Locating Multiple Leaks in Water Distribution Networks Combining Physically Based and Data-Driven Models and High-Performance Computing

Water utilities are urged to decrease their real water losses, not only to reduce costs but also to assure long-term sustainability. Hardware- and software-based techniques have been broadly used to locate leaks; within the latter, previous works that have used data-driven models mostly focused on single leaks. This paper presents a methodology to locate multiple leaks in water distribution networks employing pressure residuals. It consists of two phases: one is to produce training data for the data-driven model and cluster the nodes based on their leak-flow-rate-independent signatures using an adapted hierarchical agglomerative algorithm; the second is to locate the leaks using a top-down approach. To identify the leaking clusters and nodes, we employed a custom-built k-nearest neighbor (k-NN) algorithm that compares the test instances with the generated training data. This instance-to-instance comparison requires substantial computational resources for classification, which was overcome by the use of high-performance computing. The methodology was applied to a real network located in a European town, comprising 144 nodes and a total length of pipes of 24 km. Although its multiple inlets add redundancy to the network increasing the challenge of leak location, the method proved to obtain acceptable results to guide the field pinpointing activities. Nearly 70% of the areas determined by the clusters were identified with an accuracy of over 90% for leak flows above 3.0 L/s, and the leaking nodes were accurately detected over 50% of the time for leak flows above 4.0 L/

Experimental quantification of contaminant ingress into a buried leaking pipe during transient events

It has been hypothesized that negative pressures caused by transients within water distribution systems may result in ingress of contaminated groundwater through leaks and hence pose a risk to public health. This paper presents results of contaminant ingress experiments from a novel laboratory facility at The University of Sheffield. An engineered leak surrounded by porous media was subjected to pressure transients resulting from the rapid closure of an upstream valve. It has been shown that a pollutant originating externally was drawn in and transported to the end of the pipe loop. This paper thus presents the first fully representative results proving the occurrence and hence, risk to potable water quality of contaminant ingress

Current technologies and the applications of data analytics for crude oil leak detection in surface pipelines

Pipeline pressure monitoring has been the traditional and most popular leak detection approach, however, the delays with leak detection and localization coupled with the large number of false alarms led to the development of other sensor-based detection technologies. The Real Time Transient Model (RTTM) currently has the best performance metric, but it requires collection and analysis of large data volume which, in turn, has an impact in the detection speed. Several data mining (DM) methods have been used for leak detection algorithm development with each having its own advantages and shortcomings. Mathematical modelling is used for the generation of simulation data and this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the ANN and SVM require a large training dataset for development of accurate models, mathematical modelling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modelling for the development of a robust real time leak detection and localization system for surface pipelines. Several case studies are also presented

Leakage Characterisation in Bulk Pipes using Pressure Tests

The supply of water is becoming increasingly strained as the demand for this essential and limited resource continues to increase. A significant amount of this resource is, however, lost through leakage. Not only does this result in a waste of a precious resource, but it also leads to a direct loss of revenue, especially considering that value has been added to the leaking water through collection, storing, purifying and pumping. A great deal of research has been done on reducing water leakages in distribution networks, however, leakage in bulk pipelines has received comparatively little attention thus far. In this study, bulk pipelines in the field were tested with a pressure testing device developed by the University of Cape Town. With this device, a range of pressures were applied to various pipeline sections and the corresponding leakages were measured, resulting in characteristic pressure-leakage relationships. The Fixed and Variable Area Discharge (FAVAD) and the empirical N1 leakage models were then applied to interpret the pressure-leakage relationships. Thirteen tests were attempted on pipeline sections ranging from 300 mm to 600 mm in diameter, and pressure tests were successfully performed on eight of the thirteen sections. Even though the effectiveness of the testing technique is dependent on the sealing capability of the isolation valves, it was found that most valves sealed effectively, with only two pipelines sections failing to isolate. The high elevation differences along the length of the pipelines were found to have a dominating effect on the characteristics of the leak, which made it possible to roughly estimate the most likely leak locations by comparing the observed leak characteristics to those found in literature for similar conditions. The dependence of the leak characteristics on the location means that both have to be determined simultaneously. This can benefit the analysis, as some locations may be excluded based on their unrealistic leakage characteristics. However, it also means that there will be uncertainty with regards to the true location and leakage characteristics for sections of the pipe where the leakage characteristics are realistic. Nonetheless, the measured leakage rate together with the estimated leak characteristics provided valuable information on the pipeline conditions, making it possible to rank the pipelines according to the severity of their conditions, for optimal allocation of maintenance resources. Through practical tests, the study shows that pressure testing is an effective, simple and low cost technique to assess leakage in bulk pipelines. It causes minimal interference to the pipe operation, requires little downtime and the data can be processed in minimal time

Application of software and hardware-based technologies in leaks and burst detection in water pipe networks: a literature review

With the rise of smart water cities, water resource management has become increasingly important. The increase in the use of intelligent leak detection technologies in the water, gas, oil, and chemical industries has led to a significant improvement in safety, customer, and environmental results, and management costs. The aim of this review article is to provide a comprehensive overview of the application of software and hardware-based technologies in leak detection and bursts in water pipeline networks. This review aims to investigate the existing literature on the subject and to analyse the key leak detection systems in the water industry. The novelty of this review is the comprehensive analysis of the literature on software and hardware-based technologies for leak and burst detection in water pipe networks. Overall, this review article contributes to understanding the latest developments and challenges in the application of software- and hardware-based technologies for leak and burst detection in water pipe networks, and serves as a valuable resource for researchers, engineers, and practitioners working in the field of water distribution systems

Single-event leak detection in pipeline using first three resonant responses

Hydraulic transients (water hammer waves) can be used to excite a pressurized pipeline, yielding the frequency response diagram (FRD) of the system. The FRD of a pipeline system is useful for condition assessment and fault detection, because it is closely related to the physical properties of the pipeline. Most previous FRD-based leak detection techniques use the sinusoidal leak-induced pattern recorded on the FRD, either shown on the resonant responses or the antiresonant responses. In contrast, the technique reported in the current paper only uses the responses at the first three resonant frequencies to determine the location and size of a leak. The bandwidth of the excitation only needs to be five times that of the fundamental frequency of the tested pipeline, which is much less than the requirement in conventional FRD-based techniques. Sensitivity analysis and numerical simulations are performed to assess the robustness and applicable range of the proposed leak location technique. The proposed leak location technique is verified by both numerical simulations and by using an experimental FRD obtained from a laboratory pipeline. © 2013 American Society of Civil Engineers.Jinzhe Gong, Martin F. Lambert, Angus R. Simpson, and Aaron C. Zecchi

Pressure-based leakage characterisation of bulk pipelines

Water losses in distribution systems are a huge problem internationally and also in South Africa where more than a third of the water entering the water supply networks is lost through pipe leaks. With water demand increasing due to population growth and urbanisation, water resources are under greater stress and water supply failures are becoming more common. A great deal of work has been done over the past two decades on managing water losses in distribution systems. The Water Loss Task Force of the International Water Association (IWA) played a leading role in this effort, with the “IWA water balance” now widely used as a basis in municipal water loss programs. One of the areas that have received relatively little attention is leakage on bulk pipeline systems. Bulk pipelines connect water treatment plants to bulk reservoirs and distribute water from reservoirs to different towns or water supply zones. Bulk pipes may be operated using pumps or gravity, and generally do not supply consumers directly. It is difficult to determine what the water losses in a bulk pipeline are, as the high flow rates make it impractical or prohibitively expensive to measure flow rates at both ends of these pipelines. Cheaper solutions, such as clamp-on ultrasonic flow meters or reservoir drop tests, are prone to problems and do not have the required accuracy. Due to the lack of reliable and effective methods, water losses on bulk pipes are often assumed to be 2 or 3 %. However, these losses may, in fact, be much greater, and due to the large flow of water transported by bulk pipelines, even small fractions of losses represent large volumes of water. The aim of this project was to develop a method for identifying the size and type of leak present in real bulk water pipelines with minimal disturbance to the operation of the infrastructure. This was achieved by developing a mobile device called the pipe condition assessment equipment (PCAE), which uses pressure testing in combination with the latest models on the behaviour of leaks areas with pressure to assess the condition of the bulk pipeline. To verify the efficacy of the PCAE, the device was first tested on three uPVC pipes with known leakage characteristics in the laboratory (a 12mm round hole, 100mm by 1mm circumferential crack and a 100mm by 1mm longitudinal crack). As expected, the round hole had very small head-area slopes which are negligible, whilst the circumferential crack showed a negative head area slope and the longitudinal crack portrayed a large positive head-area slope. These results were consistent with previous laboratory experiments that investigated the behaviour of round holes and longitudinal and circumferential cracks. Bulk water suppliers and municipalities were then approached to take part in the study. Several bulk pipelines were tested using the PCAE. The results of the field test are discussed in terms of the pre-testing procedures to prepare for the tests, their repeatability and the effectiveness of the device to detect, quantify and characterise leakage on the pipeline. For pipelines with undetectable leakage, a non-intrusive technique that uses a dynamic pressure drop signature from an isolated pipe, to detect and quantify undetectable leakage, was developed. The leakage characteristics of the isolated pipe were estimated from the pressure vs time data. In summary, if the pressure remained constant the pipe was without a leak. If the pressure dropped, a novel mathematical model was fitted to the pressure vs time curve, using the known pipe properties, to determine the characteristics of the leak or leaks present in the pipe. Overall, the PCAE was capable of assessing the extent of leakage on a range of pipe materials, diameters and lengths. It was found that out of the eleven bulk pipelines tested in this study, three could not be tested due to dysfunctional isolation valves and failed connection points. The other eight pipelines that were successfully tested were found to be leaking. The effective initial leak areas for the tested pipelines ranged from 4.88mm2 to 137.66mm2 , whilst the effective head-area slope ranged from 0.0032 mm2 /m to 3.14 mm2 /m and the N1 leakage exponents were found to range from 0.56 up to 1.09. Finally, since there are no well-founded performance indicators for bulk systems, this study also described the findings from analyses of several potential performance indicators using the data from the bulk pipelines tested using the PCAE. The challenges in comparing water losses of different bulk pipelines are highlighted. Based on this, it was found that because every bulk pipeline has its unique characteristic regarding structural parameters such as diameter, pipe material, type of couplings, and operating pressure, the preferred performance indicator for assessing water losses in bulk systems mainly depends on the purpose of the analysis

Enabling Resilience in Cyber-Physical-Human Water Infrastructures

Rapid urbanization and growth in urban populations have forced community-scale infrastructures (e.g., water, power and natural gas distribution systems, and transportation networks) to operate at their limits. Aging (and failing) infrastructures around the world are becoming increasingly vulnerable to operational degradation, extreme weather, natural disasters and cyber attacks/failures. These trends have wide-ranging socioeconomic consequences and raise public safety concerns. In this thesis, we introduce the notion of cyber-physical-human infrastructures (CPHIs) - smart community-scale infrastructures that bridge technologies with physical infrastructures and people. CPHIs are highly dynamic stochastic systems characterized by complex physical models that exhibit regionwide variability and uncertainty under disruptions. Failures in these distributed settings tend to be difficult to predict and estimate, and expensive to repair. Real-time fault identification is crucial to ensure continuity of lifeline services to customers at adequate levels of quality. Emerging smart community technologies have the potential to transform our failing infrastructures into robust and resilient future CPHIs.In this thesis, we explore one such CPHI - community water infrastructures. Current urban water infrastructures, that are decades (sometimes over a 100 years) old, encompass diverse geophysical regimes. Water stress concerns include the scarcity of supply and an increase in demand due to urbanization. Deterioration and damage to the infrastructure can disrupt water service; contamination events can result in economic and public health consequences. Unfortunately, little investment has gone into modernizing this key lifeline.To enhance the resilience of water systems, we propose an integrated middleware framework for quick and accurate identification of failures in complex water networks that exhibit uncertain behavior. Our proposed approach integrates IoT-based sensing, domain-specific models and simulations with machine learning methods to identify failures (pipe breaks, contamination events). The composition of techniques results in cost-accuracy-latency tradeoffs in fault identification, inherent in CPHIs due to the constraints imposed by cyber components, physical mechanics and human operators. Three key resilience problems are addressed in this thesis; isolation of multiple faults under a small number of failures, state estimation of the water systems under extreme events such as earthquakes, and contaminant source identification in water networks using human-in-the-loop based sensing. By working with real world water agencies (WSSC, DC and LADWP, LA), we first develop an understanding of operations of water CPHI systems. We design and implement a sensor-simulation-data integration framework AquaSCALE, and apply it to localize multiple concurrent pipe failures. We use a mixture of infrastructure measurements (i.e., historical and live water pressure/flow), environmental data (i.e., weather) and human inputs (i.e., twitter feeds), combined and enhanced with the domain model and supervised learning techniques to locate multiple failures at fine levels of granularity (individual pipeline level) with detection time reduced by orders of magnitude (from hours/days to minutes). We next consider the resilience of water infrastructures under extreme events (i.e., earthquakes) - the challenge here is the lack of apriori knowledge and the increased number and severity of damages to infrastructures. We present a graphical model based approach for efficient online state estimation, where the offline graph factorization partitions a given network into disjoint subgraphs, and the belief propagation based inference is executed on-the-fly in a distributed manner on those subgraphs. Our proposed approach can isolate 80% broken pipes and 99% loss-of-service to end-users during an earthquake.Finally, we address issues of water quality - today this is a human-in-the-loop process where operators need to gather water samples for lab tests. We incorporate the necessary abstractions with event processing methods into a workflow, which iteratively selects and refines the set of potential failure points via human-driven grab sampling. Our approach utilizes Hidden Markov Model based representations for event inference, along with reinforcement learning methods for further refining event locations and reducing the cost of human efforts.The proposed techniques are integrated into a middleware architecture, which enables components to communicate/collaborate with one another. We validate our approaches through a prototype implementation with multiple real-world water networks, supply-demand patterns from water utilities and policies set by the U.S. EPA. While our focus here is on water infrastructures in a community, the developed end-to-end solution is applicable to other infrastructures and community services which operate in disruptive and resource-constrained environments

Offshore pipeline leak modeling using a computational fluid dynamics approach

Pipelines laid over long distances in the harsh offshore environment may be affected by excessive straining, corrosion, scouring, iceberg and other third-party damages. Small chronic leaks may cause severe safety and environmental effects if left undetected for a long time. A CFD model of a subsea leaking pipeline is developed to predict the pressure and temperature profiles around the pipe’s leak surroundings. The developed CFD model is used to study a pipeline section with a leak on the top. It considers the fluid inside the pipeline as well as the fluid surrounding the pipeline and does a combined simulation of the system. In addition, a hydrodynamic model is used to evaluate the parameters of a full-scale 150 km long-distance pipeline. This hydrodynamic model is developed to find the most critical section of the proposed long pipeline system. Furthermore, the hydrodynamic model provides the boundary conditions for the CFD model. The developed model was used to perform parametric studies to understand the impact of leaks on the surrounding water. The present study will help pipeline operators to select the most appropriate leak detection technology with the right specifications for the pipeline systems; especially to optimize Fiber Optic Cable (FOC) based Distributed Temperature Sensing (DTS) Solutions

Understanding the Dynamic Leakage Behaviour of Longitudinal Slits in Viscoelastic Pipes

Polyethylene pipes, and other polymeric materials, are a popular choice in the water industry due to their advertised but exaggerated leak resistance. When leaks do occur in this pipe material, the complex leakage behaviour (time and pressure dependent) presents a challenge in accurately modelling the representative response. The presented research aimed to quantify the leak behaviour of longitudinal slits in viscoelastic water distribution pipes, considering the dynamic interaction of hydraulic conditions and the pipe section characteristics. A methodology was developed to create synergy between novel physical investigations and numerical simulations, evaluating the synchronous pressure, leakage, flow-rate and leak area to understand the interdependence of the leakage and structural dynamics. The synchronous leak area was confirmed as the critical parameter defining the leak response and is in turn dependent on the leak and pipe geometry, loading conditions and viscoelastic material properties. The theoretical discharge coeffcient was shown to remain constant, thereby establishing that the structural response, i.e. the change of leak area, can be determined by quantifying the leakage flow-rate and the pressure headalone. Derivation of a generalised leakage model effectively captured the dynamic leakage behaviour. However, the model may provide an erroneous estimate of the true response due to the exclusion of the influence of ground conditions. These were shown to result in a significant increase in slit face loading dependent on the specific soil matrix properties, simultaneously altering the structural deformation and net leakage. Alongside the advances in fundamental understanding, the research also has implications for leakage management strategies. The short term behaviour may severely hinder the effectiveness of leak localisation technologies and the quantification of risk associated with contaminant ingress. However, it was shown that current leakage modelling practice over relatively long time periods are not adversely affected by the existence of such dynamic leaks