Water Leakage Research Articles

Application of Network Reconstruction Algorithm to Compute Maximum Flow for Water Supply Network: A Case Study of the City of Bulawayo, Zimbabwe

Determining the maximum flow value in Water Supply Networks (WSN) is a common problem that is being faced by many cities during and after designing of WSN. In this article, the network reconstruction (NR) algorithm is applied to compute the maximum flow value for the city’s WSN based on the actual data. The city of Bulawayo has been selected for the following reasons, availability of research data, the city is facing severe water shedding and several studies have focused only on other issues such as alternative water sources, leakage detection and demand forecasting. The goal of this study is to determine the maximum flow value from the sources to the reservoirs. The results have revealed that the computed maximum flow value is within the estimated range of 110,000 cubic meters to 190,000 cubic meters. Dam sensitivity analysis were considered to determine the sources to give maintenance priority before the rain season. Several recommendations were suggested to improve the water supply situation.

A multi-domain model for microcirculation in optic nerve: Blood flow and oxygen transport

Microcirculation of blood and transport of oxygen play important roles in the biological function of the optic nerve and its diseases. This work develops a multi-domain model for the optic nerve, that includes important biological structures and various physical mechanisms in blood flow and oxygen delivery. The two vascular networks are treated as five domains in the same geometric region, with various exchanges among them (such as Darcy’s law for fluid flow) and with the tissue domain (such as water leak, diffusion). The numerical results of the coupled model for a uniform case of vasculature distribution show mechanisms and scales consistent with literature and intuition. The effects of various important model parameters (relevant to pathological conditions) are investigated to provide insights into the possible implications. The vasculature distribution (resting volume fractions here) has significant impacts on the blood circulation and could lead to insufficient blood supply in certain local regions and thereby affect the delivery of oxygen. The water leak across the capillary wall will have nontrivial effects after the leak coefficients pass a threshold. The pulsatile arterial pressure leads to expected pulsatile patterns and stable spatial profiles, and the uniform case is almost the averaged version of pulsatile case. The effects of viscosity, the stiffness of blood vessel wall, oxygen demand, etc. have also been analyzed. The framework can be extended to include ionic transport or to study the retina when more biological structural information is available.

Development and characterization of log periodic feedline based filter for water leakage detection in size invariant PVC pipes

In this proposed work, water leakage detection in Polyvinyl chloride (PVC) pipes has been investigated using a ring filter connected to log-periodic feedlines (LPF). The proposed filter has a well-structured ring design to adjust the PVC pipes and operates between 0.3 GHz & 0.7 GHz. Using a signal generator & analyzer, attenuation measurements are obtained to analyze the impact of water leakage. PVC pipes with varying diameters (3 inches, 2 inches, 1.5 inches, & 1 inch) are connected with water stoppers to control the water flow during experiments. The leak is contained within a plastic tub to make measurements easier. Results show a good connection between attenuation & water level for all pipe diameters, supporting the LPF-based ring filter’s effectiveness as a leakage detector. An analogous circuit model is created to evaluate the filter’s performance further. At the same time, the resonant parameters, such as Q-factors & resonant frequencies, are retrieved from S21 magnitude measurements in the operating frequency range. The proposed methodology is shown to be accurate & reliable, offering significant potential for water leakage detection in PVC pipe systems. By accurately detecting water leakage, this technology enables prompt repairs, reducing water loss & associated costs, enhancing water infrastructure, and promoting sustainable water management.

Development and experimental testing of an innovative nondestructive thermal sensor utilizing the thermal interrogation method for detecting leakage in water plastic pipes

Leak detection in water pipelines is still an important issue in real-world industrial systems. Thus, a new nondestructive thermal sensor design based on the thermal interrogation method has been developed to detect and estimate the real-time leaks in water plastic pipes without environmental interference. The proposed thermal interrogation method utilizes a combination of heat flux and temperature measurements on the upstream and downstream outside plastic pipe surfaces. These measurements are obtained by using heat flux sensors and thermocouples that are covered by thin-film polyimide electric heaters. The interrogation method approach delivers that at constant input heat flux, the difference in sensor temperature values is dependent on the leakage volume flow rates. The sensor was tested over a range of water leakage volume flow rate from 0.1 m3/h to 1.3 m3/h and a range of water temperature from 21 °C to 25 °C. The water leakage volume flow rates were correlated to the difference in temperature values between the upstream and downstream sensors. The measurement results reveal that this sensor can be used to detect and estimate the real-time water leakage volume flow rate with high accuracy and repeatability for plastic pipes.

IOT Enabled Smart Washroom

While progress is undoubtedly being made in the cutting-edge globe, our country's cleanliness is in jeopardy. The purpose of this paper is to supply hygienic and clean restrooms. Every public restroom ought to be hygienic and spotless. The government of our nation launched the "Swachh Bharat" (Clean India) program. One of the goals of the Clean India initiative is to maintain uncontaminated toilets. This study has the potential to support the clean India initiative. It may eventually demonstrate the major role in the Clean India Plan. The smart bathroom system integrates features like an automatic water tap for hands-free operation, water leakage detection to prevent waste, and an exhaust fan with odour sensing for improved air quality. It dispenses auto air freshener based on bad smell detection linked to overall air quality monitoring. Users can control and monitor these functions through a mobile app. Additionally, an auto-cleaning mechanism activates after every 10 entries to ensure a hygienic space. This system aims to enhance efficiency and convenience in the bathroom environment.

Leak detection and localization in underground water supply system using thermal imaging and geophone signals through machine learning

The underground water pipeline system is a crucial infrastructure that largely remains out of sight. However, it is the source of a clean and uninterrupted flow of water for our everyday lives. Various factors, including corrosion, material degradation, ground movement, and improper maintenance, cause pipe leaks, a silent crisis that causes an estimated 39 billion dollars of loss every year. Prompt leakage detection and localization can help reduce the loss. This research investigates the potential of two machine learning models as supporting tools for surveying extensive areas to identify and pinpoint the location of underground leaks. The presented combined approach ensures the speed and accuracy of the leakage survey. The first machine learning model is a hybrid ML model that employs thermal imaging to identify subterranean water leakage. It relies on detecting thermal anomalies and distinctive signatures associated with water leakage to identify and locate underground water leakage. The developed model can detect up to 750 mm underground leakage with 95.20 % accuracy. The second model uses binaural audio from geophones to localize the leakage position. The model utilizes interaural time difference and interaural phase difference for localization purposes, and the 1D-CNN network delivers an angle in twenty-degree increments with an accuracy of 88.19 %. Large-scale implementation of the proposed model could be a powerful catalyst to reduce water loss in the water supply system.

Rheology of automotive adhesives during dispensing: A direct comparison of epoxy and rubber based systems via drag and pressure driven flows

Construction of vehicles requires adhesive dispensing for body-in-white assembly, hemming of closure panels, decking of windshields and the manufacture of battery packs. Knowledge of the rheological properties of adhesives applied using common dispensing systems is important for optimization of dispensing and application conditions. However, flow behavior of adhesives at shear rates used in dispensing is not well understood. Therefore, this study combines parallel plate and capillary rheology techniques to directly compare the rheological properties of an epoxy structural adhesive used in hemming applications and a rubber ‘topical sealer’ used to seal water leak paths across the range of shear rates observed in dispensing. Shear viscosity (η) and complex viscosity (η*) master curves were created from time-temperature-superposition (TTS) of steady shear and dynamic oscillatory data. Both adhesives did not follow the Cox-Merz rule. It was found that the Carreau-Yasuda model fit the steady shear viscosity master curve of the epoxy structural adhesive, while a simpler power law model fit the steady shear viscosity master curve of the rubber topical sealer. An inexpensive capillary rheometer was developed to simulate the adhesive dispensing process. Viscosity data was corrected for entrance pressure losses and a non-Newtonian flow front using Bagley and Weissenberg-Rabinowitsch corrections, respectively. It was observed that complex viscosity master curves better predicted viscosity during dispensing, as compared to steady shear viscosity master curves. Linear stress ramp measurements showed that the adhesives have widely different yield stresses, while the capillary rheometry measurements showed they have similar viscosities during dispensing. Furthermore, the capillary rheometer ‘shot meter’ pressures were related to the apparent and doubly corrected viscosity values through power law functions. A new quality control method based on the capillary rheology data is proposed.

A 3D-printed condom intrauterine balloon tamponade: Design, prototyping, and technical validation.

Post-partum haemorrhage is among the main causes of (preventable) mortality for women in low-resource settings (LRSs), where, in 2017, the mortality ratio was 462 out of every 100 000 live births, over 10 times higher than for high-resource settings. There are different treatments available for post-partum haemorrhage. The intrauterine balloon tamponade is a medical device that proved to be a simple and cost-effective approach. Currently, there are several balloon tamponades available, with different design and working principles. However, all these devices were designed for high-resource settings, presenting several aspects that could be inappropriate for many lower-income countries. This paper presents the results of a preclinical study aiming at informing the design, prototyping and validation of a 3D-printed intrauterine balloon tamponade concept, contributing towards the United Nation's Sustainable Development Goal 3: Good health and Well-being. Frugal engineering concepts and contextualised design techniques were applied throughout, to define the design requirements and specifications. The performance of the final prototype was validated against the requirements of the UK National Health System (NHS) technical guidelines and relevant literature, measuring the water leak and pressure drop over time, both open air and in a approximate uterus model. The resulting prototype is made up of six components, some of which are easy to retrieve, namely a water bottle, a silicone tube and an ordinary condom, while others can be manufactured locally using 3D printers, namely a modified bottle cap, a flow stopper and a valve for holding the condom in place. Validation testing bore promising results with no water or pressure leak open air, and minimal leaks in the approximate uterus model. This demonstrates that the 3D printed condom-based intrauterine balloon tamponade is performing well against the requirements and, when compared to the state of the art, it could be a more appropriate and more resilient solution to low-resource settings, as it bypasses the challenges in the supply of consumables and presents a greener option based on circular economy.

The practical aspects of remote land sensing study of the causes of water penetration on ground hydraulic structures

This article is devoted to the application of remote sensing in the context of the natural and technical geosystem of the Dniester PSPP. The main emphasis is placed on the use of geographic information systems (GIS) and thermographic data to determine the factors that may cause abnormal thermal load on hydraulic structures. The study is aimed at identifying and analysing temperature gradients that may influence the occurrence of thermal anomalies. The study is aimed at identifying potential causes, mechanisms and factors affecting water manifestations. The subject of the analysis is also the relationship between the temperature gradient on the surface of structures and the presence of water leakage, as well as the impact of temperature on geological, hydrological and engineering systems of the structure. The analysis process is based on the interpretation of thermographic data reflecting the local heating of the surface of the hydraulic structure and the geotechnical characteristics of the soils, taking into account the design features of the hydraulic structure The research provides valuable insights that can be used to optimise the design and construction of earthen dams. Analysis of thermal processes is an important step in understanding and predicting their impact on the geological structure and hydrogeological properties of the environment. Man-made soils placed in the protective layers of a dam are subject to significant uneven heating. Keywords: geoecology, constructive geography, geosystems, river-basin systems, river-valley landscapes, river natural and technical systems, landscape technical systems, landscape engineering systems, GIS technologies, Dniester PSPP, remote sensing, thermo map, GNSS.

Structure and crystallization behavior of Na2O–ZrO2–SiO2–P2O5 glass for solid-state electrolyte separation

Glass ceramics containing Na super-ionic conductor (NASICON) crystals are promising candidates for solid-state electrolyte separators in aqueous sodium ion batteries due to their high ion conductivity, water stability, and productivity. Our objective was to fabricate a glass-ceramic separator by crystallizing a NASICON phase within the glass via heat-treatment. We conducted a detailed investigation into the structural evolution of the glass and the crystallization morphology. Upon heat-treatment, Si units polymerized to form an island-like phase, while P contributed to increasing non-bridging O to form a sea-like phase during droplet phase separation; subsequently, the Na2Zr2SiP2O12 crystalline phase formed. The remaining glass comprised Q4 units of Si in the island-like phase, and Q1 and Q2 units of P in the sea-like phase. The ionic conductivity of the sample increased by crystallization up to 5.4 × 10–5 S⋅cm –1 at 300 K. Furthermore, the water leakage tests showed that both the glass and glass-ceramics exhibited low leakages.

Intelligent Detection of Tunnel Leakage Based on Improved Mask R-CNN

The instance segmentation model based on deep learning has addressed the challenges in intelligently detecting water leakage in shield tunneling. Due to the limited generalization ability of the baseline model, occurrences of missed detections, false detections, and repeated detections are encountered during the actual detection of tunnel water leakage. This paper adopts Mask R-CNN as the baseline model and introduces a mask cascade strategy to enhance the quality of positive samples. Additionally, the backbone network in the model is replaced with RegNetX to enlarge the model’s receptive field, and MDConv is introduced to enhance the model’s feature extraction capability in the edge receptive field region. Building upon these improvements, the proposed model is named Cascade-MRegNetX. The backbone network MRegNetX features a symmetrical block structure, which, when combined with deformable convolutions, greatly assists in extracting edge features from corresponding regions. During the dataset preprocessing stage, we augment the dataset through image rotation and classification, thereby improving both the quality and quantity of samples. Finally, by leveraging pre-trained models through transfer learning, we enhance the robustness of the target model. This model can effectively extract features from water leakage areas of different scales or deformations. Through instance segmentation experiments conducted on a dataset comprising 766 images of tunnel water leakage, the experimental results demonstrate that the improved model achieves higher precision in tunnel water leakage mask detection. Through these enhancements, the detection effectiveness, feature extraction capability, and generalization ability of the baseline model are improved. The improved Cascade-MRegNetX model achieves respective improvements of 7.7%, 2.8%, and 10.4% in terms of AP, AP0.5, and AP0.75 compared to the existing Cascade Mask R-CNN model.

A novel indicator for equivalent mean air temperature within the tunnel considering time-varying ventilation wind speeds: Calculation and application

The study examines the coupling effect between air temperature and time-varying ventilation wind speeds within the tunnel, abstracting their influence on tunnel coldness. This investigation introduces a novel indicator—the equivalent mean air temperature within the tunnel—derived through fluid dynamics and heat transfer theories based on the principle of equivalent convective heat transfer. Case studies using the Xinjiaodong Tunnel and BSLL Tunnel illustrate the indicator's applications, including optimal anti-freezing axis identification, insulation layer thickness design, and active-controlled ventilation implementation. The optimal anti-freezing axis orientation angle for the Xinjiaodong Tunnel entrance section is 133.3°, deviating significantly by 160.8° from the actual axis, indicating a lower level of equivalent mean annual air temperature (5.5 °C) at the entrance section. This underscores the necessity to reinforce anti-freezing measures specifically at the entrance section of the Xinjiaodong Tunnel. Determining a 10 cm-thick insulation layer requirement at the Xinjiaodong Tunnel entrance section based on the equivalent mean air temperature. Through on-site investigation and published findings, it was observed that a 5 cm-thick insulation layer failed to prevent freezing, resulting in water leakage and ice formation on the lining, thus validating the calculation results. The BSLL Tunnel requires an insulation layer thickness exceeding 10 cm based on the equivalent mean air temperature, necessitating the implementation of active-controlled ventilation. Calculation results reveal that, with active-controlled ventilation wind speeds increasing from 1 m/s to 4 m/s at a temperature threshold of 4 °C, the equivalent mean air temperature during cumulative negative temperature periods within the BSLL Tunnel rises sharply from 1.0 °C to 2.7 °C. These findings demonstrate that the equivalent mean air temperature not only guides the identification of optimal anti-freezing axis, the design of insulation layer thickness considering time-varying ventilation wind speeds, and the implementation of active-controlled ventilation but also provides new methods and technologies for anti-freezing design in cold-region tunnels.

Deep learning based water leakage detection for shield tunnel lining

Deep learning based water leakage detection for shield tunnel lining

Polarity Crossing Correlation to Detect Underground Water Leaks Using Pressure Drop and Hydrophones

Polarity Crossing Correlation to Detect Underground Water Leaks Using Pressure Drop and Hydrophones

Vibration-based water leakage detection system for public open data platforms

Vibration-based water leakage detection system for public open data platforms

Nonlinear Augmented Reality Enabled Smart Water Leakage Identification and Infrastructure Management of Pipeline System

Nonlinear Augmented Reality Enabled Smart Water Leakage Identification and Infrastructure Management of Pipeline System

Numerical Simulation Study Considering Discontinuous Longitudinal Joints in Soft Soil under Symmetric Loading

In shield tunneling, the joint is one of the most vulnerable parts of the segmental lining. Opening of the joint reduces the overall stiffness of the ring, leading to structural damage and issues such as water leakage. Currently, the Winkler method is commonly used to calculate structural deformation, simplifying the interaction between segments and soil as radial and tangential Winkler springs. However, when introducing connection springs or reduction factors to simulate the joint stiffness of segments, the challenge lies in determining the reduction coefficient and the stiffness of the springs. Currently, the hyperstatic reflection method cannot simulate the discontinuity effect at the connection of the tunnel segments, while the state space method overlooks the nonlinear interaction between the tunnel and the soil. Therefore, this paper proposes a numerical simulation method considering the interaction between the tunnel and the soil, which is subjected to compression rather than tension, and the discontinuity of the joints between the segments. The model structure and external load are symmetrical, resulting in symmetrical calculation results. This method is based on the soft soil layers and shield tunnel structures of the Shanghai Metro, and the applicability of the model is verified through deformation calculations using three-dimensional laser scanning point clouds of sections from the Shanghai Metro Line 5. When the subgrade reaction coefficient is 5000 kN/m3, the model can effectively simulate the deformation of operational tunnels. By adjusting the bending stiffness of individual connection springs, we investigate the influence of bending stiffness reduction on the bending moment, radial displacement, and rotational displacement of the ring. The results indicate that a decrease in joint bending stiffness significantly affects the mechanical response of the ring, and the extent and degree of this influence are correlated with the joint position and the magnitude of joint bending stiffness.

Time-varying compressive properties and constitutive model of EPDM rubber materials for tunnel gasketed joint

The stress relaxation of ethylene propylene diene monomer (EPDM) rubber material in a compressed state significantly increases the risk of water leakage at tunnel precast segmental joints. Additionally, EPDM rubber gaskets typically experience a complex precompression strain state, further complicating the prediction of long-term stress relaxation. Therefore, it is imperative to propose a novel constitutive model that realistically reflects the stress relaxation of rubber with arbitrary precompression strain, providing a reference for the long-term waterproof design of shield tunnels. In this study, the time-varying properties of EPDM rubber at material level were studied in detail. At first, a comprehensive set of accelerated aging tests were conducted on EPDM rubber samples with varying precompression strains. The hardening effect of rubber without precompression and the stress relaxation effect of rubber with precompression were explored. The time-varying law and mechanism governing rubber properties under these two effects were analyzed. Subsequently, a conversion relationship between the EPDM rubber test conditions and the actual service time was established. The predicted hardening coefficient for uncompressed EPDM after 100 years is 1.468, whereas the relaxation coefficient for compressed EPDM is 0.359. Comparative analysis revealed that the compression set index do not consider the beneficial effects of hardening, resulting in a 54.1% overestimation of the design water pressure. Finally, the analytical study on the constitutive model of EPDM rubber material was carried out. The error in compression curve for unaged sample obtained from empirical formulas exceeded three times that of the analytical model, underscoring the need to study time-varying constitutive models. An interpolation method was employed to extend the test curve, leading to the development of a new constitutive model that represents the stress relaxation characteristics of EPDM materials under arbitrary precompression strain states. By combining the proposed constitutive model with the timetemperature conversion relationship, the time-varying expressions of the constitutive parameters for relaxation and hardening effects during the service life were derived. In comparison with existing models, the proposed model demonstrates wider applicability, effectively captures the time-varying characteristics of EPDM materials under arbitrary precompression strains, offering an efficient approach for studying the long-term stress relaxation prediction of rubber gaskets in shield tunnels under complex precompression strain states.

Properties and Microstructure of a Cement-Based Capillary Crystalline Waterproofing Grouting Material

Cement grout is traditionally used for treating water leakage distress in tunnels. However, traditional cement grout has the disadvantages of a poor anti-seepage performance, long setting time, and slow strength gain. To this end, a high-performance cement-based capillary crystalline waterproofing (CCCW) grouting material was synthesized using cement, capillary crystalline material, and several admixtures. The influences of the material proportions on the viscosity, bleeding rate, and setting time of the fresh grout, as well as the permeability coefficient of the grouted aggregate and the unconfined compression strength of the hardened grout material, were systematically studied. The mineralogy and microstructure of the CCCW grouting material were examined using X-ray diffraction, industrial computed tomography, and scanning electron microscopy. The results indicated that the capillary crystalline material PNC803 was not suitable for mixing with bentonite, sodium chloride, and triethanolamine in cementitious slurries, but it can produce excellent synergistic effects with sulfate, calcium chloride, and triisopropanolamine. An analysis of the microstructure of the CCCW grouting material showed that the PNC803 and additives can promote the hydration of cement, which yields more hydration products, sealing water passage and filling micro voids and therefore leading to enhanced waterproofing and strengthening effects. These research results could improve the applicability of CCCW material in tunnel engineering.

Indoor Infrastructure Maintenance Framework Using Networked Sensors, Robots, and Augmented Reality Human Interface

Sensing and cognition by homeowners and technicians for home maintenance are prime examples of human–building interaction. Damage, decay, and pest infestation present signals that humans interpret and then act upon to remedy and mitigate. The maintenance cognition process has direct effects on sustainability and economic vitality, as well as the health and well-being of building occupants. While home maintenance practices date back to antiquity, they readily submit to augmentation and improvement with modern technologies. This paper describes the use of networked smart technologies embedded with machine learning (ML) and presented in electronic formats to better inform homeowners and occupants about safety and maintenance issues, as well as recommend courses of remedial action. The demonstrated technologies include robotic sensing in confined areas, LiDAR scans of structural shape and deformation, moisture and gas sensing, water leak detection, network embedded ML, and augmented reality interfaces with multi-user teaming capabilities. The sensor information passes through a private local dynamic network to processors with neural network pattern recognition capabilities to abstract the information, which then feeds to humans through augmented reality and conventional smart device interfaces. This networked sensor system serves as a testbed and demonstrator for home maintenance technologies, for what can be termed Home Maintenance 4.0.