scholarly journals Incomplete Mixing Model at Cross-Junctions in Epanet by Polynomial Equations

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 453
Author(s):  
Daniel Hernández Cervantes ◽  
P. Amparo López-Jiménez ◽  
José Antonio Arciniega Nevárez ◽  
Xitlali Delgado Galván ◽  
Martín Rubén Jiménez Magaña ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Distribution ◽  
Distribution Networks ◽  
Mixing Model ◽  
Simulation Software ◽  
Polynomial Equations ◽  
Water Quality Simulation ◽  
Incomplete Mixing ◽  
Flow Mixing ◽  
Advective Mixing

In Water Distribution Networks (WDN), the water quality could become vulnerable due to several operational and temporal factors. Epanet is a hydraulic and water quality simulation software, widely used, to preserve the control of chemical disinfectants in WDN among other capabilities. Several researchers have shown that the flow mixing at Cross-Junctions (CJs) is not complete as Epanet assumes for the cases of two contiguous inlets and outlets. This paper presents a methodology to obtain the outlet concentrations in CJs based on experimental scenarios and a validated Computational Fluid Dynamics (CFD) model. In this work, the results show that the Incomplete Mixing Model (IMM) based on polynomial equations, represents in a better way the experimental scenarios. Therefore, the distribution of the concentration could be in different proportions in some sectors of the network. Some comparisons were made with the complete mixing model and the Epanet-Bulk Advective Mixing (BAM), obtaining relative errors of 90% in some CJs.

scholarly journals Optimal Water Quality Sensor Placement by Accounting for Possible Contamination Events in Water Distribution Networks

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1999
Author(s):  
Malvin S. Marlim ◽  
Doosun Kang
Keyword(s):  
Water Quality ◽  
Water Distribution ◽  
Sensor Placement ◽  
Pso Algorithm ◽  
Distribution Networks ◽  
Fair Value ◽  
Water Distribution Networks ◽  
Optimization Approach ◽  
Protection Measure ◽  
Contamination Events

Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.

Improving water age estimation in a drinking water distribution network by field study and digital modeling

2021 ◽  
Author(s):  
Jon Kristian Rakstang ◽  
Michael B. Waak ◽  
Marius M. Rokstad ◽  
Cynthia Hallé
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Network Model ◽  
Age Estimation ◽  
Water Distribution ◽  
Distribution Network ◽  
Distribution Networks ◽  
Plate Count ◽  
Water Age ◽  
Drinking Water Distribution

<p>Municipal drinking water distribution networks are complex and dynamic systems often spanning many hundreds of kilometers and serving thousands of consumers. Degradation of water quality within a distribution network can be associated to water age (i.e., time elapsed after treatment). Norwegian distribution networks often consist of an intricate combination of pressure zones, in which the transport path(s) between source and consumer is not easily ascertained. Water age is therefore poorly understood in many Norwegian distribution networks. In this study, simulations obtained from a water network model were used to estimate water age in a Norwegian municipal distribution network. A full-scale tracer study using sodium chloride salt was conducted to assess simulation accuracy. Water conductivity provided empirical estimates of salt arrival time at five monitoring stations. These estimates were consistently higher than simulated peak arrival times. Nevertheless, empirical and simulated water age correlated well, indicating that additional network model calibration will improve accuracy. Subsequently, simulated mean water age also correlated strongly with heterotrophic plate count (HPC) monitoring data from the distribution network (Pearson’s R= 0.78, P= 0.00046), indicating biomass accumulation during distribution—perhaps due to bacterial growth or biofilm interactions—and illustrating the importance of water age for water quality. This study demonstrates that Norwegian network models can be calibrated with simple and cost-effective salt tracer studies to improve water age estimates. Improved water age estimation will increase our understanding of water quality dynamics in distribution networks. This can, through digital tools, be used to monitor and control water age, and its impact on biogrowth in the network.</p>

scholarly journals Appraisal of water quality indices for service reservoirs in water distribution networks

2020 ◽  
Vol 81 (8) ◽  
pp. 1606-1614 ◽  
Author(s):  
M. S. Nyirenda ◽  
T. T. Tanyimboh
Keyword(s):  
Water Quality ◽  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Sampling Point ◽  
Quality Indices ◽  
Water Quality Indices ◽  
State Of Water ◽  
Pollution Loads

Abstract The use of water quality indices to aggregate pollution loads in rivers has been widely studied, with researchers using various sub-indices and aggregation methods. These have been used to combine various quality variables at a sampling point in a river into an overall water quality index to compare the state of water quality in different river reaches. Service reservoirs in a water distribution network, like rivers, have complex mixing mechanisms, are subjected to various water quality variables and are variably sized and sited. Water quality indices and the relevant sub-indices are formulated here and applied to service reservoirs within a water distribution network. This is in an attempt to compare holistically the performance of service reservoirs in solutions of optimisation algorithms with regards to water quality.

scholarly journals Topological clustering as a tool for planning water quality monitoring in water distribution networks

2015 ◽  
Vol 15 (5) ◽  
pp. 1011-1018 ◽  
Author(s):  
Jonas Kjeld Kirstein ◽  
Hans-Jørgen Albrechtsen ◽  
Martin Rygaard
Keyword(s):  
Water Quality ◽  
Decision Support ◽  
Network Model ◽  
Water Distribution ◽  
Water Movement ◽  
Decision Support Tool ◽  
Water Quality Monitoring ◽  
Distribution Networks ◽  
Quality Monitoring ◽  
Support Tool

Topological clustering was explored as a tool for water supply utilities in preparation of monitoring and contamination contingency plans. A complex water distribution network model of Copenhagen, Denmark, was simplified by topological clustering into recognizable water movement patterns to: (1) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist identification of potential contamination and affected consumers in contamination cases. Although still in development, the method shows potential for assisting utilities during planning of monitoring programs and as decision support tool during emergency contingency situations.

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