Water Pipeline System Research Articles

Analysis and Research on Flow Characteristics of Hot Water Pipeline System

Based on the CFD numerical simulation method, a pipe model was established to study the internal flow characteristics of two different specifications of hot water pipe system, and the related information of the flow field was obtained, such as the internal pressure, flow velocity and flow rate. The results showed that the smoother the pipeline transition was, the smaller the velocity uniformity coefficient would be, and the higher flow field uniformity means the smaller pressure and velocity fluctuations. Therefore, the pipeline vibration will be smaller, and the flow characteristics are greatly improved.

Comparative Study on Flow Characteristics of Pipeline System Based on CFD

Based on the CFD numerical simulation method, this paper established a pipeline model to study the internal flow characteristics of three different combinations of hot water pipeline systems and thus obtained the flow field information such as pressure, flow rate, and flow rate inside the pipeline. The study results showed that the smoother the pipeline transition, the smaller the velocity uniformity coefficient; the higher the uniformity of the flow field, the smaller the pressure and velocity fluctuations, the smaller the resulting pipeline vibration. Besides, the flow characteristics have been greatly improved.

Na ceste z chudoby a sociálneho vylúčenia? Dostupnosť pitnej vody v rómskych komunitách na východnom Slovensku

Access to fresh water and sanity represent elementary human rights leading to a healthy life and high life quality. Among other features of social exclusion, poor access to basic infrastructure such as drinking water pipelines and public sewage systems may adversely affect human health and cause high risk of epidemics related to poor hygienic conditions. Not surprisingly, communities with low hygienic conditions and poor access to drinking water are often at high risk of spreading Covid-19. In Slovakia, numerous communities of Roma ethnicity have been repeatedly reported to have no or limited access to sewage and drinking water pipeline systems. The principal aim of our paper is to analyse the quality of access to various water sources in Roma communities located in NUTS2 East Slovakia consisting of Prešov and Košice Self-Governing Regions. Our ambition is to show how the level of spatial segregation of Roma communities affects the quality of access to healthy water sources. The database used in the paper allows covering regional and partly also local territorial levels of scope. Specifically, we attempt to show the conditions in the most segregated Roma communities located apart from built-up areas of municipalities with generally poor access to drinking water.

Computational Fluid Dynamics (CFD) simulation of liquid column separation in pipe transients

The present study deals with the computational simulation of transient events of water hammer and column separation in a water pipeline system. Three-dimensional CFD simulations based on the Finite-Volume (FV) approach are performed to predict pressure fluctuations and to visualize liquid column separation/rejoining caused by the sudden closure of a valve located at the upstream end of the pipe. Explanation of vaporous cavitation phenomena is also presented. The Volume of Fluid (VOF) model and Schnerr-Sauer cavitation model are used to describe the multiphase flow and the transient vaporous cavitation, respectively. Moreover, the shear-stress transport (SST) turbulence model is applied to model the Reynolds stresses using the Boussinesq hypothesis. Present results are compared with available experimental and numerical results from the literature. The comparisons show that the present method gives adequate results. Also, the 3D model adopted is deemed physically superior to the existing 1D models as it removes the restriction of the 1D models that vapor cavities, when formed, fill the whole cross-section of the pipe without radial variation. In addition, 1D models are not able to predict the stratification effect due to density variation of the two phases. Consequently, the 3D model can better visualize the phenomenon of liquid column separation/rejoining in pipes than 1D models.

Adaptive Independent Component Analysis–Based Cross-Correlation Techniques along with Empirical Mode Decomposition for Water Pipeline Leakage Localization Utilizing Acousto-Optic Sensors

AbstractThe leak localization in a water pipeline system plays a vital role in pipeline system modeling. The leak location is identified by estimating the time difference between two sensor signals...

Leakage detection in water pipelines using supervised classification of acceleration signals

Loss of treated water through buried pipeline leakage is one of the pressing challenges faced by water utilities across the world. Many current pipeline inspection techniques are ad-hoc in nature and only provide a snapshot status of the system. Although a few embedded sensor-based systems offer promise for continuous monitoring, they are limited in their ability to detect leakages of all magnitudes. Lack of a comprehensive understanding of the pipeline system's structural dynamics and the correlation to leakage detection is a primary challenge. To overcome this challenge, a deep learning algorithm that uses scalogram images of vibration signals collected from accelerometers attached to the pipeline surface is developed and validated in this study. The advantage is that the complex structural features of the water pipeline systems need not be modeled if sufficient leak-based vibration signal data is available for training purposes. A convolutional neural network (CNN) model adapted from a pre-trained AlexNet network is leveraged to demonstrate the proposed approach using vibration data collected from an experimental pipeline test bed. The CNN model is found to be able to detect leakages on polyvinyl chloride (PVC) pipelines with up to 95% accuracy. A maximum accuracy of 98% is observed with acceleration signal data collected from carefully selected locations. The approach presented in this study can be adapted for effective leakage detection in real world scenarios with minimum human intervention.

Spatio-temporal correlations for damages identification and localization in water pipeline systems based on WSNs

Pipeline leakages may conduct large excessive costs for reparation, infrastructure damage combined with environmental pollution. Consequently, the security and maintenance of the pipeline infrastructure are one of the major preoccupations for searchers. The most suitable are these solutions based on wireless sensors networks. However, WSNs are susceptible to noise effect, material defaults and malicious attacks from intruders. Therefore, it is essential to identify potential events like a leak, as well as erroneous and malicious attacks as defected sensors, occurred on the network. For that propose, we have presented a distributed one class classification technique for outliers detection based on WSNs. In addition, we have searched to improve our classifier by using a centered ellipsoidal technique to classify data. Then, we have demonstrated the importance of our improved technique comparing to other classifiers. Likewise, we have investigated the notion of the relationship existing between closed neighboring nodes and the existing correlation between historical observations to identify damages sources. These improvements led to increase the detection accuracy level and decrease the false alarm percentage by respecting WSNs constraints such as energy consumption.

Machine-Learning-Based Leakage-Event Identification for Smart Water Supply Systems

In this article, we are interested in leak identification (LI) for water supply pipelines using transient-wave (pressure) measurement data. This is challenging since water pipeline system conditions are usually uncertain in practice. For instance, the pipeline diameter, the friction factor, and the pipeline shape will vary. The conventional signal propagation model-based LI methods rely on a deterministic system model with perfectly known and fixed-value parameters, which limits their application in general cases. To address this challenge, we design a novel deep neural network (DNN)-based machine learning approach to solve the LI problem. First, we propose a novel fusion-enhanced stochastic optimization algorithm for the DNN training, which can greatly improve the DNN training performance and hence the LI accuracy, without increasing the computational cost. Second, we design a novel convolutional-based pooling network to extract the stable texture feature of transient-wave samples, thus achieving a reliable LI solution against the pipeline system dynamics. It is shown in experiments that, thanks to the above system design, the proposed DNN-based LI method can achieve a failure rate lower than $6\times 10^{-4}$ when the signal-to-noise ratio is 0 dB, which outperforms the conventional LI methods.

IoT based water distribution system

In this paper, we propose an IoT-based water distribution system approach to monitor the level of water in overhead tank, flow rate of water, quantity and leakage of water in a water pipeline system based on the measurements accumulated from the flow meters and as well as proper distribution of the water resource. In urban and rural areas, the manual operation of water distribution system is being replaced. Internet of Things (IoT) technology is implemented to monitor the water distribution system wirelessly and to monitor the wastage of water. The proposed methodology is realized through the use of real-time systems and sensors, where data are collected from individual houses then processed in real-time and finally the gathered information is displayed in the website.

Risk assessment and management in domestic water supply system in Pleiku city – Gia Lai province

Water is essential for maintaining life, ensuring a safe and continuous supply of water, therefore, it should be given the priority for concerns. Developing countries often face a number of problems with domestic water supply systems such as treatment plants with old technologies, degraded equipment leading to inefficient treatment, and a network of degraded piping, which could cause re-pollution of treated water during transport. Pleiku city, which is located in the Central Highlands of Vietnam, has built two treatment plants and a network of water supply pipelines in the core area. An analysis of the current state of the water supply system including water supply, treatment plant and pipeline system helps identify existing problems in the system. Through mixed methods, hazards or hazardous events are identified as a basis for risk assessment by using semi – quantitative method to assess raw risk and residual risk for each hazard. Priority risks are identified to focus on proposing the possible solutions that will improve the performance and management of domestic water supply systems.

Kernelized technique for outliers detection to monitoring water pipeline based on WSNs

Currently, the technology for sensing and control has become the potential for significant advances not only in science and business but equally important on a range of industrial applications. In addition to reducing costs and increasing efficiencies for monitoring systems, Wireless Sensor Networking (WSN) is expected to bring consumers a new generation of conveniences. However, there are issues when treating extremely interrelated, composite, and noisy databases with a large dimension. For that purpose, outliers detection techniques (ODT) are used for an effective monitoring system to ensure the safety of a transport process. Therefore, in this paper, a novel model of outliers detection and classification has been developed to complement the existing hardware redundancy and limit checking techniques. To overcome these problems, we present a Combined Kernelized Outliers Detection Technique (CKODT) based WSN for damages detection in water pipeline. Initially, training pressure measurement is collected from the sensors which are implemented outside the pipe. Next, these data are fed into the data reduction algorithm as known as Kernel Fisher Discriminant Analysis (KFDA) to create discriminant vectors. Then, these vectors were utilized as inputs for the One Class Support Vector Machine (OCSVM) method to classify the feature sets which were extracted using the proposed technique. The main objective of this work was to combine the advantages of these tools to enhance the performance of the monitoring water pipeline system. The accuracy of our Combined Kernelized Outliers Detection Technique for classification was analyzed and compared with variety of techniques. The experimental results showed the improvements of the proposed framework compared to other techniques in the context of damage detection in the monitoring water pipeline process.

Measurement and Characterization of Acoustic Noise in Water Pipeline Channels

Measurement and characterization of acoustic noise in water pipeline systems across the 10 Hz to 100 kHz acoustic frequency band are reported in this paper. The motivation for the noise characterization is to support the development of acoustic signal processing and communication systems for water pipeline systems. Measurements are reported from an urban water supply system in the city of Christchurch, New Zealand, using hydrophones inserted into the pipelines. These measurements are some of the first that have been reported for an operational water supply system. In addition, for comparison to a controlled baseline reference, measurements have also been performed in a 160 m pipeline laboratory testbed at The Hong Kong University of Science and Technology. A key finding is that the noise amplitude probability density function (PDF) is found to follow a heavy-tailed distribution and the α-stable distribution is proposed for its characterization. The resultant acoustic noise measurements have also been analyzed to determine their power spectral density (PSD) characteristics. The measured noise PSD is not flat and characteristic frequencies and power density levels are utilized to capture the features of the noise PSD. These findings could have a significant impact on the design of signal processing systems for water pipeline systems due to their deviation from the conventional added white Gaussian noise model. In addition, three different acoustic noise sources with individual power and distribution characteristics are also postulated. These postulated sources are used to propose a straightforward acoustic noise model for supporting the simulation of acoustic noise for signal processing system design in water pipelines.

Smart and Sustainable Leakage Monitoring for Water Pipeline Systems

Smart and Sustainable Leakage Monitoring for Water Pipeline Systems

Risk Assessment of Water Pollution in Mountainous Industrial Parks

Water system security is the basic condition and important factor to promote the stable development of mountain industrial parks. The purpose of this study is to scientifically evaluate the water pollution risks that mountain industrial parks may face. To this end, in this paper a water pollution risk assessment index system was constructed in four aspects such as water supply, water use, drainage and flood control. Then, the analytic hierarchy process (AHP) was applied to calculate the weight of each factor. Finally, based on expert scoring, few water pollution risks in the mountain industrial park were found, of which the flood control facilities, chemical pollution, ground seepage capacity and water pipeline system are potential unsafe factors with high risk, and especially various chemical pollution poses a risk for the water source safety, water supply quality and drainage in the park, which needs to be strictly controlled.

Accuracy and Sensitivity Evaluation of TFR Method for Leak Detection in Multiple-Pipeline Water Supply Systems

The transient frequency response (TFR) based pipe leak detection method has been developed and applied to water pipeline systems with different connection complexities such as branched and looped pipe networks. Previous development and preliminary applications have demonstrated the advantages of high efficiency and non-intrusion for this TFR method. Despite of the successful validations through extensive numerical applications in the literature, this type of method has not yet been examined systematically for its inherent characteristics and application accuracy under different system and flow conditions. This paper investigates the influences of the analytical approximations and assumptions originated from the method development process and the impacts of different uncertainty factors in practical application systems on the accuracy and applicability of the TFR method. The influence factors considered for the analysis contain system properties, derivation approximations and data measurement, and the pipeline systems used for the investigation include simple branched and looped multi-pipe networks. The methods of analytical analysis and numerical simulations are adopted for the investigation. The accuracy and sensitivity of the TFR method is evaluated for different factors and system conditions in this study. The results and findings are useful to understand the validity range and sensitivity of the TFR-based method, so as to better apply this efficient and non-intrusive method in practical pipeline systems.

Steady state algorithm for leak diagnosis in water pipeline systems

This work proposes an algorithm for leak diagnosis in pipelines based on a steady-state analysis. The motivation of this proposition arises from the fact that often leaks appear in specific locations in water pipeline systems, namely in between two consecutive pipeline stretches (junctions), according with experience of the staff of a real water distribution network. By dismissing other kind of leaks (as leaks in oil pipelines) for which other considerations must be taken into account, this work is focused to the most normal events of leaks in water pipeline systems, and here, the leak diagnosis problem is reduced to identify the junction where the leak occurs. To do that, a steady-state expression is obtained from the classical Water Hammer equations and it is used to compute a drop pressure head between the pipeline ends for each junction. Then this estimation is compared with the one computed by using the pressure head measurements. Finally for each case a residual can be generated and the junction position that produces a residual closer to zero is finally identified as the leak location. The main advantage of this proposition is that the uncertainties in the leak location are not longer important, i. e., the leak location can be given with an exact position as long as the configuration of the pipeline (possibly located underground) is well known. For sake of illustration, some examples are provided via simulations.

Internet system for hydraulic calculations of pipeline systems by the methods of the theory of hydraulic circuits

The paper is focused on a characteristic of an innovative technology for remote application of methods of the theory of hydraulic circuits for modeling the operation of multi-loop water and gas pipeline systems, using the Internet browser. The aims, objectives and implementation principles of the technology resting on the concept of object-oriented modeling of pipeline systems and clientserver architecture of the distributed software are presented. The results of its application are demonstrated.

Groundwater-based water wells characterization from Guinea Bissau (Western Africa): A risk evaluation for the local population

The study conducted in two regions of Guinea Bissau, Oio and Cacheu, focusing on the characterization of the groundwater supplies sampled during the dry season and their associated risks for human health. Twenty samples were collected in wells located nearby pit latrines. In situ analyses were conducted with Semi-quantitative test strips for the determination of turbidity, pH, chloride, carbonate, sulfites, ammonium, nitrite and nitrate. The analysis of metals was performed by an ICP-MS Elan DRC-e and an ICP-OES Optima 8000. The Target Hazard Quotient (THQ) was applied to evaluate the risk of developing chronic systemic effects derived from exposure to metals. Values of concern of turbidity ammonium, and pH values were lower than the normal range for drinking water in most samples. From both regions, Fe and Al were occasionally found with values higher than the international thresholds fixed by the World Health Organization and by the European Commission for drinking water, while, only in one sample from Cacheu region Pb was found significantly above these limits. THQs resulted next to the level of risk (1) for the highest values found of Al, As, Fe and Mn. Of great concern is the resident risk obtained from a well water of Cacheu for the highest value of Pb (96.8μg/L), because the values of the resident risk found of 1 and 0.7 for child and adults respectively. The results obtained highlighted a close correlation between the chemistry of water and sediment and a correlation with the proximity of the water supplies with the latrines. This study evidenced the potential toxicity of the water supplies for the local populations and the risk of developing chronic systemic effects due to some physico-chemical parameters, the importance of functioning water pipeline system, the importance of maintaining adequate distance between latrines and drinking water access.

Comparative Evaluation of Topological and Flow-Based Seismic Resilience Metrics for Rehabilitation of Water Pipeline Systems

AbstractWhereas the continuous functioning of water distribution pipeline systems is important during normal times, it is paramount in the event of disasters such as earthquakes that are usually fo...

Resilience-based water main rehabilitation planning in a multi-hazard context

Due to aging beyond the intended design life, many water mains in the USA are currently deteriorated resulting in an increasing number of failures which challenge water utilities with diminished supply reliabilities, loss of treated water, and numerous other societal issues. Water pipeline systems serving regions that are naturally vulnerable to external hazards, such as earthquakes, pose additional challenges. Numerous vulnerabilities such as these must be congruently analyzed for optimal capital improvement planning of water supply systems. A resilience-based rehabilitation planning framework is presented and demonstrated in this paper to coherently integrate the vulnerabilities of water pipelines to seismic hazards and natural deterioration. The artificial bee colony (ABC), shuffled frog leaping (SFLA), and genetic algorithms (GA) are investigated to identify the best performing optimization algorithm to be used in the modeling framework presented in this study. A scenario of a real-world water supply system operating in the earthquake-prone region in South Carolina is used for demonstrating the rehabilitation framework. The study approach and the presented findings will provide guidance to water utility professionals in optimal capital improvement planning to enhance supply resilience to a multitude of vulnerabilities.