scholarly journals Improving leakage management in urban water distribution networks through data analytics and hydraulic simulation

2013 ◽  
Author(s):  
A. Candelieri ◽  
F. Archetti ◽  
E. Messina
Keyword(s):  
Data Analytics ◽  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Urban Water ◽  
Hydraulic Simulation

scholarly journals Optimal Placement of Pressure Gauges for Water Distribution Networks Using Entropy Theory Based on Pressure Dependent Hydraulic Simulation

Entropy ◽  
2018 ◽  
Vol 20 (8) ◽  
pp. 576 ◽  
Author(s):  
Do Yoo ◽  
Dong Chang ◽  
Yang Song ◽  
Jung Lee
Keyword(s):  
Water Distribution ◽  
Pressure Gauge ◽  
Distribution Networks ◽  
Entropy Method ◽  
Water Distribution Networks ◽  
Optimal Placement ◽  
Hydraulic Simulation ◽  
Priority Order ◽  
The Impact ◽  
Pressure Driven

This study proposed a pressure driven entropy method (PDEM) that determines a priority order of pressure gauge locations, which enables the impact of abnormal condition (e.g., pipe failures) to be quantitatively identified in water distribution networks (WDNs). The method developed utilizes the entropy method from information theory and pressure driven analysis (PDA), which is the latest hydraulic analysis method. The conventional hydraulic approach has problems in determining the locations of pressure gauges, attributable to unrealistic results under abnormal conditions (e.g., negative pressure). The proposed method was applied to two benchmark pipe networks and one real pipe network. The priority order for optimal locations was produced, and the result was compared to existing approach. The results of the conventional method show that the pressure reduction difference of each node became so excessive, which resulted in a distorted distribution. However, with the method developed, which considers the connectivity of a system and the influence among nodes based on PDA and entropy method results, pressure gauges can be more realistically and reasonably located.

Study on Safety Evaluation Method for Water Distribution Networks Based on LS-SVM

2011 ◽  
Vol 243-249 ◽  
pp. 5003-5008
Author(s):  
Zhi Tao Wang ◽  
Jing Yu Su ◽  
Wei Wang
Keyword(s):  
Water Distribution ◽  
Distribution Network ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Influential Factors ◽  
Water Distribution Networks ◽  
Security Level ◽  
Urban Water ◽  
Ann Model ◽  
Svm Model

To evaluate the security of urban water distribution network, one model based on LS-SVM was put forth. On the basis of summary and analysis of influential factors for urban water distribution network security, a set of indexes used in the evaluation model above was constructed. The nonlinear mapping between the water distribution networks security classification and its conditions were learned from the finite samples and a water distribution network example was simulated using this model. In addition, the BP ANN model was used to simulate the same example. Through the analysis of the result of the actual security level, the security level acquired by the LS-SVM model and BP ANN model, it may be found that the result acquired by the LS-SVM model has high accuracy, and may used in actual engineering.

scholarly journals Conceptual design of a generic, real-time, near-optimal control system for water-distribution networks

2007 ◽  
Vol 9 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Derek G Jamieson ◽  
Uri Shamir ◽  
Fernando Martinez ◽  
Marco Franchini
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Real Time ◽  
Time Use ◽  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Hydraulic Simulation ◽  
Current State ◽  
Potential Benefits

This paper is intended to serve as an introduction to the POWADIMA research project, whose objective was to determine the feasibility and efficacy of introducing real-time, near-optimal control for water-distribution networks. With that in mind, its contents include the current state-of-the-art and some of the difficulties that would need to be addressed if the goal of near-optimal control was to be achieved. Subsequently, the approach adopted is outlined, together with the reasons for the choice. Since it would be somewhat impractical to use a conventional hydraulic simulation model for real-time, near-optimal control, the methodology includes replicating the model by an artificial neural network which, computationally, is far more efficient. Thereafter, the latter is embedded in a dynamic genetic algorithm, designed specifically for real-time use. In this way, the near-optimal control settings to meet the current demands and minimize the overall pumping costs up to the operating horizon can be derived. The programme of work undertaken in achieving this end is then described. By way of conclusion, the potential benefits arising from implementing the control system developed are briefly reviewed, as are the possibilities of using the same approach for other application areas.

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