Linear Least-Squares Formulation for Operation of Booster Disinfection Systems

Propato, Marco; Uber, James G.

doi:10.1061/(asce)0733-9496(2004)130:1(53)

Cited by 84 publications

(40 citation statements)

References 17 publications

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“…This network has been used to validate and test different water quality models, and has been optimized by a number of methods, including linear programming Boccelli et al 1998, a linear least-squares formulation Propato andUber 2004 anda GA Munavalli andKumar 2003. The data used for the system are the same as those used by Boccelli et al 1998. The objective of the Cherry Hill-Brushy Plains optimization problem is to minimize the mass of chlorine added to the system at six possible locations over a 24-hour period, subject to maintaining the chlorine concentrations at all nodes in the network in the acceptable range of 0.2-4.0 mg L −1 .…”

Section: Case Studymentioning

confidence: 99%

Relationship between problem characteristics and the optimal number of genetic algorithm generations

Gibbs

Maier

Dandy

2011

Engineering Optimization

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Genetic Algorithms (GAs) have been successfully applied to a wide range of engineering optimization problems. The success of the GA is dependent on the parameter values used, and identifying suitable values to use is a difficult task. Typically, the GA parameters must be calibrated for each application, hence it might be expected that the optimal parameter values are related to the characteristics of each problem. To aid the calibration of GAs, it is proposed that there exists an optimal number of GA generations for a given problem, where from the number of generations, the population size can be determined from the total function evaluations that are available. A number of test functions have been considered with different problem characteristics, such as salience, correlation structure, and epistasis, and statistics are proposed to quantify each of these characteristics. A large-scale parametric study has been undertaken to determine the effect of these characteristics on the optimal number of GA generations necessary in order to solve the problem most efficiently. From these results, two function classes have been identified. The function classes have been tested on two instances of an engineering optimization problem and found to classify the most appropriate population size accurately for solving each problem. Hence, the classification method developed can be used to assist in the calibration of GAs for applications where long simulation times are expected.

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Section: Case Studymentioning

confidence: 99%

Relationship between problem characteristics and the optimal number of genetic algorithm generations

Gibbs

Maier

Dandy

2011

Engineering Optimization

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“…injection scheduling) [5][6][7][8][9] can be found. Majority of these works consider the two in a disjoint manner.…”

Section: Introductionmentioning

confidence: 99%

Optimised allocation of actuators for DWDS

Ewald

Zubowicz

Brdyś

2015

Journal of Process Control

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“…Researchers have examined different methods for determining the optimal schedule of disinfection boosters to maintain adequate levels of residual chlorine throughout the distribution system (Boccelli et al 1998(Boccelli et al , 2003Tryby et al 1999Tryby et al , 2002Munavalli and Kumar 2003;Ozdemir and Ucaner 2003;Propato and Uber 2004;Parks and Shannon 2009;Ostfeld et al 2010). Thus, knowledge of residual chlorine concentration throughout the distribution network suggests the water utilities regarding selection of chlorine application strategy i.e.…”

Section: Introductionmentioning

confidence: 99%

Analysis of residual chlorine in simple drinking water distribution system with intermittent water supply

Goyal¹,

Patel

2014

Appl Water Sci

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Knowledge of residual chlorine concentration at various locations in drinking water distribution system is essential final check to the quality of water supplied to the consumers. This paper presents a methodology to find out the residual chlorine concentration at various locations in simple branch network by integrating the hydraulic and water quality model using first-order chlorine decay equation with booster chlorination nodes for intermittent water supply. The explicit equations are developed to compute the residual chlorine in network with a long distribution pipe line at critical nodes. These equations are applicable to Indian conditions where intermittent water supply is the most common system of water supply. It is observed that in intermittent water supply, the residual chlorine at farthest node is sensitive to water supply hours and travelling time of chlorine. Thus, the travelling time of chlorine can be considered to justify the requirement of booster chlorination for intermittent water supply.

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Linear Least-Squares Formulation for Operation of Booster Disinfection Systems

Cited by 84 publications

References 17 publications

Relationship between problem characteristics and the optimal number of genetic algorithm generations

Relationship between problem characteristics and the optimal number of genetic algorithm generations

Optimised allocation of actuators for DWDS

Analysis of residual chlorine in simple drinking water distribution system with intermittent water supply

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