively reduce resource wastage and prevent accidents. Traditional manual detection methods are inefficient and can be based on subjective judgments. A classification model based on an improved ResNet34 network has been proposed to classify and detect various types of corrosion on the inner walls of pipes under challenging conditions. The introduction of the attention mechanism and multi-scale feature fusion modules further improved the model's effectiveness in classifying defects within the inner walls of pipes. The model can detect various types of pipeline corrosion with a detection accuracy of 98.61%. This accuracy is significantly superior to that achieved with traditional models such as ResNet34, AlexNet, MobileNet, and VGGNet.

Remote Detection of Leakages from a Compromised Buried Water Supply Pipe through Geophysical Measurements

The continuous drastic loss of stored water at a private household presumed to be caused by leakage(s) was subjected to geophysical investigations with a view to delineating the source(s) of the leakage(s). The Spontaneous Potential (SP) and Electrical Resistivity (ER) methods were deployed for the study. Measurements were taken along four (4) traverses at two intervals – firstly when the water supply valve from the overhead storage tank was closed and secondly when it was opened. The Total Field array was adopted for SP measurements with constant station separation of 0.5 m. ER measurements were taken via the Wenner array with electrode spacing (a) varied with an interval of 0.5 m from 0.5 m to 1.5 m. SP data were presented as profiles and maps while ER data were presented as 3-D resistivity depth stacks. SP values varied from -100 mV to 350 mV during the two measurement periods. ER values also varied from 100 ohm.m to 1200 ohm.m during the closed valve period and 100 ohm.m to 900 ohm.m during the opened valve period. During the closed valve period, pipeline routes were interpreted as manifesting oval-shaped high potential anomalies with central linear trend on the SP map; and as linearly-trending high resistivity intrusion within low resistivities on resistivity maps. The disparities between the results of closed valve and opened valve measurements were pointers to leakage-induced inhomogeneity in the subsurface. The diminished high potential SP anomaly and the anomalously low resistivity specks within linearly-trending high resistivity values were regarded as the source of leakage.

Experimental study of a leakage location method based on plug flow mass transfer characteristics

Leaks in water supply pipes pose a threat to water security. In order to save labor investment in pipeline leak location and to find a method to obtain the leak location by calculating upstream and downstream related data, an experimental study was conducted to investigate the plug flow mass transfer characteristics in horizontal pipelines. The results show that the addition of carbon dioxide gas can better detect the occurrence of small area ruptures in the pipeline. The translational velocity equation for elongated bubbles has better accuracy for both the insoluble gas air and the slightly soluble gas carbon dioxide. The local volumetric mass transfer coefficient shows a better linear relationship with the residual gas volume. The iterative equation derived from such a law can effectively predict the distribution of carbon dioxide concentrations in the pipeline. The study shows that the iterative equation, combined with the carbon dioxide concentration at a point downstream and the bubble translation velocity, can make a good localization judgment of the pipeline rupture point.

A Study on the Development of a Water Supply Pipe Network Optimal Operation Program through Minimum Hydraulic Gradient Evaluation

A Study on the Development of a Water Supply Pipe Network Optimal Operation Program through Minimum Hydraulic Gradient Evaluation

Analysis of Municipal Water Supply and Drainage Pipe Design Technology

The quality and safety of residents’ water rely heavily on the design of municipal water supply and drainage pipes. Therefore, this paper aims to enhance the optimization of municipal water supply and drainage pipe design by focusing on design requirements, principles, and key elements. Drawing from relevant design optimization experiences, technology advancements, and optimization measures, the research will analyze and consolidate the essential aspects of municipal water supply and drainage pipe design. The goal is to fundamentally elevate the quality standards of these designs, ensuring they meet the criteria for engineering project excellence. Through this comprehensive approach, we aim to contribute to the improvement and sustainability of water supply and drainage systems, safeguarding the well-being of residents.

Geophysical Self-Potential Investigation to Detect Buried Water Supply Pipe Location in Kirkuk City-Northern Iraq

Geophysical Self-Potential Investigation to Detect Buried Water Supply Pipe Location in Kirkuk City-Northern Iraq

Selection of Water Transmission Method and Analysis of Pipe Network Zoning in Municipal Water Supply and Drainage Design

With the acceleration of urbanization, the demand for water supply and drainage pipe networks has increased significantly. In the planning of urban construction, it is necessary to optimize the design of the water supply and drainage system pipe network to effectively save energy while providing residents with more accessible water resources. Therefore, the municipal water supply and drainage system and the water transmission methods should be designed according to the geographical conditions of the city. In this paper, we mainly analyze the design of municipal water supply and drainage systems and the selection of water transmission methods. Besides, the optimization of the water supply and drainage network zoning process and pipe network maintenance is also discussed, so as to provide a reference for municipal water supply and drainage work.

Fractal Characteristics of Water Outflows on the Soil Surface after a Pipe Failure

Water pipe failures result in real water losses in the form of water outflowing into the porous medium, such as the surrounding soil. Such an outflow may result in the creation of suffosion holes. The appropriate management of the water supply network may contribute to reducing the number of failures, but due to their random nature, it is not possible to completely eliminate them. Therefore, alternative solutions are being sought to reduce the effects of the failures. This article presents a fragment of the results from a broader scope of the research, which attempted to determine the outflow zone in relation to the fractal characteristics of water outflows. The research included the analysis of the actual geometric structures created by the water outflows, which were simplified into linear structures using isometric transformations. The structures were analyzed in terms of the parameters characterizing them, including their fractal dimensions. As a result, it was found that there was no relationship between the analyzed fractal parameters and the leakage area or hydraulic pressure in the water pipe. However, the influence of the number of points forming each linear structure on the analyzed parameters was shown. This allowed for the determination of further research aimed at estimating the size of the water outflow zone after the unsealing of an underground water supply pipe.

Effects of Internal Pressure on Urban Water Supply Pipeline Leakage-Induced Soil Subsidence Mechanisms

After the rupture of pressurized water supply pipes in urban underground areas, seepage-induced ground subsidence becomes a severe geological hazard. Understanding the permeation and diffusion patterns of water in soil is crucial for deciphering the mechanisms underlying soil settlement and damage. Notably, the pressure within water supply pipes significantly influences the settlement and damage of the soil. Therefore, this study simulated experiments on soil settlement and damage caused by water seepage from a preexisting damaged pipeline under various internal pipe pressure conditions using an indoor model apparatus. The results indicate that the internal pressure of the pipe significantly influences the settlement of the soil. High-pressure seepage causes noticeable erosion in the soil, forming cavities within it. In contrast, low-pressure seepage results in water diffusing in an ellipsoidal pattern, leading to the formation of circular surface cracks. The degree of surface settlement increases with higher pipe pressure. The onset of subsidence at a specific point on the ground is not directly related to whether the moistening front within the soil has reached that point horizontally. Instead, it is associated with the moisture content below the subsidence point within the soil. The research results further illustrate the water diffusion and moisture content increase processes after water seepage from pipes with different pressures, revealing the influence of pipe pressure on the degree and form of soil settlement damage and clarifying the relationship between water diffusion and settlement in the soil.

Enhancing Sustainability in Italian Water Supply Pipes through Life Cycle Analysis

The primary concern regarding the sustainability of the urban water cycle remains the performance of water supply systems. This, in turn, is determined by the functionality and sustainability of the system components, such as the pipe networks, pumps, and other appurtenances, which must be analyzed from an environmental perspective. The aim of the present study is to analyze the sustainability of two different types of water supply pipe materials that are commonly used, polyvinyl chloride and high-density polyethylene, using a comparative Life Cycle Analysis methodology. The functional unit was established in accordance with the water supply system that serves an Italian metropolitan city with a dimension of 9240 km, as one meter of water supply infrastructure, with 40 years as a life span. A cradle-to-gate analysis was conducted, starting from the production phase of the water pipelines to the maintenance phase, excluding the end of life and disposal phases. The chosen methodology was CML, justified by the fact that the results are more understandable and reproducible. Results comparison revealed a higher environmental impact during the production phase, while the maintenance phase had a very low impact. Notably, PVC pipe in comparison with HDPE material had a higher impact, except in two categories of impact: abiotic depletion and photochemical oxidation. The study contributes to the future development of alternative approaches for sustainable and eco-efficient water supply infrastructure designs and materials.

Monitoring domestic water consumption: a comparative study of model-based and data-driven end-use disaggregation methods

ABSTRACT Monitoring the water usage of different appliances and informing consumers about it has been shown to have an impact on their behavior toward drinking water conservation. The most practical and cost-effective way to accomplish this is through a non-intrusive approach, that locally analyzes data received from a flow sensor at the main water supply pipe of a household. In this work, we present two different methods addressing the challenges of disaggregating end-use consumption and classifying consumption events. The first method is model-based (MB) and uses a combination of dynamic time wrapping and statistical bounds to analyze four water end-use characteristics. The second, learning-based (LB) method is data-driven and formulates the problem as a time-series classification problem without relying on a priori identification of events. We perform an extensive computational study that includes a comparison between an MB and an LB method, as well as an experimental study to demonstrate the application of the LB method on an edge computing device. Both methods achieve similar F1 scores (LB: 71.73%, MB: 71.04%) with the LB being more precise. The embedded LB method achieves a slightly higher score (72.01%) while enhancing on-site real-time processing, improving security and privacy and enabling cost savings.

A review: Exposure to bisphenol a analogues in non-human primates as a potential cause of endometriosis

Introduction: Bisphenol A is a synthetic compound widely used in the production of polycarbonate plastics and epoxy resins worldwide. As an environmental toxin, it has been reported in plastic equipment and utensils, water bottles and bottle tops, water supply pipes and epoxy resins that coat most of the metal food cans. It is a known endocrine-disrupting chemical and has been progressively replaced by its derivatives including bisphenol S, bisphenol F, bisphenol E, bisphenol AF, bisphenol B and tetramethyl bisphenol F. Bisphenol A and its analogues can bind to estrogen receptors and trigger multiple cellular responses at the organism level. Methods: A comprehensive literature review was done utilising electronic databases of PubMed, Google Scholar, Hinari, Connected papers and Science Direct from 1991 onwards. The articles were only included if they reported original relevant research and were limited to articles written in English. Results: Animal models, including non-human primates, have been used to study their effects on the endocrine system. Its endocrine disruption activity is reported to be the most studied effect in reproductive biology indicating that it may potentially cause endometriosis in females. Though non-human primates are closely related to humans, limited data exists on their associations between Bisphenol A exposure and its analogues and the pathophysiology of endometriosis. Conclusion: Given the current multifaceted knowledge/theory on endometriosis etiology, there is a strong necessity to conduct further biomedical research that utilises non-human primates to study the link between endocrine-disrupting chemicals and its effects on endometriosis.

Multi-leakage localization in water supply pipes based on convolutional blind source separation

In acoustic-based methods for water pipeline leak localization, there are few studies on complex multi-leak localization since these sources mix with and affect each other during propagation. In this paper, a novel multi-leak localization method based on the convolutional blind source separation (CBSS) algorithm is proposed, in which the time delays are estimated by the quadrature filter of the demixing matrix or the cross-correlation function between the separated signals and the measured signals, and then the leakage locations are found by linear localization formula. In theory, this paper analyzes the basic principle of the algorithm for locating multiple leaks. In simulation results, the algorithm’s feasibility is verified. In addition, it is obtained that the location distribution of the leakage sources will affect the location of the peak of the delay, and that strong noise will reduce the applicability of the algorithm. In prototype experiments, the algorithm is verified to locate the leaks effectively. This paper is the first to apply CBSS to multi-leakage localization, providing a feasible solution to this complex problem.