Optimal reliability-based design of bulk water supply systems

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dc.contributor.advisorVan Zyl, Jakobus Een_ZA
dc.contributor.authorChang, Ching-Chiaoen_ZA
dc.date.accessioned2015-11-02T10:53:04Z
dc.date.available2015-11-02T10:53:04Z
dc.date.issued2011en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.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.en_ZA
dc.identifier.apacitationChang, C. (2011). <i>Optimal reliability-based design of bulk water supply systems</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Civil Engineering. Retrieved from http://hdl.handle.net/11427/14593en_ZA
dc.identifier.chicagocitationChang, Ching-Chiao. <i>"Optimal reliability-based design of bulk water supply systems."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Civil Engineering, 2011. http://hdl.handle.net/11427/14593en_ZA
dc.identifier.citationChang, C. 2011. Optimal reliability-based design of bulk water supply systems. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Chang, Ching-Chiao AB - Bulk 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. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - Optimal reliability-based design of bulk water supply systems TI - Optimal reliability-based design of bulk water supply systems UR - http://hdl.handle.net/11427/14593 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/14593
dc.identifier.vancouvercitationChang C. Optimal reliability-based design of bulk water supply systems. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Civil Engineering, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/14593en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Civil Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherCivil Engineeringen_ZA
dc.titleOptimal reliability-based design of bulk water supply systemsen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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