"November 2001" / Includes bibliographical references (leaves 235-240) / xiii, 285 leaves : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 2003

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016 / The water-energy nexus considers the relationship between water and energy resources. Increases in environmental degradation and social pressures in recent years have necessitated the development of manufacturing processes that are conservative with respect to both these resources, while maintaining financial viability. This can be achieved by process integration (PI); a holistic approach to design which emphasises the unity of processes. Within the realm of PI, water network synthesis (WNS) explores avenues for reuse, recycle and regeneration of effluent in order to minimise freshwater consumption and wastewater production. When regeneration is required, membrane-based treatment processes may be employed. These processes are energy intensive and result in a trade-off between water and energy minimisation, thus creating an avenue for optimisation. Previous work in WNS employed a black box approach to represent regenerators in water minimisation problems. However, this misrepresents the cost of regeneration and underestimates the energy requirements of a system. The aim of the research presented in this dissertation is to develop an integrated water regeneration network synthesis model to simultaneously minimise water and energy in a water network. A novel MINLP model for the design of an electrodialysis (ED) unit that is capable of treating a binary mixture of simple salts was developed from first principles. This ED model was embedded into a water network superstructure optimisation model, where the objective was to minimise freshwater and energy consumption, wastewater productions, and associated costs. The model was applied to a pulp and paper case study, considering several scenarios. Global optimisation of the integrated water network and ED design model, with variable contaminant removal ratios, was found to yield the best results. A total of 38% savings in freshwater, 68% reduction in wastewater production and 55% overall cost reduction were observed when compared with the original design. This model also led to a 80% reduction in regeneration (energy) cost. / GS2016

A holistic procedure GLOBAL for the global optimization of water distribution systems is presented. The procedure identifies an optimal tree layout for the network and augments it with loop forming links to assure reliability. Thus, the chosen optimal layout in judiciously subjected to various flow configurations to find an optimal flow division among pipes for the least cost diameter selection. Because the problem is nonconvex, two global search schemes, MULITIST ART and ANNEALING, both within the framework of procedure GLOBAL, are employed to permit a local optimum seeking method to migrate among various local minima. A modified Linear Programming Gradient (LPG) procedure is judiciously employed as local optimizer. An example problem from the literature is solved using the proposed procedure. The optimal solution has a cost very near to the theoretical limit for this problem and is significantly smaller than the ones reported by other researchers. / Master of Science

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2015 / The scarcity of water and strict environmental regulations have made sustainable engineering a prime concern in the process and manufacturing industries. Water minimisation involves the reduction of freshwater use and effluent discharge in chemical plants. This is achieved through water reuse, water recycle and water regeneration. Optimisation of the water network (WN) superstructure considers all possible interconnections between water sources, water sinks and regenerator units (membrane systems). In most published works, membrane systems have been represented using the “black-box” approach, which uses a simplified linear model to represent the membrane systems. This approach does not give an accurate representation of the energy consumption and associated costs of the membrane systems. The work presented in this dissertation therefore looks at the incorporation of a detailed reverse osmosis network (RON) superstructure within a water network superstructure in order to simultaneously minimise water, energy, operating and capital costs. The WN consists of water sources, water sinks and reverse osmosis (RO) units for the partial treatment of the contaminated water. An overall mixed-integer nonlinear programming (MINLP) framework is developed, that simultaneously evaluates both water recycle/reuse and regeneration reuse/recycle opportunities. The solution obtained from optimisation provides the optimal connections between various units in the network arrangement, size and number of RO units, booster pumps as well as energy recovery turbines. The work looks at four cases in order to highlight the importance of including a detailed regeneration network within the water network instead of the traditional “black-box’’ model. The importance of using a variable removal ratio in the model is also highlighted by applying the work to a literature case study, which leads to a 28% reduction in freshwater consumption and 80% reduction in wastewater generation. / GR2016

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. Johannesburg, May 2016. / This thesis presents work on four problems identi ed in the Zomba Water Distribution Network. The research was carried out on the existing network infrastructure with the aim of improving e ciency by reducing Unaccounted-For Water (UFW). The rst challenge was to develop a demand model for the city based on its in uencing factors: daily and seasonal uctuations as well as population dynamics. The model was to capture demand patterns for short-term, medium-term to long-term time periods, thereby becoming an important input factor into decision making. The developed model may be employed to generate demand which can be input into the city's 10 year infrastructure expansion plan. The second problem was to explain why houses built too close to tanks are at risk of inconsistent water supply. It was found that the requirement of observing the tank elevations, helv, had been violated. As a result, the discontinued supplies occurred. Once the required tank elevation helv had been established, an extra increase in the elevation so as to accommodate a larger population was determined to be on the order of one centimeter. Third problem was to explain the continued mains pipe failures observed in the network. It was established that the main cause was the hammering e ects started through the process of manually closing ow control valves (FCVs) tted next to tanks. A possible remedy was to rather t the FCVs at joint nodes and not at the tanks. This was estimated to greatly reduce the hammering e ects, eventually turning them into minor head losses due to elbow bends. Finally, a structural approach to designing tanks that optimize the use of gravity is presented. This is an input into the infrastructure expansion planning of the city. Regardless of any design shapes they may take, tanks with height-radius, h=r, ratio of less than 1 exhibit diminished, as opposed to increased, height changes with demand changes. Such a property would ensure consistency in the pressure at the tank, allowing for delivery of the demanded load. / GR2016

Implementation of physically distributed catchment modelling systems reshapes the fundamental philosophy of traditional calibration approaches by supporting the concept of equifinality. Arising from the concept of equifinality, alternative behavioural parameter sets within a given catchment modelling system structure can generate similar levels of simulation performance. This concept is motivated by the existence of a variety of uncertainties associated with a complex catchment modelling system, such as an imperfect model structure, measurement errors in both the input data and the recorded flows, and unknown, or poorly defined, interactions among parameters. However, the difficulty of searching for behavioural parameter sets increases as the complexity of the catchment modelling systems increases. This study undertook an investigation on the feasibility and robustness of a real-value coding genetic algorithm (GA) for calibrating the physically distributed Storm Water Management Model (SWMM) using the Centennial Park catchment in Sydney as a case study. It was found that a real-value coding GA was a robust technique suitable to search for behavioural parameter sets and, in particular, it was found that this approach was capable of identifying the promising range of values for spatially variable parameters. Moreover, the widespread use of physically distributed catchment modelling systems has highlighted the importance of estimating the uncertainty in the parameter values and in the predictions obtained from a complex catchment modelling system as well as in catchment averaged, or lumped, systems that have been the focus of many previous studies. Bayesian inference has been shown to be a tool suitable for parameter uncertainty estimation in catchment modelling. However, the application of Bayesian inference faces difficulties in complex high-dimensional systems where there is little if any a priori knowledge about the proposal distribution of the parameters. In this study, a real-value coding GA was used to undertake uncertainty estimation on spatially variable control parameters with little a priori knowledge about the proposal distribution of parameters. After 50,000 evaluations, the marginal posterior distributions of spatially variable parameters which are associated with behavioural parameter sets were identified. The performance of a behavioural parameter set under a range of hydrological conditions was evaluated. Updating of the marginal distributions of these control parameters was implemented by adding additional calibration data. Interactions among the spatially variable control parameters were investigated also. Results based on the Pearson Correlation method indicate no clear relationship between any two control parameters. However, a methodology to detect relationships among groups of parameters was developed. Application of this methodology suggests that the simulation performance of SWMM was influenced by combinations of parameter values rather than values of the individual parameters. Finally, the predictive uncertainty associated with the existence of behavioural parameter sets was considered. A number of alternative strategies were used to evaluate the predictive performance. Consideration of the results suggests that use of a small number of parameter sets randomly selected from the large number of behavioural parameter sets was the best strategy in terms of efficiently obtaining predictive performance.

Implementation of physically distributed catchment modelling systems reshapes the fundamental philosophy of traditional calibration approaches by supporting the concept of equifinality. Arising from the concept of equifinality, alternative behavioural parameter sets within a given catchment modelling system structure can generate similar levels of simulation performance. This concept is motivated by the existence of a variety of uncertainties associated with a complex catchment modelling system, such as an imperfect model structure, measurement errors in both the input data and the recorded flows, and unknown, or poorly defined, interactions among parameters. However, the difficulty of searching for behavioural parameter sets increases as the complexity of the catchment modelling systems increases. This study undertook an investigation on the feasibility and robustness of a real-value coding genetic algorithm (GA) for calibrating the physically distributed Storm Water Management Model (SWMM) using the Centennial Park catchment in Sydney as a case study. It was found that a real-value coding GA was a robust technique suitable to search for behavioural parameter sets and, in particular, it was found that this approach was capable of identifying the promising range of values for spatially variable parameters. Moreover, the widespread use of physically distributed catchment modelling systems has highlighted the importance of estimating the uncertainty in the parameter values and in the predictions obtained from a complex catchment modelling system as well as in catchment averaged, or lumped, systems that have been the focus of many previous studies. Bayesian inference has been shown to be a tool suitable for parameter uncertainty estimation in catchment modelling. However, the application of Bayesian inference faces difficulties in complex high-dimensional systems where there is little if any a priori knowledge about the proposal distribution of the parameters. In this study, a real-value coding GA was used to undertake uncertainty estimation on spatially variable control parameters with little a priori knowledge about the proposal distribution of parameters. After 50,000 evaluations, the marginal posterior distributions of spatially variable parameters which are associated with behavioural parameter sets were identified. The performance of a behavioural parameter set under a range of hydrological conditions was evaluated. Updating of the marginal distributions of these control parameters was implemented by adding additional calibration data. Interactions among the spatially variable control parameters were investigated also. Results based on the Pearson Correlation method indicate no clear relationship between any two control parameters. However, a methodology to detect relationships among groups of parameters was developed. Application of this methodology suggests that the simulation performance of SWMM was influenced by combinations of parameter values rather than values of the individual parameters. Finally, the predictive uncertainty associated with the existence of behavioural parameter sets was considered. A number of alternative strategies were used to evaluate the predictive performance. Consideration of the results suggests that use of a small number of parameter sets randomly selected from the large number of behavioural parameter sets was the best strategy in terms of efficiently obtaining predictive performance.

M.Ing. / Stochastic analysis of water distribution systems allow the performance of systems to be evaluated under more realistic conditions that involve both deterministic and probabilistic factors. A software package called Mocasim II has been developed to perform stochastic analysis on water supply systems. This allows the relationship between the reliability of the supply system and the capacity of its service reservoir(s) to be quantified using Monte Carlo analysis. In a Monte Carlo analysis the factors which influence the reliability of the system such as water demand, fires, and pipe failures are simulated stochastically over a long period of time. A reliability-capacity relationship is quantified by analysing the failure behaviour of different service reservoir sizes. A previous version of Mocasim used a simple mass balance model for calculating the flows in simple, linear distribution networks. Mocasim II extends the functionality of its predecessor by enabling the probabilistic modelling of more complex water distribution models. This was achieved by integrating the stochastic modelling technique into the Epanet hydraulic analysis software package. Mocasim II was designed using an object-oriented model which has various advantages such as ease of programme testing, upgrading and maintaining as well as minimum repetitive code and a logical structure. Additional capabilities of Mocasim II include the determination of probability distributions for network properties such as flow rate, pressure and water quality at any node in the network. This will assist in estimating the levels of service of a water supply system. This project focussed on developing sections of Mocasim II to be integrated with existing software such as Mocasim I, the Epanet hydraulic engine, OOTEN, and a random number generator. The software was tested thoroughly. This involved testing each class separately as well as applying it to a test case which is a simple network consisting of a source, reservoir and demand node. The theoretical background of the stochastic model has been investigated and various aspects discussed. Various case studies in Windhoek-Namibia, Mabeskraal-South Africa and an Epanet design example demonstrate the capabilities of the software and benefits of a stochastic analysis. A workbook to be used in addition to the software's help facility has been developed.

Errata sheet pasted onto front end-paper. / Bibliography: leaves 357-377. / xxvi, 514 leaves : ill. (some col.), fold. maps ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 1999?

The management of Water Distribution Systems (WDSs) involves making decisions about various operations in the network, including the scheduling of pump operations and setting of disinfectant dosing rates. There are often conflicting objectives in making these operational decisions, such as minimising costs while maximising the quality of the water supplied. Hence, the operation of WDSs can be very difficult, and there is generally considerable scope to improve the operational efficiency of these systems by improving the associated decision making process. In order to achieve this goal, optimisation methods known as Genetic Algorithms (GAs) have been successfully adopted to assist in determining the best possible solutions to WDS optimisation problems for a number of years. Even though there has been extensive research demonstrating the potential of GAs for improving the design and operation of WDSs, the method has not been widely adopted in practice. There are a number of reasons that may contribute to this lack of uptake, including the following difficulties: (a) developing an appropriate fitness function that is a suitable description of the objective of the optimisation including all constraints, (b) making decisions that are required to select the most appropriate variant of the algorithm, (c) determining the most appropriate parameter settings for the algorithm, and (d) a reluctance of WDS operators to accept new methods and approaches. While these are all important considerations, the correct selection of GA parameter values is addressed in this thesis. Common parameters include population size, probability of crossover, and probability of mutation. Generally, the most suitable GA parameters must be found for each individual optimisation problem, and therefore it might be expected that the best parameter values would be related to the characteristics of the associated fitness function. The result from the work undertaken in this thesis is a complete GA calibration methodology, based on the characteristics of the optimisation problem. The only input required by the user is the time available before a solution is required, which is beneficial in the WDS operation optimisation application considered, as well as many others where computationally demanding model simulations are required. Two methodologies are proposed and evaluated in this thesis, one that considers the selection pressure based on the characteristics of the fitness function, and another that is derived from the time to convergence based on genetic drift, and therefore does not require any information about the fitness function characteristics. The proposed methodologies have been compared against other GA calibration methodologies that have been proposed, as well as typical parameter values to determine the most suitable method to determine the GA parameter values. A suite of test functions has been used for the comparison, including 20 complex mathematical optimisation problems with different characteristics, as well as realistic WDS applications. Two WDS applications have been considered: one that has previously been optimised in the literature, the Cherry Hills-Brushy Plains network; and a real case study located in Sydney, Australia. The optimisation problem for the latter case study is to minimise the pumping costs involved in operating the WDS, subject to constraints on the system, including minimum disinfectant concentrations. Of the GA calibration methods compared, the proposed calibration methodology that considered selection pressure determined the best solution to the problem, producing a 30% reduction in the electricity costs for the water utility operating the WDS. The comparison of the different calibration approaches demonstrates three main results: 1. that the proposed methodology produced the best results out of the different GA calibration methods compared; 2. that the proposed methodology can be applied in practice; and 3. that a correctly calibrated GA is very beneficial when solutions are required in a limited timeframe. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1325448 / Thesis (Ph.D.) - University of Adelaide, School of Civil, Environmental and Mining Engineering, 2008