Sizing Municipal Storage Tanks Based on Reliability Criteria

Zyl, J. E. van; Piller, Olivier; Gat, Yves Le

doi:10.1061/(asce)0733-9496(2008)134:6(548)

Cited by 25 publications

(47 citation statements)

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“…Work on a stochastic model for the reliability analysis of bulk systems was first started by Nel & Haarhoff (1996). Since then, research on the model has been ongoing (van Zyl & Haarhoff, 1999;Haarhoff & van Zyl, 2002;van Zyl et al, 2008). An advantage of stochastic simulation is that it is more realistic since it is able to include uncertainty and randomness of factors (Yang et al, 1996).…”

Section: Background and Motivation For Researchmentioning

confidence: 99%

“…However, with current advances in technology, this is becoming less of a problem and stochastic simulation is steadily gaining feasibility as a modelling technique. Nevertheless, an attempt has been made to reduce the computational effort required by the stochastic analysis model developed by van Zyl et al (2008) through the use of a compression heuristic (Chang & van Zyl, 2010).…”

Section: Background and Motivation For Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…It was also found that a single feeder pipe is optimal in most cases, and that parallel feeder pipes are only optimal for short feeder pipe lengths. Tables Table 2.1 Reservoir design criteria for low-density residential areas (van Zyl et al, 2008) 19 Table 5.6 Summary of remaining supply inflow to the storage reservoir as a percentage for each pipe configuration 66 Table 6.1 Service reservoir cost 75 Table 7.1 Average simulation times and simulated hours for each system 92 Table 7.2 Comparison of simulation times for a large number of simulations 93 Table 7.3 Range of available pipe diameters 94 Table 7.4 Supply ratios for different combinations of pipe configuration and diameter 95 Table 7.5 Demands failure frequency results from the pre-run 95 Table 7.6 Full reservoir fraction results from the pre-run 95 Table 7.7 Summary of final solutions for the test system 97 Table 7.8 Summary of costs for the test system solutions 98 Table 7.9 Costs for systems designed according to South African deterministic guidelines 102 Table 7.10 Systems designed according to South African deterministic guidelines 103 Table 7.11 Sensitivity analysis parameters 106 Table 7.12 Pipe diameter selection for each supply pipe system length 107 Table 7 .19 Average failure rates for different pipeline materials (Nel, 2009) 116 Table 7.20 Comparison of single solution for different pipe failure rates 117 Table 7.21 Comparison of single solution for different pipe failure durations 119 Table 7.22 Near optimal solutions satisfying design criterion for each sensitivity parameter 121 U n i v e r s i t y o f C a p e T o w n Acknowledgements I would like to express my appreciation for the guidance and assistance that I have received from:…”

Section: Introductionmentioning

confidence: 99%

“…Nel & Haarhoff (1996) proposed a stochastic analysis method that allowed the reliability of a reservoir to be estimated based on a Monte Carlo analysis of consumer demand, fire water demand and pipe failures. Van Zyl et al (2008) developed this method further and proposed a design criterion of one failure in ten years under seasonal peak conditions.In this study, a method for the optimal design of bulk water supply systems is proposed with the design variables being the configuration of the feeder pipe system, the feeder pipe diameters (i.e. capacity), and the size of the bulk storage reservoir.…”

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confidence: 99%

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Optimal Reliability-Based Design of Bulk Water Supply Systems

Chang

Zyl

2014

J. Water Resour. Plann. Manage.

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DJ :;sc rt(l 1I UIl s uhnlltt ed In p a rt i~l fulfi lm en t o~' th e reqlllrcrnen ts fu r tht., degree ofM~s t e r ofSClence In Enginee ring AbstractBulk water supply systems are usually designed according to deterministic design guidelines. In South Africa, design guidelines specify that a bulk storage reservoir should have a storage capacity of 48 hours of annual average daily demand (AADD), and the feeder pipe a capacity of 1.5 times AADD (CSIR, 2000). Nel & Haarhoff (1996) proposed a stochastic analysis method that allowed the reliability of a reservoir to be estimated based on a Monte Carlo analysis of consumer demand, fire water demand and pipe failures. Van Zyl et al. (2008) developed this method further and proposed a design criterion of one failure in ten years under seasonal peak conditions.In this study, a method for the optimal design of bulk water supply systems is proposed with the design variables being the configuration of the feeder pipe system, the feeder pipe diameters (i.e. capacity), and the size of the bulk storage reservoir. The stochastic analysis method is applied to determine a trade-off curve between system cost and reliability, from which the designer can select a suitable solution.Optimisation of the bulk system was performed using the multi-objective genetic algorithm, NSGA-II. As Monte Carlo sampling can be computationally expensive, especially when large numbers of simulations are required in an optimisation exercise, a compression heuristic was implemented and refined to reduce the computational effort required of the stochastic simulation. Use of the compression heuristic instead of full Monte Carlo simulation in the reliability analysis achieved computational time savings of around 75% for the optimisation of a typical system.Application of the optimisation model showed that it was able to successfully produce a set of Pareto-optimal solutions ranging from low reliability, low cost solutions to high reliability, high cost solutions. The proposed method was first applied to a typical system, resulting in an optimal reservoir size of approximately 22 h AADD and feeder pipe capacity of 2 times AADD. This solution achieved 9% savings in total system cost compared to the South African design guidelines. In addition, the optimal solution proved to have better reliability that one designed according to South African guidelines.A sensitivity analysis demonstrated the effects of changing various system and stochastic parameters from typical to low and high values. The sensitivity results revealed that the length of the feeder pipe system has the greatest impact on both the cost and reliability of the bulk system. It was also found that a single feeder pipe is optimal in most cases, and that parallel feeder pipes are only optimal for short feeder pipe lengths.The optimisation model is capable of narrowing down the search region to a handful of possible design solutions, and can thus be used by the engineer as a tool to assist with the design of the final system.

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Section: Background and Motivation For Researchmentioning

confidence: 99%

Section: Background and Motivation For Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Optimal Reliability-Based Design of Bulk Water Supply Systems

Chang

Zyl

2014

J. Water Resour. Plann. Manage.

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Water Distribution Networks

Ostfeld

2014

Studies in Computational Intelligence

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A water distribution system is a complex assembly of hydraulic control elements connected together to convey quantities of water from sources to consumers. The typical high number of constraints and decision variables, the nonlinearity, and the non-smoothness of the head-flow-water quality governing equations are inherent to water supply systems planning and management problems. Traditional methods for solving water distribution systems management problems, such as the least cost design and operation problem, utilized linear/ nonlinear optimization schemes which were limited by the system size, the number of constraints, and the number of loading conditions. More recent methodologies employ heuristic optimization techniques, such as genetic algorithms or ant colony optimization as stand alone or hybrid data driven-heuristic schemes. This book chapter reviews some of the more traditional water distribution systems problem algorithms and solution methodologies. It is comprised of sub sections on least cost and multi-objective optimal design of water networks, reliability incorporation in water supply systems design, optimal operation of water networks, water quality analysis inclusion in distribution systems, water networks security related topics, and a look into the future.

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Parameters Influencing the Sizing of Rainwater Tanks for Use in Houses

Ghisi

2009

Water Resour Manage

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Rainwater harvesting has been studied in different countries as a way of easing water availability problems and reducing potable water demand in buildings. The most important factor relating to the efficiency of a rainwater system is the correct sizing of the rainwater tank. Therefore, the objective of this article is to assess the influence of rainfall, roof area, number of residents, potable water demand and rainwater demand on rainwater tank sizing. The analysis was performed by using computer simulation and by considering daily rainfall data for three cities located in the state of São Paulo, Brazil. The roof areas considered were 50, 100, 200 and 400 m 2 ; the potable water demands were 50, 100, 150, 200, 250 and 300 l per capita per day; the rainwater demands were taken as a percentage of the potable water demand, i.e., 10% to 100% at increments of 10%; and the number of residents was two and four. Results indicated a wide variation of rainwater tank sizes for each city and also for each parameter. The main conclusion that can be made from the study is that rainwater tank sizing for houses must be performed for each specific situation, i.e., considering local rainfall, roof area, potable water demand, rainwater demand and number of residents. Therefore, sizing rainwater tanks according to local tradition is not recommended as it may incur low efficiency.

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Sizing Municipal Storage Tanks Based on Reliability Criteria

Cited by 25 publications

References 24 publications

Optimal Reliability-Based Design of Bulk Water Supply Systems

Optimal Reliability-Based Design of Bulk Water Supply Systems

Water Distribution Networks

Parameters Influencing the Sizing of Rainwater Tanks for Use in Houses

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