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International audience; Water utilities are challenged to reduce their water losses through detecting, localizing, and repairing leaks as quickly as possible in their aging distribution systems. In this work, we solve this challenging problem by detecting multiple leaks simultaneously in a water distribution network for the Battle of the Leak Detection and Isolation Methods. The performance of leak detection and localization depends on how well the system roughness and demand are calibrated. In addition, existing leaks affect the diagnosis performance unless they are identified and explicitly represented in the model. To circumvent this chicken-and-egg dilemma, we decompose the problem into multiple levels of decision-making (a hierarchical approach) where we iteratively improve the water distribution network model and so are able to solve the multileak diagnosis problem. First, a combination of time series and cluster analysis is used on smart meter data to build patterns for demand models. Second, point and interval estimates of pipe roughnesses are retrieved using least squares to calibrate the hydraulic model, utilizing the demand models from the first step. Finally, the calibrated primal model is transformed into a dual model that intrinsically combines sensor data and network hydraulics. This dual model automatically converts small pressure deviations caused by leaks into sharp and localized signals in the form of virtual leak flows. Analytical derivations of sensitivities with respect to these virtual leak flows are calculated and used to estimate the leakage impulse responses at candidate nodes. Subsequently, we use the dual network to (1)detect the start time of the leaks, and (2)compute the Pearson correlation of pressure residuals, which allows further localization of leaks. This novel dual modeling approach resulted in the highest true-positive rates for leak isolation among all participating teams in the competition.

International audience; This paper used the fusion of an active-set method (ASM) and an interior point method (IPM), with a Newton method, to solve for the steady-state flows, heads, and outflows of a pressure-dependent water distribution system. The outflow constraints which arise from the pressure dependency are handled by an ASM, and the linkflow constraints are handled by an IPM. The authors believe that this is the first time an ASM and an IPM have been used together in this way to solve a real-world optimization problem. Including flow constraints in a network model allows a variety of flow control devices (flow control valves, check valves, pumps) to be modeled efficiently. The new method does not require damping. The separate treatment methods for the two constraint sets mean that the linear inequality constraint qualification condition cannot be violated during iteration, unlike the case in which all the constraints are handled by an ASM. The method was shown to converge quickly on nine case study networks, the largest of which had more than 157,000 links, 150,000 nodes, and 6,000 linkflow constraints. When tested on those same nine networks, an interior point optimizer software package took about 2–4 times longer than the new method for five of the networks, 7 and 9 times as long for two of the networks, and about an equal amount of time for the remaining two networks. For the largest network, the software package took 34 min, whereas the method presented here took 4 min. The generality of the method makes it applicable to network design and management, capacity analysis, and self-cleaning networks.

International audience; In this paper a new method is proposed that solves for the steady state of pressure-dependent models (PDMs) with flow control valves. Rather than model flow devices individually, the method solves the more general problem in which a water distribution system (WDS) has some link flows constrained to lie between upper and lower, or possibly equal, set limits. No heuristics are used to determine device states. The method is shown to be fast, and its effectiveness is demonstrated on PDM WDSs with up to about 20,000 links and 18,000 nodes and 60 link flow constraints, some of which prescribe a fixed flow. The method has applications in network management, network design, and flow control to deal with water distribution where there is insufficient supply.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI [ADD1_IRSTEA]Gestion intégrée de la ressource et des infrastructures; International audience; To date, the hydraulics of water distribution networks are calculated using deterministic models. Because many of the parameters in these models are not known exactly, it is important to evaluate the effects of their uncertainties on the results through uncertainty analysis. For the propagation of uncertain parameters, this article for the first time applies the polynomial chaos expansion to a hydraulic model and compares the results with those from classical approaches like the first-order second-moment method and Monte Carlo simulations. Results presented in this article show that the accuracy of the polynomial chaos expansion is on the same level as the Monte Carlo simulation. Further, it is concluded that due to its computational efficiency, polynomial chaos expansion is superior to the Monte Carlo simulation.

International audience; The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1)time without supply for hospital/firefighting, (2)rapidity of recovery, (3)resilience loss, (4)average time of no user service, (5)number of users without service for eight consecutive hours, and (6)water loss. Three main types of approaches were identified from the submissions: (1)general-purpose metaheuristic algorithms, (2)greedy algorithms, and (3)ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI [ADD1_IRSTEA]Gestion intégrée de la ressource et des infrastructures; International audience; Water distribution networks are critical infrastructures that should ensure the reliable supply of high quality potable water to its users. Numerical models of these networks are generally governed by many parameters for which the exact value is not known. This may be due to a lack of precise knowledge like for consumer demand or due to a lack of accessibility as for the pipe roughness. For network managers, the effect of these uncertainties on the network state is important information that supports them in the decision-making process. This effect is generally evaluated by propagating the uncertainties using the mathematical model. In the past, perturbation, fuzzy and stochastic collocation methods have been used for uncertainty propagation. However, these methods are limited either in the accuracy of the results or the computational effort of the necessary calculations. This paper uses an alternative spectral approach that uses the polynomial chaos expansion and has the potential to give results of comparable accuracy to the Monte Carlo sampling through the definition of a stochastic model. This approach is applied to the hydraulic model of two real networks in order to evaluate the influence of uncertain demands on the water age.

The calculation of hydraulic state variables for a network is an important task in managing the distribution of potable water. Over the years the mathematical modeling process has been improved by numerous researchers for the utilization in new computer applications and the more realistic modeling of water distribution networks. But, in spite of these continuous advances, there are still a number of physical phenomena that cannot be tackled correctly by current models. This paper will take a closer look on the two modeling paradigms given by demand and pressure driven modeling. The basic equations are introduced and parallels are drawn to the optimization formulations from electrical engineering. These formulations guarantee existence and uniqueness of the solution. One of the central questions in the French and German research project ResiWater is the investigation of the network resilience in case of extreme events or disasters. Under such extraordinary conditions where models are pushed beyond their limits we talk of deficient network models. Examples of deficient networks are given by highly regulated flow, leakage or pipe bursts and cases where pressure falls below the vapor-pressure of water. These examples will be presented and analyzed on the solvability and physical correctness of the solution with respect to demand and pressure driven models.

International audience; Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors.

Modeling of water distribution systems is fundamental for the design, analysis and operation of any water network. As with all hydraulic models, water demands are one of the most important input components in the model. However, estimation of the demand parameters is usually complicated due to the stochastic behavior of the water consumptions. Several methods have been proposed for estimating water demands. Most of them have been developed based on given frameworks where the number of unknown parameters is assumed to be equal or less than the number of measurements. The outcomes, therefore, rely on this assumption, which can lead to significant approximation errors in real water distribution systems. The approach proposed in this paper does not require the number of known inputs to be equal to the number of variables. In fact, nodes in the model could each have a different demand pattern. The genetic algorithm approach adopted here shows that the average results of multiple GA runs can estimate the demand patterns at each node. Moreover, the model can also be used to estimate the flow rates and nodal heads at non-measured locations of the water network, although the accuracy of the estimation depends on number, type and location of the measurements. Results are shown and discussed for a literature case study tested for a 24-hour time period.

Sensitivity analysis of the actual hydraulic state of water distribution systems is a valuable tool with number of applications in hydraulic systems analysis. Sensitivity matrices include the information of the response of the hydraulic state variables (flows, pressures) to changes in model parameters (e.g. demands, roughness, control parameters) for a specific hydraulic state of the system. For calculation, there exists in addition to finite difference approximations also exact solutions that include the inversion of the system matrix (the Schur Complement of the Jacobian of the hydraulic network equations). In combination with hydraulic network simulations, the factorization (for example Cholesky matrix decomposition) of the matrix that has already been done by the hydraulic solver in the computation process can be used for the efficient calculation of the inverse matrix. However, for large realworld networks the sensitivity calculation is a time and memory consuming process because the inverse of the system matrix of a connected network has no zero elements. In this paper a new method is presented that allows for the exact calculation of sensitivities of a particular subgraph of interest, the topological minor or supergraph within a water distribution system network graph. Supernodes are the most important nodes in terms of connectivity redundancy within the network graph. Superlinks replace all pipes (links) in series between two supernodes. It will be shown that the sensitivities that are calculated for the subgraph deliver exactly the same results as the inversion of the entire system matrix reduced to supernodes. This paper focuses on the derivation of the equations for the reduced system matrix inversion of the topological subgraph. In addition, the paper includes the proof of equivalence of the matrix inverses for the topological minor subgraph. This inverse represents the fundamental sensitivities of nodal heads and pipe flows with respect to nodal demands in demand driven analysis. The results presented can be extended to other sensitivities, since the matrix inverse in question is included in all other derived parameter sensitivities.

Resume La gestion patrimoniale des infrastructures, au plan operationnel, inclut une surveillance des ouvrages en temps reel, en lien fort avec le controle et la regulation de leur fonctionnement, afin d'assurer la securite des usagers et de l'environnement. Cet article presente les principes et methodes qui sous-tendent les actions au pas de temps fin pour des patrimoines tels que les digues, les barrages et les reseaux d'eau et d'assainissement et montre comment ces actions contribuent de maniere determinante a la connaissance de l'etat du patrimoine.

International audience; Flow control is an important tool for providing an adequate volume of water to all the consumers, especially in the case when natural resources are limited. In real systems different kinds of flow control devices can be distinguished. One of the simplest is the tap control, where the outflow can be directly adjusted by the user. More sophisticated devices are normally used by water supply companies in order to control the flow within the pipe system. Here, the feedback loop is between a flow measuring sensor and the state of the control valve. Using such flow control devices, it is possible to limit the flow through the pipe to a justifiable threshold. Flow control is an important measure providing at least a limited water supply to the entire population, especially in regions that suffer from water scarcity where the demand is higher than the available resources. Thus, flow control could, in combination with proper rehabilitation of leaking pipes, replace the current wide-spread occurrence of intermittent water supply, which poses a high risk for human health (contaminant intrusion due to regular emptying of pipes) as well as the physical state of the system (transients, water hammer). Hydraulic simulation models are invaluable tools for proper planning of distribution network design. The difficulties that result from the presence of control devices in hydraulic simulation models are well reported in the literature. One prominent problem arises from the fact that mathematically flow control devices add inequality constraints to the hydraulic system equations. For example, the hydraulic steady-state can be formulated as the minimum of the convex Content function. Considering flow control devices, the unconstrained nonlinear optimization problem is replaced by a constrained nonlinear optimization problem where the flow control is represented by box constraints for the link flow. As has been previously shown [1] in demand driven analysis, the existence of a feasible flow distribution can be guaranteed if the links with flow control are part of the cotree. If this condition does not hold the non-emptiness of the feasible set can be proved by solving an LP-problem. In the more realistic case of pressure dependent modelling [2, 3], the constrained problem always has a solution if 1.) the consumer behaviour is modelled by pressure dependent demands and 2.) the general box constraints for links with flow control include the point 0. In the first part of this paper, the methods that are used to check the existence of a feasible flow distribution are discussed with respect to their applicability for large networks. Even in the case where the existence of a solution has been proved, the iterative active set method for calculation of the hydraulic steady-state may fail to converge. This is often caused by the linear dependency of the active link flow constraints of and nodal outflow constraints. In the second part of the paper a method for avoiding such linear dependence is presented and discussed with respect to its applicability to large networks. If the pressure deficiency is great, possibly due by large failures such as massive pipe bursts or failure of pumping stations, entire subregions of the network may be without supply. In such cases, there often exists, mathematically speaking, degenerate solutions where the Lagrangian multipliers of the active constraints and the constraints themselves are zero. This paper presents examples for large networks with extensive flow controls as well as proposals on how to deal with such cases numerically.

International audience; A new content-based, box-constrained, active-set projected Newton method is presented that solves for the heads, the pipe flows, and the nodal outflows of a water distribution system in which nodal outflows are pressure dependent. The new method is attractive because, by comparison with the previously published weighted least-squares energy and mass residuals (EMR) damped Newton method, (1) it typically takes fewer iterations, (2) it does not require damping, (3) it takes less wall-clock time, (4) it does not require the addition of any virtual elements, and (5) it is algorithmically easier to deal with. Various pressure-outflow relationships (PORs), which model nodal outflows, were considered and two new PORs are presented. The new method is shown, by application to eight previously published case study networks with up to about 20,000 pipes and 18,000 nodes, to be up to five times faster than the EMR method and to take between 34% and 70% fewer iterations than the EMR method.

Water distribution networks are critical infrastructures that should ensure the reliable supply of high quality potable water to its users. Numerical models of these networks are generally governed by many parameters for which the true value is unknown. This may be due to a lack of knowledge like for consumer demand or due to a lack of accessibility as for the pipe roughness. For network managers, the effect of these uncertainties on the network state is important information that supports them in the decision-making process. This effect is generally evaluated by propagating the uncertainties using the mathematical model. In the past, perturbation and stochastic collocation methods have been used for uncertainty propagation. However, these methods are limited either in the accuracy of the results or the complexity of the calculation. This paper uses an alternative spectral approach with the polynomial chaos expansion that has the potential to give comparable results to the Monte Carlo sampling through the definition of a stochastic model. This approach is applied to the model of a water distribution network in order to evaluate the influence of uncertain demands on the water age.

The reliability of a water distribution system is highly dependent on the management of its pipeline network. A pipe or a portion of the network can be isolated for inspection, maintenance,...

1st International WDSA / CCWI 2018 Joint Conference, Kingston, CAN, 23-/07/2018 - 25/07/2018; International audience; Water distribution systems (WDSs) are an essential part of the urban infrastructure, which consist of a labyrinth of networks of pipes, tanks, pumps and monitoring systems. In order to provide water of appropriate quantity, quality and pressure to customers, a WDS needs to be stable and reliable. Isolation valves, which are installed along the pipelines, are designed to provide system reliability. By closing related isolation valves, a pipe or a portion of the network can be isolated for inspection, maintenance and replacement without disrupting other parts of the system. However, these isolation valves may cause adverse operating conditions in the network if some of the valves in the system are active (partially or fully closed) while their statuses are unknown (due to poor or non-existent documentation, valves left closed inadvertently, errors in data transfer or valve mechanical failure, etc.). This can be observed by a disagreement between the measured pressure and flow values from the real system and results from its corresponding hydraulic simulation model. Calibration of these unknown valve statuses is, therefore, a necessary step that has to be implemented to ensure the reliability of the system. This paper introduces a hybrid method for the identification of unknown partially/fully closed valves in a water distribution network. An optimization problem is formulated for unknown valve statuses and solved by application of three sequentially applied methods, which include: a local sensitivity analysis, the application of genetic algorithms and the application of the Levenberg-Marquardt algorithm. In order to eliminate the valves that are unable to be localized by the measurement data, first, the sensitivity of the flow rates and nodal heads at measurement locations with respect to the change in the minor losses of the valves is computed. Following, a genetic algorithm combined with an extended period simulation is applied to preliminarily identify the locations of the partially/fully closed valves and their degree of opening of the valves. Finally, the application of the Levenberg- Marquardt algorithm has been implemented to correct the results from the GA model. A water distribution network is used to demonstrate the applicability of the proposed methodology. Results show that the model is able to provide relatively good approximation of the locations of unknown partially/fully closed valves as well as their corresponding settings.

International audience; The forest core partitioning algorithm (FCPA) and the fast graph matrix partitioning algorithm (GMPA) have been used to improve efficiency in the determination of the steady-state heads and flows of water distribution systems that have large, complex network graphs. In this paper, a single framework for the FCPA and the GMPA is used to extend their application from demand dependent models to pressure dependent models (PDMs). The PDM topological minor (TM) is characterized, important properties of its key matrices are identified, and efficient evaluation schemes for the key matrices are presented. The TM captures the network's most important characteristics: It has exactly the same number of loops as the full network, and the flows and heads of those elements not in the TM depend linearly on those of the TM. The inverse of the TM's Schur complement is shown to be the top, left block of the inverse of the full system Jacobian's Schur complement, thereby providing information about the system's essential behavior more economically than is otherwise possible. The new results are applicable to other nonlinear network problems, such as in gas, district heating, and electrical distribution.

It has been well established in several experimental and modeling studies that leak areas are often not fixed, but vary as linear functions of pressure. Replacing this linear equation into ...

The core of Resiwater project is the development of new sensors and secured sensor networks, self- learning monitoring tools, robust simulation models and vulnerability and resilience assessment tools. To ensure realistic and relevant application on field for water suppliers the project is end user oriented. Increasing the resilience of water distribution systems is a strong target of the project. Consequently the benefits of developed tools have to be investigated and assessed by the perspective of realistic water distribution system failures. Therefore, WP1 aims to specify the use cases with scenarios for each end user (WP1.1) to evaluate vulnerability and resilience of a Water Distribution System (WDS) for the use cases (WP1.3) and to evaluate new tools of the project by the mean of the use cases (WP1.2) as described in the present report. First, the test results for online water quality measurement at the TZW scale network are reported. Then, the self-learning methods and tools are tested for different configurations at the ResiWater three water utility.

One way of reducing water leakage, pipe bursts and water consumption in a water distribution system (WDS) is to manage the pressure to be as low as possible. This can be done by adjusting a pressure control valve (PCV) in real time in order to keep the pressure low and constant at a remote consumer location, by using a controller. When such smart infrastructure is implemented in a WDS, the choice of controller is important. Recently proposed controllers which use the flow rate in the PCV are more resilient to different WDS conditions than conventional proportional control. Here, the former controllers which adjust the head loss coefficient of the PCV are considered; either with a tunable parameter or parameter less. For two parameter-less controllers new mathematical expressions are derived for the deviation of the pressure from constant pressure in a WDS with one PCV. The deviation is proportional to the head loss over the PCV, which varies for different WDSs. Also, the deviation is proportional to the time-step between successive controller iterations. Hence the time-step can be chosen to reduce the deviation to a preselected level. Moreover, the deviation is proportional to the scale-independent rate of change of flow rate in the PCV. In addition, it is shown that for the two ‘constant flow’ controllers, the flow does not have to be known accurately. Hence, although the flow needs to be known, it can be known with significant uncertainty, enhancing the practical use of these controllers.

The aim of work package 3 is the development of an enhanced self-learning monitoring and event detection module. In summary the principal items of work package 3 are: 1) Development of a data analysis platform for the integration of the heterogeneous sensor measurements 2) Development of self-learning monitoring and event detection algorithms. These algorithms will take into account the spatial distribution of the measurements. 3) Integration of online plausibility checks for the results of the algorithms 4) Deployment of tools for the launch of the enhanced event detection module. This deliverable describes the integration of hydraulic information into the event detection module with the aim to reduce the rate of false positive alarms. Three main concepts are proposed: - Use of backward transit time between two sensors; - Knowledge of source provenance; - Aggregation of clusters of similar water quality for spatial segmentation.

This deliverable report aims to analyse the three case studies from CUS Eurométropole Strasbourg with the help of the ResiWater modelling solutions. The modelling solutions were developed in the WP4 (Robust hydraulic simulation tools) and in the WP5 (Development of Tools for Assessing WDS Vulnerability, Resilience and Robustness and Decision Support for Design) for the criticality and resilience indicators. The three case studies are described in the D1.1 report. Two phases were defined. The first one corresponds to the current state at the pilot water utilities. Vulnerability and resilience modelling tools are used to evaluate the level of criticality regarding each of the selected used cases. In phase two, it is evaluated how the new sensors, monitoring tools, robust models and assessment tools can improve the overall resilience of the water infrastructures. A plan with concrete measures at the water utilities at several levels will be prepared (e.g. instrumentation and installation of new sensor systems, new simulation and training tools and planning and preparedness tools).

Supplying modern water systems in smart cities requires the ability to monitor water quality in the production plants and the distribution network. Protection against accidental or intentional events is usually based on an Early Warning Detection System (EWDS) to minimize the impact of any contamination [1]. A major issue is positioning online sensors along the water distribution network to ensure the best protection at minimum cost. Several contributions for tackling such problem have been proposed during the last decade, including a scientific challenge comparing 14 methodologies [2] and two reviews of about 150 articles [3,4]. Currently there is no consensus about algorithms or design objectives to use, and such a problem is NP-hard [5,6]. In this paper, a greedy approach is proposed to near-optimally solve the sensor placement problem dealing with large-scale water systems. This methodology is designed to integrate both the specificity of the studied network (expert/prior knowledge) and flexibility related to the uncertainty of the nature, time, and duration of contamination injections. The method is illustrated to minimize the expected fraction of the exposed population on the largest network in France (about 100,000 nodes, 600,000 connections, above 8,000 km of pipes). Costly approaches in terms of computation time, such as MIP (Mixed-Integer Programming) and exhaustive search cannot scale to large networks. A sensitivity analysis is presented using the greedy approach on a sub-network which leads to choose the number of sufficient contamination simulations and the concentration threshold used to detect contaminations. The extensive experiments allow us to highlight the effectiveness and the rapidity of the proposed approach.

International audience; This paper considers the sectoring of a large water distribution network into district metered areas (DMAs) and simultaneously optimizes rehabilitation of the network with new pipes, control valves, and storage tanks. Because available water resources are much lower in the dry season, both the design and operational settings are optimized to satisfy water-demand, water-quality, and pressure constraints, as well as efficiency indices under stringent conditions. Because of the heterogeneity of the multiple decision variables and the complicated way they interact through the multiple objectives (some complimentary and some conflicting), it is not possible to fully automate the simultaneous sectorization, rehabilitation, and operational optimization. Therefore, a multistage approach is used where engineering judgment and network graph simplification and visualization tools are used to find a good feasible solution that serves as a first guess for further optimization of sectors and operational settings, to achieve feasible solutions with better cost of implementation, demand similarity among DMAs, and better pressure uniformity in operations. A multiobjective agent swarm optimization framework is used to iteratively change the sectors at the boundaries. For the final configuration, sequential linear programming is used to find optimal valve and pump settings.

Accurate modeling of water distribution systems is fundamental for planning and operating decisions in any water network. One important component that directly affects model accuracy is kno...

10ème Congrès international EWRA Panta Rhei, Athènes, GRC, 05-/07/2017 - 09/07/2017; International audience; The main objective of a water distribution network (WDN) is to deliver the required amount of water to the customer under a certain threshold of the desired pressure and quality. These networks are critical infrastructures that should face multiple and continuous changes and even abnormal events that alter their normal service provision. Water utility managers require modelling tools to be able to predict how the WDN will perform during disruptive events and understand how the system can better absorb them. Assessing and enhancing resilience in water infrastructures is a crucial step towards more sustainable urban water management. Several resilience key performance indicators (RKPIs) have been suggested to quantify and assessing WDNs resilience. This work proposes a structured classification for measuring and understanding the supply system by means of RKPIs. The proposed classification is based on a three-stage resilience concept which includes absorptive, adaptive, and restorative stages. This classification attempts to provide engineers, modellers, and managers with structured tools which allow a comprehensive analysis of crisis management case studies in order to enhance the WDN resilience. As the resources in supply are usually limited, recovery phases have a crucial role in resilience enhancing, while under sufficient availability of resources, deploying redundancy, making critical components stronger and ensuring a rapid recovery are all effective responses of the system.

International audience; Water distribution networks are subject to potential intentional contamination to cause harm to the consumer. Reliable transport models are needed to detect, trace and follow any contaminant transported inside the network. For now, the transport of contaminants in pipes has been mostly modeled assuming perfect mixing conditions at T-junction. However, some studies have shown that it is not always the case when crosses or double T-junctions are involved. In this paper an imperfect mixing at Double T-junction model is developed considering 3-D mixing behavior. A reduced model is then constructed in the form of a 1-D law to apply it to current 1-D transport models for water distribution networks. The methodology to create such law is detailed and can be applied to any reduced model problem including multi parameters and time consuming simulations. The procedure is composed of three steps: first calibrate the Kriging interpolation method parameters; then couple it with the Delaunay triangulation method to select simulation points with maximum gain; and finally implement a 1-D law based on the simulation results and the interpolation.

International audience; The problem of sensor placement for early-warning detection systems is a topical issue for industry and utilities who want to equip their networks with such technology. Solving the problem entails finding the best sensor locations that optimize a criterion such as detection rate or time to detection. Few methods exist concerning sensor placement that optimize the result of a source identification method. This paper fills the gap by coupling an adjoint source identification method and a Monte Carlo sensor placement algorithm. The first one is treated through the use of a backtracking algorithm. It uses binary responses at sensors to calculate the ranked list of potential contamination location nodes and contamination times. A criterion is then defined based on the source identification accuracy and specificity. Finally, two optimizing methods that maximize this criterion are proposed: a greedy algorithm and a local search algorithm, which are both coupled with a Monte Carlo method to give the locations of sensors that are the best suited for allocating the source of a contamination. These methods are tested on a 2,500-node network to evaluate their efficiency.

International audience; The first-order sensitivity matrices (matrices of sensitivity or influence coefficients) have application in many areas of water distribution system analysis. Finite-difference approximations, automatic differentiation, sensitivity equations, and the adjoint method have been used in the past to estimate sensitivity. In this paper new, explicit formulas for the first-order sensitivities of water distribution system (WDS) steady-state heads and flows to changes in demands, resistance factors, roughnesses, relative roughnesses, and diameters are presented. The formulas cover both pressure-dependent modeling (PDM) and demand-dependent modeling (DDM) problems in which either the Hazen-Williams or the Darcy-Weisbach head-loss models are used. Two important applications of sensitivity matrices, namely calibration and sensor placement, are discussed and illustrative examples of the use of sensitivity matrices in those applications are given. The use of sensitivity matrices in first-order confidence estimation is briefly discussed. The superior stability of the PDM formulation over DDM is established by the examination of the sensitivity matrices for the same network solved by both model paradigms. The sensitivity matrices and the key matrices in both the global gradient method for DDM problems and its counterpart for PDM problems have many elements in common. This means that the sensitivity matrices can be computed at marginal cost during the solution process with either of these methods.

This report describes different methods for modelling of pressurized water supply networks with consideration of pressure dependent demands (PDM: Pressure Driven Modelling). The capability of a hydraulic network simulation software to correctly deal with pressure dependent demands is essential for the development in ResiWater. In case of system failures that might be caused by pipe bursts, natural disasters or malevolent attacks by humans, the pressure is reduced due to decreased capacity of the system. In such case, the common DDM solvers (DDM: Demand Driven Modelling) deliver unrealistic results with negative pressures while maintaining the defined outflows at the side of the customers. PDM modelling fixes this problem by automatically reducing the demand when the pressure drops under the minimum service pressure. The deliverable starts with an overview of existing approaches to PDM. Problems with convergence are well documented in literature. Two different methods for solution are proposed in the main part. The first includes a step size control based on Goldstein criterion. It has been published already in a journal that's why it is not presented in detail in the deliverable. The second approach contains the so-called Content Model formulation of the PDM problem that delivers also statements about existence and uniqueness of the solution. For numerical calculation, an active set method is proposed. The methods have been implemented in Matlab and successfully tested for several test networks with up to 20.000 nodes under strong PDM conditions (almost all nodes are in PDM mode). Small examples exist also in Excel. The approach will be also implemented in Porteau and SIR 3S as part of the reliable hydraulic system solver (task 4.4). Tests were made in SIR 3S for the BWB pilot networks. The deliverable ends with Conclusion.

Water quality of water distribution networks may be assessed using models. Single-species transport-reaction equations without interaction between indicators are often sufficient to reproduce the observed values. The objective of this paper is to present a new numerical scheme, which transforms water quality equations into a unique simple transport equation to solve. An advection-reaction equation is derived from incompressible Navier-Stokes for modeling the water temperature in the network. A quality solver was realized using Matlab and validated on small and medium-sized networks. As a result the same subroutine code is called for calculating the evolution of several water quality indicators.

International audience; The standard formulation of the hydraulic network equations incorporates a power function for modeling pressure-dependent consumption such as leakage. However, recent research has shown that the FAVAD leakage model more accurately accounts for the behavior of leaks in practice. The objective of this paper is to propose a method for solving the hydraulic network equations incorporating the FAVAD model. An energy minimization problem is used to prove the existence and the uniqueness of the solution to this problem, and to provide the basis for a robust solver. A damped Newton algorithm is proposed for solving the system equations.

New sensors are currently being installed in water distribution networks, which give data every few minutes on water quantity and quality. How to manage the data to produce alarms, to get reliable water quality and water quantity models and to take appropriate countermeasures are the principal questions the SMaRT-OnlineWDN project focuses on. This paper discusses how to enhance hydraulic and transport models and adapt them to the online use and security. Firstly, the transport model is enriched by adding incomplete junction mixing at nodes, axial dispersion and diffusion. Then the hydraulic model is also improved adopting transient formulation, graph simplification and online calibration of demands. Finally, source identification algorithms adapted for real-time are developed.

In this paper, the concept of graph decomposition is used for simplification and enhancement of solution algorithms for different problems related to water supply network security and management. Three examples including sensor placement, source identification and decision support for response actions are presented. The decomposition concept can be used as general framework for adaptive modeling. Based on one comprehensive all pipe model of the entire supply system, the most appropriate level of accuracy can be chosen. Unlike conventional network aggregations and simplification algorithms, the proposed model simplifications do not have the problem of losing the original information. The method is suited for being used within a real-time environment where calculation time is one of the most important requirements for practical applicability.

International audience; Modern water distribution networks (WDNs) are complex and difficult to manage due to increased level of urbanization, varying consumer demands, ageing infrastructure, operational costs, and inadequate water resources. The management problems in such complex networks may be classified into short-term, medium-term, and long-term, depending on the duration at which the problems are solved or considered. To address the management problems associated with WDNs, mathematical models facilitate analysis and improvement of the performance of water infrastructure at minimum operational cost, and have been used by researchers, water utility managers, and operators. This paper presents a detailed review of the management problems and essential mathematical models that are used to address these problems at various phases of WDNs. In addition, it also discusses the main approaches to address these management problems to meet customer demands at the required pressure in terms of adequate water quantity and quality. Key challenges that are associated with the management of WDNs are discussed. Also, new directions for future research studies are suggested to enable water utility managers and researchers to improve the performance of water distribution networks.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI14th CCWI international conference, Computing and Control in Water Industry, Amsterdam, NLD, 07-/11/2016 - 09/11/2016; International audience; Water Distribution Systems (WDSs) are constantly exposed to deliberate or accidental contaminations or may undergo a partially or full system collapse. In this paper we present the goals and preliminary results of the French-German project ResiWater (2016). The project ResiWater aims to develop tools to prepare water utilities for crisis management and enhance their resilience with regards to three specific case studies: collapse of WDS, water quality deterioration and cascade effects between water, energy and IT infrastructures.

8th International Congress on Environmental Modelling and Software, Toulouse, FRA, 10-/07/2016 - 14/07/2016; International audience; This paper proposes a new methodology to analyze images from subsoil surveys obtained by using ground penetrating radar (GPR) as a non-destructive method. The aim is to advance towards automatic GPR image interpretations. The main idea is to promote the inclusion of these non- destructive technologies as support in technical management in large-scale systems such as water distribution systems (WDSs). The methodology proposed in this paper uses pre-processing techniques based on a multi-agent approach and analysis of the properties of the obtained groups. In addition, a first classification (via perceptron) of the selected property in the groups is performed. The work is based on GPR studies performed on controlled laboratory conditions; two kinds of test conditions are raised. The first kind pursues capturing objects in GPR images to favor feature extraction thereof, since these tests are used to develop the proposed methodology. The second kind of tests seeks to assess the feasibility of the proposed methodology implementation, while the interaction of the captured objects with other objects and with the environment is evaluated. The results of this study are promising in regard to the selection of areas in GPR images via automatic interpretation that allows the extraction of relevant features for WDS networks. In addition, with the proposed methodology, the use of GPR is promoted by non-highly skillful and expert operators in GPR image interpretation.

International audience; Hydraulic models have been widely used for design, analysis, and operation of water distribution systems. As with all hydraulic models, water demands are one of the main parameters that cause the most uncertainty to the model outputs. However, the calibration of the water demands is usually not feasible attributable to the limited quantity of available measurements in most real water networks. This paper presents an approach to calibration of the demand multiplier factors under an ill-posed condition where the number of measurements is less than the number of parameter variables. The problem is solved using a genetic algorithm (GA). The results show that not only is the GA able to match the calibrated values at measured locations, but by using multiple runs of the GA model, the flow rates and nodal heads at nonmeasured locations can be estimated. Three case studies are presented as an illustration of the problem. The first case study is a small network that demonstrates the calibration model. The second case study shows a comparison between the genetic algorithm model and a singular value decomposition model. The last case study is a large network that allows for practical considerations in applying the proposed methodology to a realistic context.

International audience; In the past, pressure dependent models (PDM) have suered from convergence diculties. In this paper conditions are established for the existence and uniqueness of solutions to the PDM problem posed as two optimization problems, one based on weighted least squares (WLS) and the other based on the co-content function. A damping scheme based on Goldstein's algorithm is used and has been found to be both reliable and robust. A critical contribution of this paper is that the Goldstein theorem conditions guarantee convergence of our new method. The new methods have been applied to a set of eight challenging case study networks, the largest of which has nearly 20,000 pipes and 18,000 nodes, and are shown to have convergence behaviour that mirrors that of the Global Gradient Algorithm on demand dependent model problems. A line search scheme based on the WLS optimization problem is proposed as the preferred option because of its smaller computational cost. Additionally, various consumption functions, including the Regularized Wagner function, are considered and four starting value schemes for the heads are proposed and compared. The wide range of challenging case study problems which the new methods quickly solve suggests that the methods proposed in this paper are likely to be suitable for a wide range of PDM problems.

International audience; Leakage represents a large part of the supplied water in Water Distribution Systems (WDS). Consequently, it is important to develop some efficient strategies to manage such a phenomenon. In this paper an improved formulation of the hydraulic network equations that incorporate pressure-dependent leakage, is presented and validated. The formulation is derived from the Navier-Stokes equations and solved using an adequate splitting method. Then, this formulation is used to study a constrained optimization problem with the objective to minimize the distributed water volume reducing the leakage. The problem is described and validated for academic case studies and real networks.

Municipal storage tanks are used to balance differences in supply and demand. Tanks have traditionally been sized based on deterministic criteria for balancing, fire, and emergency storage components. In this paper a stochastic analysis method is proposed to model both the deterministic and probabilistic components of consumer demand, fire demand, and pipe failures in water distribution systems. The method estimates a number of tank reliability criteria as functions of tank capacity, which provide a site-specific way of determining the required tank capacity based on user-defined reliability criteria. The method is illustrated by applying it to a “typical” water supply system. It was found that the tank failure duration follows a Weibull distribution. The tank failure rate was found to be very sensitive to tank capacity and can be described with an exponential distribution. It is proposed that one failure in 10 years under seasonal peak conditions is used as a design criterion for tank sizing. In many cas...

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI; International audience; The vulnerability analysis of our societies to major disturbances is of outmost importance in the fields of Infrastructure Asset Management (IAM). Several methodologies have already been developed to assess the vulnerability of critical infrastructures (CIs). Supply networks (water, gas, energy…) are also critical infrastructures (called Critical Networks or CNs hereafter), and should be considered with specific care due to (a) their complexity and spatial extent, (b) their role in providing other CIs with resources. In a first part, we present our framework for vulnerability and resilience in the French-German project “ResiWater” (Innovative Secure sensor Networks and Model-based Assessment Tools for Increased Resilience of water Infrastructures), funded by ANR and BMBF. We will then illustrate the various approaches to vulnerabilities. Lastly, we will draw our conclusions, which will be the guidelines for our project.

International audience; Water utilities have started to install water quality sensors to protect their network against intentional and accidental contamination events. In this context, for taking appropriate action, not only are early-warning detection systems important, but so is the identification of the contamination source, and knowledge of the present and future contamination extent. For the latter there is a need for reliable and updated network models. The main objective of this paper is to specify which performance criteria should be considered to place water quality and water quantity sensors for both early detection and model calibration. Firstly, a brief bibliographical review is given for optimal sensor location design. Next, formulations and objectives for early-warning detection are proposed. Problem formulations that aim to minimize the estimator variance for calibration are then specified. Finally, the method is applied on the real WDN system of the CUS water service (1,000 km, 25,000 nodes and 45,000 customers).

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI; National audience; Il semble important, dans le travail sur les réseaux d’eau potable, de bien connaître leur vulnérabilité et en particulier en distinguant la vulnérabilité structurelle (impact sur le patrimoine, les infrastructures du réseau), la vulnérabilité fonctionnelle (impact sur le service rendu aux usagers) et la vulnérabilité externe (impact au-delà du service d’eau lui-même, sur l’environnement ou les activités mécaniques).