Multiple Paths Leak Localization System in Water Distribution Network

2020 ◽  
Author(s):  
Wen Hao Png ◽  
Chang Hong Pua ◽  
Mau Luen Tham
Keyword(s):  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Localization System ◽  
Multiple Paths ◽  
Leak Localization

EFFICIENT CHLORINATION SCHEDULE FOR A WATER DISTRIBUTION NETWORK WITH MULTIPLE PUMPING STATIONS

2017 ◽  
Vol 16 (5) ◽  
pp. 1071-1079 ◽  
Author(s):  
Andrei-Mugur Georgescu ◽  
Sanda-Carmen Georgescu ◽  
Remus Alexandru Madularea ◽  
Diana Maria Bucur ◽  
Georgiana Dunca
Keyword(s):  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Pumping Stations

A study on appropriate investment of pipeline rehabilitation for water distribution network

2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Supply ◽  
Water Distribution ◽  
Ad Hoc ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Optimal Basis ◽  
Model Case

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.

Whole life costing: application to water distribution network

2003 ◽  
Vol 3 (1-2) ◽  
pp. 87-93 ◽  
Author(s):  
M. Engelhardt ◽  
D. Savic ◽  
P. Skipworth ◽  
A. Cashman ◽  
A. Saul ◽  
...  
Keyword(s):  
Network Management ◽  
Asset Management ◽  
Water Distribution ◽  
Distribution Network ◽  
Operating Cost ◽  
Water Distribution Network ◽  
Activity Based Costing ◽  
Operational Strategies ◽  
Long Term Impact ◽  
Whole Life Costing

There is an increasing pressure from the economic regulator in England and Wales for water companies to ensure that their capital maintenance decisions reflect an understanding of the long-term impact on their operational costs and risks. This implies that decisions must not only reflect the costs borne now but the likely costs in the future, and how these might be optimised. It is noteworthy that within the construction and transport industries, asset management decisions which have been driven in this direction utilise a whole life costing (WLC) methodology. This paper addresses the implications of transferring the concept of WLC to service-based assets such as water systems. A WLC approach to distribution network management aims to achieve the lowest network provision and operating cost when all costs are considered to achieve standards enforced by regulation. Cognisance is to be taken of all relevant costs - direct and indirect, private and societal - in order to balance the needs of the service supplier, the customer, society and the environment in a sustainable manner. A WLC analysis thus attempts to develop a cost profile over the life of the asset. Accounting for the costs over this period is achieved through a combination of activity based costing (ABC) and a life cycle assessment (LCA) used to identify potential social and environmental costs. This process means that each of these identified costs must be linked to some physical parameter that itself varies over time due to changing demands on the system, the different operational strategies available to the operator and natural deterioration of the fabric of the system. The links established between the cost and activities of the operator provide the basis for the development of a WLC decision tool (WiLCO) for application to water distribution network management.

Nitrite and Nitrate Levels in Groundwater, Water Distribution Network, Bottled Water and Juices in Iran : A systematic Review

2020 ◽  
Vol 21 ◽  
Author(s):  
Maasoumeh Marhamati ◽  
Asma Afshari ◽  
Behzad Kiani ◽  
Behrooz Jannat ◽  
Mohammad Hashemi
Keyword(s):  
Drinking Water ◽  
Water Distribution ◽  
Scientific Information ◽  
Distribution Network ◽  
Water Distribution Network ◽  
The Body ◽  
International Standards ◽  
Nitrogen Fertilizers ◽  
Nitrate Content ◽  
Nitrate And Nitrite

Background: Nitrate and nitrite can get into the body through the consumption of contaminated water either directly or indirectly. The accumulation of these compounds in the body, in the long run, leads to health problems, for example, digestive disorders, cancers, and even death threats in children. The aim of this review is to investigate nitrate and nitrite pollution levels in drinking water and fruit juices in Iran. Methods: In this review data were collected through searching the Scientific Information Database, Science-Direct, Scopus, PubMed, Google Scholar, and Magiran databases using the keywords Nitrate, Nitrite, Drinking water, Drinking Water Resources, Juice and Iran. Finally, the location of the studies was geocoded through the Google My Maps (https://www.google.com/mymaps) software. Results: Studies clearly indicated that the juices are safe in terms of nitrate. Nitrate and nitrite values were less than the national and international standards in all samples of bottled drinking water except for a few of the studies. The results of the reviewed studies also indicated that the nitrate content was higher than that written on the label in 96% of the samples, and nitrite was not labeled in 80% of them. The nitrate quantity was higher than the permissible limit, in the water distribution network of Bushehr, Gilan and Mazandaran Provinces. Talesh, Ardabil, Hashtgerd, Divandareh, and Kerman cities had high nitrate levels in more than 50% of wells. Conclusion: Using nitrogen fertilizers and lack of a wastewater treatment system were the main reasons for the presence of nitrate and nitrite.

scholarly journals Optimal Design of District Metered Areas in a Water Distribution Network Using Coupled Self-Organizing Map and Community Structure Algorithm

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 836
Author(s):  
Xuan Khoa Bui ◽  
Malvin S. Marlim ◽  
Doosun Kang
Keyword(s):  
Community Structure ◽  
Optimal Design ◽  
Water Distribution ◽  
Distribution Network ◽  
Coupled Model ◽  
Water Distribution Network ◽  
Self Organizing Map ◽  
Structure Algorithm ◽  
Demand Variability ◽  
Self Organizing

Operation and management of a water distribution network (WDN) by district metered areas (DMAs) bring many benefits for water utilities, particularly regarding water loss control and pressure management. However, the optimal design of DMAs in a WDN is a challenging task. This paper proposes an approach for the optimal design of DMAs in the multiple-criteria decision analysis (MCDA) framework based on the outcome of a coupled model comprising a self-organizing map (SOM) and a community structure algorithm (CSA). First, the clustering principle of the SOM algorithm is applied to construct initial homologous clusters in terms of pressure and elevation. CSA is then coupled to refine the SOM-based initial clusters for the automated creation of multiscale and dynamic DMA layouts. Finally, the criteria for quantifying the performance of each DMA layout solution are assessed in the MCDA framework. Verifying the model on a hypothetical network and an actual WDN proved that it could efficiently create homologous and dynamic DMA layouts capable of adapting to water demand variability.

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