Efficient Technique for Pipe Roughness Calibration and Sensor Placement for Water Distribution Systems

Wéber, Richárd; Hős, Csaba

doi:10.1061/(asce)wr.1943-5452.0001150

Cited by 28 publications

(16 citation statements)

References 42 publications

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“…The C factor can be considered as a static parameter [54] unless maintenance activities are employed to restore it. Estimating the C factor usually requires a large amount of data [54], [55], and an empirical equation based on only a few parameters is often useful for estimating the C factor [38], [51], [56]. In terms of practical applications, this simplification plays a major role in engineering judgment.…”

Section: A Hydraulic Geodesic Indexmentioning

confidence: 99%

Shortest-Path-Based Two-Phase Design Model for Hydraulically Efficient Water Distribution Network: Preparing for Extreme Changes in Water Availability

Lee

Jung

2021

IEEE Access

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Environmental issues can cause changes in source water availability in water distribution networks (WDNs). Thus, an efficient connection between the source and consumers is important for securing water serviceability, which can generally be achieved by minimizing energy losses. In this study, a novel two-phase design (TPD) model is proposed to design an energy-efficient WDN by maximizing a hydraulic geodesic index (HGI), which is the weighted shortest path from the source to the demand node. Before applying the TPD model for WDN design, a correlation analysis between the system HGI, hydraulic performance, and graph theory indices is conducted using 33 J-City networks to verify the proposed HGI. Next, the TPD model is used to determine the optimal layout of the grid network (Phase I). Based on this layout, the optimal diameter set is identified in Phase II. The TPD is thereafter compared with the traditional single-phase design (SPD) model, which determines the optimal layout and diameter simultaneously, and a least-cost model for each phase in the grid network layout and pipe-sizing problem. The correlation analysis clearly indicates that the system HGI with the weighted graph theory successfully determines the hydraulic performance without any hydraulic analysis. Furthermore, TPD is advantageous for designing energy-efficient, hydraulically and structurally sustainable, and resilient networks, as compared to SPD and the least-cost model. The TPD model is expected to provide a better opportunity to prepare for extreme water availability changes by enhancing the hydraulic performance and efficiency through a better connection between the source and nodes.

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Section: A Hydraulic Geodesic Indexmentioning

confidence: 99%

Shortest-Path-Based Two-Phase Design Model for Hydraulically Efficient Water Distribution Network: Preparing for Extreme Changes in Water Availability

Lee

Jung

2021

IEEE Access

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“…In addition, node pressures are more sensitive to leaks than flow rates, which is why many localization algorithms are based primarily on pressure measurements. The problem of sensor placement is closely related to other WDN management problems, such as the state estimation of the network [4][5][6], model calibration [7,8], water quality monitoring such as detection of contaminants and cyberattacks [9][10][11][12][13][14][15], among others. Nevertheless, the present work focuses on the context of leak detection and localization as discussed in [16,17].…”

Section: Introductionmentioning

confidence: 99%

Pressure Sensor Placement for Leak Localization in Water Distribution Networks Using Information Theory

Santos‐Ruiz

López‐Estrada

Puig

et al. 2022

Sensors

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This paper presents a method for optimal pressure sensor placement in water distribution networks using information theory. The criterion for selecting the network nodes where to place the pressure sensors was that they provide the most useful information for locating leaks in the network. Considering that the node pressures measured by the sensors can be correlated (mutual information), a subset of sensor nodes in the network was chosen. The relevance of information was maximized, and information redundancy was minimized simultaneously. The selection of the nodes where to place the sensors was performed on datasets of pressure changes caused by multiple leak scenarios, which were synthetically generated by simulation using the EPANET software application. In order to select the optimal subset of nodes, the candidate nodes were ranked using a heuristic algorithm with quadratic computational cost, which made it time-efficient compared to other sensor placement algorithms. The sensor placement algorithm was implemented in MATLAB and tested on the Hanoi network. It was verified by exhaustive analysis that the selected nodes were the best combination to place the sensors and detect leaks.

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“…Many techniques have been proposed to estimate the nodal water demand. Examples include evolutionary algorithm(EA) based methods (Dini and Tabesh 2014;Di Nardo et al 2015), explicit methods (Du et al 2015), singular value decomposition (SVD) methods (Weber and Hos 2020), and data assimilation methods (Bragalli et al 2016;Chu et al 2021a;Kang and Lansey 2009;Qin and Boccelli 2019;Rajakumar et al 2019;Zhou et al 2018). For the EA-based methods, the nodal water demand is estimated by minimizing the deviation from the model-simulated values to the measurements.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Approach for Nodal Water Demand Estimation in Large-scale Water Distribution Systems

Chu

Zhang

Zhou

et al. 2022

Water Resour Manage

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Real-time modeling of the water distribution system (WDS) is a critical step for the control and operation of such systems. The nodal water demand as the most important time-varying parameter must be estimated in real-time. The computational burden of nodal water demand estimation is intensive, leading to inefficiency for the modeling of the large-scale network. The Jacobian matrix computation and Hessian matrix inversion are the processes that dominate the main computation time. To address this problem, an approach to shorten the computational time for the real-time demand estimation in the large-scale network is proposed. The approach can efficiently compute the Jacobian matrix based on solving a system of linear equations, and a Hessian matrix inversion method based on matrix partition and Iterative Woodbury-Matrix-Identity Formula is proposed. The developed approach is applied to a large-scale network, of which the number of nodal water demand is 12523, and the number of measurements ranging from 10 to 2000.Results show that the time consumptions of both Jacobian computation and Hessian matrix inversion are significantly shortened compared with the existing approach.

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Efficient Technique for Pipe Roughness Calibration and Sensor Placement for Water Distribution Systems

Cited by 28 publications

References 42 publications

Shortest-Path-Based Two-Phase Design Model for Hydraulically Efficient Water Distribution Network: Preparing for Extreme Changes in Water Availability

Shortest-Path-Based Two-Phase Design Model for Hydraulically Efficient Water Distribution Network: Preparing for Extreme Changes in Water Availability

Pressure Sensor Placement for Leak Localization in Water Distribution Networks Using Information Theory

An Efficient Approach for Nodal Water Demand Estimation in Large-scale Water Distribution Systems

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