Seismic-Reliability-Based Optimal Layout of a Water Distribution Network

Yoo, Do Guen; Jung, Donghwi; Kang, Doosun; Kim, Joong Hoon

doi:10.3390/w8020050

Cited by 16 publications

(10 citation statements)

References 32 publications

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“…The hydraulic model of the network after an earthquake was developed [27]. The hydraulic adjustment of the water supply network after an earthquake was calculated based on the pressure-driven node's water distribution model [28].…”

Section: Solution Processmentioning

confidence: 99%

Analyze the Surplus Power Entropy of Water Supply Network after an Earthquake Based on the Pressure Drive Demand (PDD) Model

et al. 2020

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It is necessary to evaluate the reliability of the water supply network, when the water supply network is damaged by an earthquake. Therefore, this paper researched the feasibility and characteristics of the surplus power entropy as the reliability index of the water supply network, and established a scheme framework for optimizing and improving the reliability of the water supply network. This paper developed a reliability evaluation model for the water supply network after an earthquake. Combined with the Monte Carlo stochastic simulation hydraulic analysis, this model is also based on the pressure-driven nodes water demand model. In the case study, the surplus power entropy method was applied to test the reliability of the model. The statistical curves of the surplus power entropy of nodes and pipe networks, the distribution of the surplus power entropy with different intensities in pipe networks, and the comparison results of three reliability improvement schemes, before and after, were obtained. The influence factors of the surplus power entropy were obtained from the data analysis. The high consistency between the surplus power entropy and flow entropy verifies the feasibility of the surplus power entropy as a reliability index. The three schemes show that the surplus power entropy index can be used as a beneficial supplement to the reliability evaluation index of the pipe network.Sustainability 2020, 12, 1591 2 of 17 variety of specified working conditions, investigate the pipe network's ability to meet the demand, and test the reliability of the water supply network. The commonly used simulation methods include the Monte Carlo method [10], the quasi-Monte Carlo method [11], and so on. The agency methods do not directly test the reliability of the pipe network, but use the appropriate agency model to test the reliability [12]. The agency methods include information entropy [13,14], flow entropy [15], the path entropy method [16], and the recoverable index method [17]. Many academics and researchers used a combination of reliability methods in their studies. For example, Deng et al.[18] proposed a system reliability solution method for a water supply pipe network by combining analytics methods and simulation methods, while calculating path importance and connectivity ratio. The simulation methods can simulate and perform hydraulic analysis under various working conditions. However, this method requires many rounds of hydraulic calculation to reach the results. In addition, the agency method models are simple and easy to program and calculate, but they lack the source of certainty.This study combined the advantages of simulation methods and agency methods, and used Monte Carlo stochastic simulation to obtain the hydraulic analysis of the water supply network after earthquakes, based on the pressure drive node water demand model. Surplus power entropy was taken as the reliability evaluation index of the water supply network. On the basis of solving the entropy value, the paper developed the structural optimiz...

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Section: Solution Processmentioning

confidence: 99%

Analyze the Surplus Power Entropy of Water Supply Network after an Earthquake Based on the Pressure Drive Demand (PDD) Model

et al. 2020

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“…These scenarios which prompt the need for demand development (connections to community level plans) are important part of the long-term level water management problems. There are several approaches that have been proposed [65][66][67][68] but the meta-heuristics techniques are most preferred methods due to their ability to find close-to-optimal solutions to the problem within reasonable computing times [69].…”

Section: Optimal Designmentioning

confidence: 99%

Solving Management Problems in Water Distribution Networks: A Survey of Approaches and Mathematical Models

Bello

Abu‐Mahfouz

Hamam

et al. 2019

Water

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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.

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“…Therefore, a total of 30 earthquake hazard assessment scenarios were constructed assuming a situation where a single earthquake of magnitude 4 (M4) has occurred. Yoo et al [39] suggests that a minimum of 10 to 5000 Monte Carlo simulations should be performed in order to obtain a consistent system reliability factor that does not show large variance in REVAS.NET. The changes in the number of repetitions as such are affected by the size of the pipe network and the number of pipes.…”

Section: Earthquake Occurrence and Pipe Damage Scenario Settingmentioning

confidence: 99%

Comparative Study of Hydraulic Simulation Techniques for Water Supply Networks under Earthquake Hazard

Yoo

Lee

2019

Water

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Water supply facilities such as waterworks systems are facilities that supply residential and industrial water essential for humans to live and it is essential for these facilities to be prepared for earthquake hazards. In the present study, new hydraulic analysis procedures that can complement problems in existing model were proposed for performance quantification under seismic hazards. Detailed procedures for estimating the serviceability of water supply networks using pressure dependent demand (PDD) and pressure dependent leakage (PDL) techniques were proposed. The developed methodologies can simulate many pipe leakage and breakage situations more realistically. The methodologies were applied to representative pipe networks to investigate the models and new performance quantification indicators were additionally presented. The developed models are judged to be usable as a basic tool finding for guidelines because they can simultaneously quantify the amount of leakage calculated from the viewpoint of suppliers as well as the water availability of consumers when an earthquake hazard has occurred.

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Seismic-Reliability-Based Optimal Layout of a Water Distribution Network

Cited by 16 publications

References 32 publications

Analyze the Surplus Power Entropy of Water Supply Network after an Earthquake Based on the Pressure Drive Demand (PDD) Model

Analyze the Surplus Power Entropy of Water Supply Network after an Earthquake Based on the Pressure Drive Demand (PDD) Model

Solving Management Problems in Water Distribution Networks: A Survey of Approaches and Mathematical Models

Comparative Study of Hydraulic Simulation Techniques for Water Supply Networks under Earthquake Hazard

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