2nd WDSA/CCWI Joint Conference

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https://riunet7pre.upv.es/handle/10251/205560

The Department of Hydraulic Engineering and Environment of the Universitat Politècnica de València (Valencia Tech) is pleased to invite you to the second edition of the WDSA/CCWI Joint Conference to be held in Valencia (Spain).

This conference will bring together professionals from municipalities, consulting firms, and universities to exchange ideas about the big challenges facing the water industry.

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Now showing 1 - 20 of 127

A Bayesian Generative Adversarial Networks (GAN) to Generate Synthetic Time-Series Data, Application In Combined Sewer Flow Prediction
(Editorial Universitat Politècnica de València, 2024-03-06) Bakhshipour, Amin; Koochali, Alireza; Dittmer, Ulrich; Haghighi, Ali; Ahmed, Sheraz; Dengel, Andreas
[EN] Despite various breakthroughs of machine learning and data analysis techniques for improving smart operation and management of urban water infrastructures, some key limitations obstruct this progress. Among these shortcomings, the absence of freely available data due to data privacy or high costs of data gathering and the nonexistence of adequate rare or extreme events in the available data plays a crucial role. Here, the Generative Adversarial Networks (GANs) can help overcome these challenges. In machine learning, generative models are a class of methods capable of learning data distribution to generate artificial data. In this study, we developed a GAN model to generate synthetic time series to balance our limited recorded time series data and improve the accuracy of a data-driven model for combined sewer flow prediction. We considered the sewer system of a small town in Germany as the test case. Precipitation and inflow to the storage tanks are used for the Data-Driven model development. The aim is to predict the flow using precipitation data and examine the impact of data augmentation using synthetic data in model performance. Results show that GAN can successfully generate synthetic time series from real data distribution, which helps more accurate peak flow prediction. However, the model without data augmentation works better for dry weather prediction. Therefore, an ensemble model is suggested to combine the advantages of both models.
A critical review of leakage detection strategies including pressure and water quality sensor placement in water distribution systems – sole and integrated approaches for leakage and contamination intrusion
(Editorial Universitat Politècnica de València, 2024-03-06) Rathi, Shweta
[EN] Water leakages in water distribution networks not only affects on natural water resources but also cause problems to nearby infrastructure or environment and makes water distribution networks more prone to contamination. Complexity in water distribution systems makes leakage detection and its monitoring a difficult task. Leakages in water distribution systems are caused due to damages in pipes, lack of maintenance of pressure due to uncertain demand and various operating conditions. Therefore, to manage the pressure in the water distribution systems it is necessary to identify appropriate leak location. Various studies on pressure management focused on optimal sensor placement for leak localization considering various constraints cost of sensors, demand uncertainty, damages and burst in pipes and few focused on valve location and optimization for control of pressure. The aim of the paper is mainly focus to provide a comprehensive review of various studies related to water quantity and quality related aspects in WDSs. Therefore, it mainly focuses on pressure and water quality sensor placement in water distribution systems with sole and integrated approaches for leakage minimization and contamination intrusion in water distribution systems. This study also focused on optimization model formulations including objective function and constraints, solution methodologies used, and other informative details as inclusive of water quality consideration, network analysis and optimization methods used. A critical review of available methodologies, including existing simulation tools, existing solution approaches, available sensor placement toolkits, technical challenges, and future research direction is presented.
A decision-making approach to assess and prioritise intervention solutions in water distribution systems
(Editorial Universitat Politècnica de València, 2024-03-06) Cabral, Marta; Loureiro, Dália; Covas, Dídia; Foundation for Science and Technology (FCT) (Portugal)
[EN] The present paper aims at proposing and demonstrating the application of a decision-making approach for the identification, assessment, comparison and prioritisation of different intervention solutions. Infrastructural, financial, performance and economic perspectives are considered in the study. The proposed approach is composed of three main modules: 1) Analysis planning and database construction; 2) Infrastructure, asset or component diagnosis and prioritisation; and 3) Study of intervention solutions for priority assets or components. Three assessment levels – macro, meso and micro – are proposed, and the decision-making approach is adapted to each level. A water distribution system located in Portugal is used to demonstrate the proposed approach. This case study comprises five water subsystems, including different assets, such as water storage tanks, pumping and booster stations and water distribution pipes. Five intervention solutions are defined by identifying the main problems associated with the priority subsystem and the respective causes. The intervention solutions are compared considering the financial metrics and performance indicators, such as standardised energy consumption, energy in excess per unit of the authorised consumption, infrastructure value index and non-revenue water. New metrics regarding the assets’ physical condition are also incorporated in the assessment system. Results have shown the influence of considering different assessment criteria and performance indicators in the solutions' prioritisation, highlighting that the solution with the lowest capital cost does not always correspond to the solution with the highest overall performance.
A Model of Intermittent Water Supply Simulating the Inequitable Distribution of Water
(Editorial Universitat Politècnica de València, 2024-03-06) MacRorie, Matthew; Speight, Vanessa; Weston, Sally; Price, Robin; Collins, Richard; EPSRC; WaterAid; Anglian Water
[EN] Over one billion people worldwide with access to piped water experience Intermittent Water Supply (IWS), where consumers receive water for only a fraction of the day or week. A widely observed problem associated with IWS is the inequitable distribution of water across the network. This results in different consumers in the network receiving different volumes of water. Modelling the inequity within IWS systems remains an open research field. To date, simulations have often adapted hydraulic modelling software to understand the distribution of water with little attention to the consumer interaction with the network. This paper proposes a conceptual model based on a more holistic understanding of water distribution in IWS systems. Understanding the spatial and temporal variation in received volumes, as well as the variation in consumer access within the network, enables a more representative simulation of the inequitable quantity of water received by consumers.
A Nonlinear Model Predictive Control Framework for Dynamic Water Network Optimization
(Editorial Universitat Politècnica de València, 2024-03-06) Arandia, Ernesto; Uber, James
[EN] This paper proposes the application of nonlinear model predictive control (NMPC) strategies within an integrating framework for planning and scheduling real-time water distribution system operations. Model predictive control (MPC) refers to a class of algorithms that make explicit use of a process model to optimize the future predicted behavior of a system. Originally developed to address the control needs of power plants and petroleum refineries, over the past 30 years it has successfully been used in a very wide range of applications in industry. In addition to the predictive model, MPC consists of a performance metric reflecting the control actions, an optimization algorithm that computes a sequence of future control signals that minimizes the performance index subject to a given set of constraints, and a moving horizon strategy, according to which only the first element of the optimal control sequence is applied online. The predictive models are generally intended to represent the behavior of complex nonlinear dynamical systems and often consist of linear models that circumvent the stability and performance challenges associated with their nonlinear counterparts. Recent developments on methods to model and solve large-scale nonlinear optimization problems lead to a reconsideration of these formulations, in particular, through development of efficient large-scale barrier methods for nonlinear programming (NLP). As a result, it is now realistic to solve NLPs on the order of a million variables, for instance, with the IPOPT algorithm. These developments are leveraged here to develop an NMPC dynamic real-time optimization strategy that combines a nonlinear dynamical model of the water network with a large-scale NLP optimization algorithm, and a moving horizon strategy to determine how to exert control on the system at the pump facility and network levels. We consider a recent water utility case study to illustrate these concepts.
A review on staged design of water distribution networks
(Editorial Universitat Politècnica de València, 2024-03-06) Tsiami, Lydia; Makropoulos, Christos; Savic, Dragan; This work has received funding from the European Research Council (ERC) under the ERC Synergy Grant Water-Futures (Grant agreement No. 951424).
[EN] Water distribution networks (WDNs) evolve continuously over time. Changes in water demands and pipe deterioration require construction upgrades to be performed on the network during its entire lifecycle. However, strategically planning WDNs, especially for the long term, is a challenging task. This is because parameters that are essential for the description of WDNs in the future, such as climate, population and demand transitions, are characterized by deep uncertainty. To cope with future uncertainty, and avoid overdesign or costly unplanned and reactive interventions, research is moving away from the static design of WDNs. Dynamic design approaches, aim to make water networks adaptive to changing conditions over long planning horizons. A promising, dynamic design approach is the staged design of WDNs, in which the planning horizon is divided into construction phases. This approach allows short-term interventions to be made, while simultaneously considering the expected long-term network growth outcomes. The aim of this paper is to summarize the current state of the art in staged design of water distribution networks. To achieve that, we critically examined relevant publications and classified them according to their shared key characteristics, such as the nature of the design problem (new or existing network design, expansion, strengthening, and rehabilitation), problem formulation (objective functions, length of planning horizon), optimization method, and uncertainty considerations. In the process, we discuss the latest findings in the literature, highlight the major contributions of staged design on water distribution networks, and suggest future research directions.
A stochastic sewer model to predict pipe flows and pollutant loads in an urban drainage system
(Editorial Universitat Politècnica de València, 2024-03-06) Addison-Atkinson, William; Chen, Albert; Memon, Fayyaz; Hofman, Jan; Blokker, Mirjam; EPSRC
[EN] This work implemented a stochastic sewer model (SIMDEUM-WW) to forecast dry weather sewer flows and pollutant loading, from probabilistic household demand patterns based on information about inhabitants and appliance usage. The probabilistic outputs were fed into MIKE URBAN (DHI) for hydrodynamic and water quality simulations. The MIKE URBAN model consists of a 1D sewer network model. The model was validated against field measurement data and the results show that the SIMDEUM-WW can adequately calculate wastewater and pollutant loading. However, the SIMDEUM-WW was originally calibrated on households in the Netherlands such that errors were observed in the UK application. The uncertainties in actual flow and pollutant loading also contributed to the inaccuracy of modelling results.
A Thorough Cybersecurity Dataset for Intrusion Detection in Smart Water Networks
(Editorial Universitat Politècnica de València, 2024-03-06) Murillo, Andrés; Taormina, Riccardo; Tippenhauer, Nils; Galelli, Stefano; Singapore’s National Satellite Of Excellence, Design Science and Technology for Secure Critical Infrastructure (NSoE DeST-SCI)
[EN] The increase in the number and complexity of cyber-physical attacks on water distribution systems requires better intrusion detection systems. So far, the design and validation of such systems has relied on datasets, such as the EWRI 2017 BATtle of the Attack Detection ALgorithms (BATADAL), that provide a detailed representation of hydraulic processes in response to cyber-physical attacks. However, the BATADAL, generated with epanetCPA, does not include an equivalent and detailed representation of the processes occurring within the industrial communication system. Here, we fill in this gap by presenting the BATADAL 2.0 dataset, generated with the DHALSIM simulator, a novel co-simulation environment that can represent the hydraulic processes, digital control, and network communication of smart water networks. The dataset includes a broad variety of attacks and network anomalies. Most importantly, the availability of both process and network data is expected to pave the way to more advanced and accurate detection algorithms.
Acoustic Data Analysis Framework for Near Real-Time Leakage Detection and Localization for Smart Water Grid
(Editorial Universitat Politècnica de València, 2024-03-06) Chew, Alvin; Wu, Zheng; Kalfarisi, Rony; Xue, Meng; Pok, Jocelyn; Jianping, Cai; Lai, Kah; Hew, Sock; Wong, Jia
[EN] Acoustic sensors are widely used for monitoring urbanized water distribution networks (WDNs) to detect and localize pipe leakages. Since their inception, few research studies have focused on developing a generic, effective, and practical methodology to analyse complex acoustics signals for leakage detection and localization in large-scale WDNs. In collaboration with PUB, Singapore’s National Water Agency, a generic acoustic data analysis approach has been developed to facilitate PUB’s present Smart Water Grid (SWG) management. The proposed approach encompasses multi-stage systematic analyses, namely: (1) data quality assessment; (2) data pre-processing; (3) near real-time leakage event detection and classification; and finally (4) near real-time leakage localization. Our proposed approach is then tested in major WDNs in Singapore having more than 1100km of underground water pipelines and 82 permanently installed hydrophone acoustic sensors between 1 Aug 2019 and 31 Aug 2020, where multiple historical leakage events were reported to within 600m, or less, from neighbouring hydrophones across the large complex networks. By emulating the near real-time detection and localization analyses daily, our proposed methodology could localize reported leakage events to an error range of around 150m on average, while demonstrating significant and stable acoustic leakage power rate over the temporal size of the leakage event cluster(s).
Advanced fire flow risk analysis using EPANET
(Editorial Universitat Politècnica de València, 2024-03-06) Sinske, Alexander; de Klerk, Altus; van Heerden, George
[EN] A water reticulation system is key infrastructure that enables hydraulic water services. It is therefore a critical component in providing the full level of water service to a city’s consumers. Extended water outages and below minimal pressure is a risk for the water network and especially for fire flows. GLS has developed and implemented a multi-threaded client-server software application based on the latest open-source EPANET 2.2 hydraulic analysis engine which now enables city-wide fire flow risk analyses on a property-by-property basis in reasonable time. Previously it has been virtually impossible to assess the risk on a city-wide basis, for each and every property, and to consider the improvement of such risk in the master plan (MP) of the water distribution system. Hence, the focus of the MP has been the provision of flows and pressures for the peak hour demand scenario in the network. Consequently, many township developments, densifications, and land use re-zonings require a separate and focussed specific fire risk analysis to ensure the existing system is capable of providing the requisite fire flow and pressure. If not, specific additional MP items related to the fire requirements of the specific property have to be investigated and considered for implementation. The fire flow risk analysis produces a GIS-based heat map displaying a Fire Risk Compliance Score (FRCS) of areas and properties where the current system is inadequate to deliver the fire flows and pressures. Such a heat map provides valuable information that can be used to improve and prioritise the MP and minimise future additional ad-hoc analyses for specific properties or developments. The fire flow risk analysis also allows the identification of pressure management zones where adjustments to the pressure regime are required in order to ensure requisite fire flows/pressures are achieved. Various methodologies based on Pressure Driven Analysis and Demand Driven Analysis have been evaluated and tested on models from South African cities. Great care has been take to optimise the multi-threaded communication of the application with the EPANET engine to streamline performance and support concurrent hydraulic analyses. In addition, a concept of automatically creating unique fire events to reduce the number of analyses, has been introduced for large models. This has resulted in smaller cities that can be analysed on modern PCs with few processor cores in a few minutes and large cities that can be analysed in reasonable time on high-core cloud-computing platforms. Visualisation in GIS-based software greatly helps to control the analyses and interpret results visually. Critical areas can be identified on a broader scale and allows for a rational approach to decide where to focus on network augmentation, or alternatively to provide on-site fire fighting capabilities.
Advances in Premise Plumbing Modeling
(Editorial Universitat Politècnica de València, 2024-03-06) Platten, William; Murray, Regan; Lee, Juneseok; Janke, Robert; Haxton, Terra; Grayman, Walter; Burkhardt, Jonathan; Buchberger, Steven
[EN] In summer 2019, a new task committee on Premise Plumbing Modeling (PPM) was approved under the auspices of the Water Distribution Systems Analysis Committee of ASCE EWRI. The primary purpose of the PPM task committee is to advance the science of the new field of premise plumbing modeling. In particular, the PPM committee intends to identify areas where methods and models developed over the past several decades to manage municipal water distribution systems can also be applied to solve vexing problems that arise in the premise plumbing systems of contemporary buildings. The ultimate goal of the PPM committee is to identify and develop water systems management tools for use by practicing engineers, as well as the larger water distribution research community, in support of the safe design and operation of indoor water distribution systems. Initially, three general areas were identified where current modeling approaches could be applied to premise plumbing: [1] hydraulic design and performance, [2] building water quality and age, and [3] water safety and security. Using these three core areas as a backdrop, this presentation will describe key accomplishments of the PPM task committee including: creation of a monthly webinar series reaching an international audience, distribution of a quarterly newsletter to the professional community, presentation of technical sessions at annual EWRI national Congress, preparation of a state-of-the-art journal paper, publication of a textbook style final report to archive the main topics covered in the PPM webinar series. Finally, this talk will conclude with a glimpse of the challenging problems posed by modern premise plumbing systems and the unique opportunities waiting for researchers working in the field of water distribution network analysis.
Advancing towards semi-automatic labeling of GPR images to improve visualizations of pipes and leaks in water distribution networks using multi-agent systems and machine learning techniques
(Editorial Universitat Politècnica de València, 2024-03-06) Stanton, Gemma; Ayala-Cabrera, David
[EN] Critical infrastructures such as water distribution networks (WDNs) require reliable and affordable information at a reasonable cost to address challenges that can negatively affect their operation. Inadequate knowledge about WDN assets and their state of health presents challenges for essential activities such as network modeling, operation, assessment, and maintenance. This work seeks to increase the availability of WDN asset data through improved interpretability of GPR images. The semi-automatic labeling approach presented here expands upon existing multi-agent image-cleaning methods and feature characterization techniques. The division of a pre-processed image, in the form of a matrix, into a grid of smaller blocks allowed the identification of relevant features using density of nonzero values in the blocks; this approach, conducted manually in this proof of concept, can provide a basis for training an intelligent system (e.g., a convolutional neural network) to extract the families of interest and eliminate noise. Thus, this research expands this methodology to advance towards automatic detection of pipes and leaks and easily visualize the data. In this paper, 3D visualizations of WDN assets have been created to demonstrate the usefulness of this semi-automatic process in delivering easily-interpretable GPR data for managers and operators of WDNs.
An approach to improve drainage networks based on the study of flood risk
(Editorial Universitat Politècnica de València, 2024-03-06) Bayas-Jiménez, Leonardo; Martínez Solano, Francisco Javier; Iglesias Rey, Pedro Luis; Boano, Fulvio; Dpto. de Ingeniería Hidráulica y Medio Ambiente; Escuela Técnica Superior de Ingeniería Industrial
[EN] In recent years, the number of pluvial floods in cities has increased. There are different reasons for this increase, but certainly the most important are the increase in the intensity of the rain and the growth of cities, which increases the impervious surface, decreases the concentration time, and consequently increases runoff. To determine the costs of flood damage, land use is very important in the estimation of the cost of flood damage because it defines the type, value, and vulnerability of the structures. On this wise, an approach of great interest to managers of drainage networks is the estimation of annual damages in the area under study, because by knowing these costs, corrective measures can be taken, and the investment needed to reduce flooding can be determined. This work aims to present a methodology to improve drainage networks with lack of capacity due to increased runoff with a focus on the study of the vulnerability to the risk of flooding. To improve the operation of the networks, the method considers the possibility of changing the existing pipes for others with greater capacity, the construction of storm tanks and the implementation of hydraulic controls. To find the best solutions, an optimization model was developed that uses a Pseudo Genetic Algorithm and the SWMM model to perform hydraulic simulations. To reduce calculation times, a search space reduction procedure is applied to identify the regions containing the best solutions. These actions are intended to improve the efficiency of the model. For the economic assessment of flood risks, the cost of flood damage is related to its probability of occurrence for different return periods. With these data, a curve with a log-linear relationship is constructed. The cost of the flood risk is obtained by integrating the area under the curve obtained. The methodology is applied in a drainage network with flooding problems called Balloon, located in located in northern Italy. The results are useful to demonstrate the benefit of risk cost analysis to make decisions and underline the relevance of including optimization models to prevent future damage in cities.
An Experimental Study On Early Leak Localization In Drinking Water Networks using pressure measurements
(Editorial Universitat Politècnica de València, 2024-03-06) Deleuze, Yannick; Nova-Rincón, Arley; Batany, Yves-Marie; Abril, Teodulo; Chenu, Damien; Roux, Nicolas
[EN] Leaks represent a major issue impacting the management and efficiency of Drinking Water Networks (DWN) in cities worldwide. According to the Development Bank of Latin America, by 2018 the losses in DWN range from 40 to 60% in the region. In Europe, the OECD reports a wider range with few losses in cities like Amsterdam (4%) up to 37% in Naples. With this context, some regional policies have emerged like the 2020 european drinking directive “Right2Water”, that aims to encourage major suppliers (more than 50000 users), to develop tools to measure and reduce leakages by 2025. Considering this situation, we introduce here a systematic approach for leak management that combines field data, hydraulic models (HM) and machine learning.Model-based and data driven methods have been of great interest for leak location methodologies in DWN. This research will design energy-efficient and cost-efficient leak localization hotspots in the DWN. The approach is intended for sectorized DWN, equipped with a SCADA system and where a calibrated hydraulic model (e.g. EPANET) is available. This latter serves to evaluate the sensitivity of the system to leaks and identify potential points for pressure measurements in order to optimise the number of installed sensors. Given a detected leak in the network, a multiclass classifier using pressure data is developed to reduce the inspected pipe length for the leak location. The leakage localization method is implemented combining multiple individual classifiers using ensemble learning methods and a reduced number of decision variables. The methodology is tested on a real case study from a Colombian site. The method faces challenges in (a) collecting correctly labelled real leak data, and (b) modelling and calibrating hydraulic models. Those challenges are being addressed. The outcome shows that the length of pipes inspected can be reduced by one third with high performance in accuracy with few sensors required (low capital expenditures) and low computational effort (low energy and low operational expenditures).
An improved control strategy for high-pressure pumping irrigation systems
(Editorial Universitat Politècnica de València, 2024-03-06) Wang, Ye; Zhao, Qi; Weyer, Erik; Wu, Wenyan; Simpson, Angus; Willis, Ailsa
[EN] Pumped irrigation systems are critical infrastructure that supply water from water sources to rural users through interconnected pressurized water pipes. To supply enough pressure head to all the irrigation outlets located in the irrigation network, it is required to have an appropriately high pressure head supplied by the pump station. Therefore, the energy consumption related to pumping could be correspondingly high, which may lead to significant operating costs. With the aid of real-time flow data available from each irrigation outlet, the proposed improved pump head setpoint selection algorithm can locate the most critical outlet in terms of the smallest downstream pressure head and therefore guarantee to deliver the minimum pressure required for all active outlets in the network. By using the proposed algorithm, it has been demonstrated with a two-day simulation that a 4.74% savings in pumping energy cost as well as a reduction in the associated greenhouse gas emissions can be achieved.
An optimization framework for large water distribution systems based on complex network analysis
(Editorial Universitat Politècnica de València, 2024-03-06) Sitzenfrei, Robert; This research was funded by the Austrian Science Fund (FWF): P 31104-N29
[EN] The major task of water distribution networks (WDNs) is to reliably supply water in sufficient quantity and quality. Due to the complexity in design and operation of WDNs, and to ensure a reliable level of service with minimum costs, multi-objective design approaches are used which are usually rely on evolutionary algorithms. However, for large WDNs the decision variable space increases exponentially. When considering multiple objectives (e.g., resilience, costs, water quality), for complex, large (real) WDNs with several thousand decision variables, evolutionary algorithms are practically infeasible to apply. With complex network analysis mathematical graphs of WDNs can be analysed very computationally efficient and therefore such an approach is especially suitable for analysing large spatial transport networks. Recently, based on complex network, a highly efficient approach for Pareto-optimal design of WDNs was developed. Based on topological features and a customized graph measure for the demand distribution (demand edge betweenness centrality), a graph-based multi-objective design approach was developed, which outperformed the results of an evolutionary algorithm regarding the quality of solutions and computation time (factor 105 faster). Further, also based on complex network analysis, a highly efficient surrogate method for assessing water quality in large WDNs was developed (2.4∙105 times faster than extended period simulation Epanet2). In this paper, these two approaches based on complex network analysis: (1) two objective optimization model and (2) the graph-based water quality model, are combined in a novel graph optimization framework which is especially suitable for complex, large (real) WDNs. The applicability of this very computationally efficient, novel approach is shown on a real case studies with 4,000 decision variables for which the results are be obtained within 18.5 seconds of computation time, while with a state-of-the-art evolutionary algorithm it took more than 8 weeks.
Analysis of friction models during simulations of filling processes in single pipelines
(Editorial Universitat Politècnica de València, 2024-03-06) Coronado-Hernández, Óscar E.; Fuertes Miquel, Vicente Samuel; Iglesias Rey, Pedro Luis; Besharat, Mohsen; Ávila, Humberto; Ramos, Helena M.; Dpto. de Ingeniería Hidráulica y Medio Ambiente; Escuela Técnica Superior de Ingeniería Industrial
[EN] The analysis of filling processes in pressurized pipelines has been conducted using a steady friction model in the implementation of governing equations. This research is focused on the case of a filling process of a single pipeline without an air valve. Three equations were used to represent the phenomenon: (i) a rigid water column approach, which describes the water movement along the water system; (ii) a piston flow model, which assumes a perpendicular air-water interface to the main direction of the pipe; and (iii) a polytropic model for representing the thermodynamic behaviour of an entrapped air pocket. This research studies the filling processes occurrence using equations of steady and unsteady friction models, where Moody, Wood, Hazen-Williams, and Swamee-Jain equations are analysed. The analysis is applied to a case study of a single pipe of a total length of 1000 m with an internal diameter of 595 mm variation of pressure surges in the implementation of these formulations. Results confirm that there is a minimum discrepancy between steady and unsteady friction models since values of pressure surges pattern are similar.
Analysis of online pressure for resilience phase characterisation of leakages/burst events
(Editorial Universitat Politècnica de València, 2024-03-06) Hoseini Ghafari, Sotudeh; Francés-Chust, Jorge; Piller, Olivier; Ayala-Cabrera, David
[EN] While operating a water distribution network (WDN), it is essential to prepare the system to face with intentional (e.g., cyber-physical attack) or unintentional (e.g., pipe leakage/burst) adverse events or other drivers such as the effects of climate change. Increasing the network’s preparedness to deal with anomalous events is an effective manner to improve the system’s resilience, reducing the negative impacts of events. In this paper, leakage/burst events, and ordinary network operation, are captured by both sensors and expert knowledge in a WDN in Spain. Event-driven and data-driven approaches are used to characterise the system behaviour, in particular when it is operating under the effects of an anomalous event, based on the resilience phases (i.e., absorptive, adaptive, restorative) for the collected dataset. The relationship of clustering pressure head time series based on their potential state in a particular resilience phase, in three random cases of short-term leakage events, was explored. This paper focuses on capturing the behaviour of the system, through the exploration of the hydraulic parameters of WDNs (in particular the pressure head) before, during, and after a leakage event, by means of a spatial-temporal analysis. It was observed that the network behaviour could be categorised into 1) ordinary operation and 2) during the event, which would allow to characterise the system behaviour when influenced by leakage/burst event and also explore its adaptability to resilience phases. The results show that it is possible to extract relevant patterns (i.e., feature maps) and generate an anomaly indicator from the pressure head heatmaps that facilitate the characterisation of anomalous events for WDNs.
Analysis of PDA-based Water Distribution System Suspension Risk using statistical and machine learning method
(Editorial Universitat Politècnica de València, 2024-03-06) Oh, Yoojin; Park, Haekeum; Hyung, Jinseok; Kim, Taehyeon; Kim, Kibum; Koo, Jayong; Ministry of environment (South Korea)
[EN] Recently, there have been frequent cases of water shortages caused by failure to old water pipes. As water is the most basic resource in life and is an indispensable resource in various fields such as industry and agriculture, the scale of the failure is significant in the event of accidents in the water supply pipe network, and in order to minimize the damage of accidents, it is important to prevent accidents through timely maintenance. At this time, the risk map of the water shortage of the water pipeline needs to be prepared for efficient maintenance, and it needs to be managed first from the high-risk area.To this end, water shortage risk analysis due to pipe failure was performed in this study. Risk analysis is one of the ways in which water pipes are evaluated and decisions on investment plans, such as replacement or repair, can be supported. The risk is generally calculated by multiplying PoF (Probability of failure) with the resulting direct and indirect effects of CoF (Consequence of failure). In this study, PoF was derived as the failure of an individual water pipe was set as the probability of failure caused by corrosion, and in order for it to be predicted, MLP (Multi-layer perceptron) and XGBoot were developed as a data-based machine learning model. In addition, it was analyzed by setting the amount of water (supply shortage) that CoF could not be supplied due to failure, considering that the failure to the water pipe was directly linked to water shortage. In order to analyze the supply shortage at this time, the mathematical analysis of PDA (Pressure driven analysis) was performed.Finally, the developed methodology was applied to the cities of the Republic of Korea, and the risks were analyzed by calculating the PoF and CoF of individual water pipes, and the GIS technique was used to create the risk map.The results of this study can be more accurate in predicting the condition of water pipes, which can be helpful when water utilities establish maintenance plans.
Aquarellus: a numerical too to calculate accumulation of particulate matter in drinking water distribution systems
(Editorial Universitat Politècnica de València, 2024-03-06) van Summeren, Joost; Dash, Amitosh; Morley, Mark; de Waal, Luuk; van Steen, Jip
[EN] Despite preventive measures, turbid (vernacular: “discolored”) distributed drinking water is still a common cause for customer complaints across the world. Discoloration events are caused by the accumulation of particulate matter in drinking water distribution systems (DWDSs) and subsequent remobilization during hydraulic events [1], although uncertainties remain concerning the specific accumulation and transport processes. For Dutch DWDSs, it is plausible that microscopic particles originating at treatment plants contribute substantially to the particulate matter that resides in DWDSs, and that physical processes within the distribution network are cardinal in the subsequent transport during distribution. Aquarellus, a predictive numerical tool has been developed to predict the accumulation of particulate material in DWDSs. It integrates hydraulic calculations using the EPANET toolbox with a particle transport module that is based on a description of gravitational settling, particle stagnation, bed load transport, and resuspension of particles in distribution pipes, depending on the shear stress near the pipe wall [2]. The performance of the multi-core calculations allows for simulating distribution network sizes that are common to Dutch water utilities (100s of km total pipe length). The user can assign the injection of multiple particle species corresponding to temporal patterns at multiple source locations. A graphical user interface handles user IO and the visualization of geographical maps as well as time-dependent build-up of particulate material across the distribution network and within individual pipes. To characterize particle properties (critical input parameters) encountered in Dutch DWDSs, we performed lab experiments on 9 samples from 3 water utilities to determine particle size distributions, mass density, mobility thresholds, and a measure for gravitational settling. Using the outcomes of these lab experiments, a sensitivity test with a range of input parameters was performed in Aquarellus. This helped determine how the variation in the relevant input parameters influence the calculated spatial patterns of accumulated particulate matter ̶ a measure for the discoloration risk. We compared the modeling results to turbidity measurements from systematic cleaning actions in a real-life Dutch distribution network (Spijkenisse). Finally, we will discuss the potential for applying the tool to assist the planning of cleaning actions and monitoring programs.

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