Water Distribution System Design Under Uncertainties

Lansey, Kevin; Duan, Ning; Mays, Larry W.; Tung, Yeou Koung

doi:10.1061/(asce)0733-9496(1989)115:5(630)

Cited by 182 publications

(59 citation statements)

References 7 publications

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“…Researchers have reported a number of applications of nonlinear optimization to pipe network problems (EI-Bahrawy andSmith 1985, 1987;Su et al 1987;Lansey and Mays 1989a;Lansey et al 1989;Duan et al 1990). EI-Bahrawy and Smith (1985) applied MINOS to the design of water collection and distribution systems.…”

Section: Nonlinear Programmingmentioning

confidence: 99%

“…The inclusion of constraints on reliability usually produced looped networks. Lansey et al (1989) considered the optimal design of pipe networks where there is uncertainty in the nodal demands, Hazen-Williams coefficients and the minimum nodal heads. They used a chanceconstrained approach to convert the probabilistic constraints into deterministic ones.…”

Section: Nonlinear Programmingmentioning

confidence: 99%

See 1 more Smart Citation

Genetic Algorithms Compared to Other Techniques for Pipe Optimization

Simpson

Dandy

Murphy

1994

J. Water Resour. Plann. Manage.

601

255

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ABSTRACT:The genetic algorithm technique is a relatively new optimization technique. In this paper we present a methodology for optimizing pipe networks using genetic algorithms. Unknown decision variables are coded as binary strings. We investigate a three-operator genetic algorithm comprising reproduction, crossover, and mutation. Results are compared with the techniques of complete enumeration and nonlinear programming. We apply the optimization techniques to a case study pipe network. The genetic algorithm technique finds the global optimum in relatively few evaluations compared to the size of the search space. INTRODUCTIONThe construction and maintenance of pipelines for water supply costs many millions of dollars every year. As funds for the development of new infrastructure become increasingly scarce, there is an increasing desire to achieve the highest level of effectiveness for each dollar spent. Traditionally, the design of water distribution networks has been based on experience. However, there is now a significant (and growing) body of literature devoted to optimization of pipe networks.

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Section: Nonlinear Programmingmentioning

confidence: 99%

Section: Nonlinear Programmingmentioning

confidence: 99%

Genetic Algorithms Compared to Other Techniques for Pipe Optimization

Simpson

Dandy

Murphy

1994

J. Water Resour. Plann. Manage.

601

255

View full text Add to dashboard Cite

show abstract

“…Lambert [45] conducted an experimental study to investigate the accuracy of the power function model in Equation (6) and provided a guideline on using exponent α based on the pipe material and level of leakage. It was suggested that the exponent of 0.5 would be used to simulate large detectable leakages in metal pipes; the exponent of 1.0 (linear relationship between discharge and pressure) would be used if no information on the pipe material is available.…”

Section: Pipe Failure Modelingmentioning

confidence: 99%

“…Various surrogate measures of WDS reliability have been proposed including capacity reliability [6,7], resilience [40], robustness [10,11], availability [51]. Bao and Mays [52] proposed three formulations of WDS system reliability which can be calculated from nodal reliability values: minimum nodal reliability, arithmetic mean reliability, and flow-weighted mean reliability.…”

Section: Seismic Reliability Indicatormentioning

confidence: 99%

“…Thereafter, some studies have included the system's performance index within the optimization framework. Lansey et al [6] developed a chance-constrained least-cost model in which the capacity reliability is defined as the probability that stochastic pressures are equal to or higher than pressure requirement and are constrained at a certain level while minimizing cost. The nodal demands, pressure requirements, and pipe roughness coefficients were assumed to be uncertain while optimizing the pipe size.…”

Section: Introductionmentioning

confidence: 99%

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

Yoo

Jung

Kang

et al. 2016

Water

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Abstract:We proposed an economic, cost-constrained optimal design of a water distribution system (WDS) that maximizes seismic reliability while satisfying pressure constraints. The model quantifies the seismic reliability of a WDS through a series of procedures: stochastic earthquake generation, seismic intensity attenuation, determination of the pipe failure status (normal, leakage, and breakage), pipe failure modeling in hydraulic simulation, and negative pressure treatment. The network's seismic reliability is defined as the ratio of the available quantity of water to the required water demand under stochastic earthquakes. The proposed model allows no pipe option in decisions, making it possible to identify seismic-reliability-based optimal layout for a WDS. The model takes into account the physical impact of earthquake events on the WDS, which ultimately affects the network's boundary conditions (e.g., failure level of pipes). A well-known benchmark network, the Anytown network, is used to demonstrate the proposed model. The network's optimal topology and pipe layouts are determined from a series of optimizations. The results show that installing large redundant pipes degrades the system's seismic reliability because the pipes will cause a large rupture opening under failure. Our model is a useful tool to find the optimal pipe layout that maximizes system reliability under earthquakes.

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Chance Constrained Optimization of Booster Chlorination in Water Distribution Networks

Köker

Altan-Sakarya

2014

CLEAN Soil Air Water

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Quality of municipal water is sustained by addition of disinfectant, generally chlorine, to the water distribution network. Because of health problems, chlorine concentration in the network is limited between maximum and minimum limits. Carcinogenic disinfectant by-products start to occur at high concentrations so it is desired to have minimum amount of chlorine without violating the limit. In addition to the health issues, minimum injection amount is favorable concerning cost. Hence, an optimization problem which covers all of these considerations should be modeled. However, there are uncertain factors as chlorine is reactive and decays both over time and space. Thus, probabilistic approach is necessary to obtain reliable and realistic results from the model. In this study, a linear programming model is developed for the chance constrained optimization of the water distribution network. The objective is to obtain minimum amount of injection mass subjected to maintaining more uniformly distributed chlorine concentrations within the limits, while considering the randomness of chlorine concentration by probability distributions. Network hydraulics and chlorine concentration are computed by the network simulation software, EPANET.

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Water Distribution System Design Under Uncertainties

Cited by 182 publications

References 7 publications

Genetic Algorithms Compared to Other Techniques for Pipe Optimization

Genetic Algorithms Compared to Other Techniques for Pipe Optimization

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

Chance Constrained Optimization of Booster Chlorination in Water Distribution Networks

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