Thesis (M.S. in Management) Naval Postgraduate School, December 1996. / Thesis advisor(s): James Fremgen, Janice M. Menker. "december 1996." Includes bibliographical references (p. 73-75). Also available online.

This thesis describes a study of two approaches to the design of water distribution networks to meet specified demands at minimum cost. One method is based on an incremental increase technique which first examines all possible "one-size" pipe increases in the network, then based on a benefit/cost analysis a decision is made on which pipe to increase one diameter size. The second approach utilizes a computerized linear programming technique to rapidly converge on an optimal network design. Both techniques rely on the use of an effective computerized network analysis program. It was found after studying several networks that the incremental increase technique is operational for any size of network. However, computer costs quickly become a limiting factor in the usefulness of this approach. The linear programming based technique was considerably less costly but did not prove itself to be fully capable of optimizing large networks in its present developmental state. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

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This thesis is concerned with the developments of analysis, modelling and optimization techniques and computer program algorithms, with the ultimate aim of control of water supply and distribution systems to lead to overall optimal operation. Typical system features and operational conditions are analyzed, and the requirements for the overall objective are examined, to determine an overall control strategy which is subsequently developed and tested on real systems throughout this thesis. As a prerequisite, short-term water demand forecasting is extensively studied by employing time series analysis. Special consideration is given to improving the forecasting accuracy of the method and its on-line implementation. In order to speed up the solution time of optimal system operation, simplified system models -- namely, piecewise macroscopic model and equivalent network model -- are developed respectively. Then by employing the piecewise macroscopic model, a nonlinear programming method is developed to cater for the optimal operation of a class of multi-source systems without significant storage. The optimal operation policy obtained by this method is realized at two levels: the first level calculates the optimized apportioning of water to be delivered by different sources; the second level decides the least cost pump schedules to supply the optimized apportioning of water. Based on the equivalent network model, a linear programming method is developed for optimization of a class of multi-source, multi-reservoir systems with a mixture of fixed speed pumps and variable speed and/or variable throttle pumps. This method yields directly optimized pump schedules and reservoir trajectories in terms of least cost system operation. The integration of the developments results in a scheme which can be applied to give overall dynamic control of a wide range of water supply and distribution systems. The application results presented in this thesis justify the theoretical developments and show that benefits can be obtained from these developments.

"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

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A comprehensive study on the application of flow cytometry (FCM) for the analysis of biofilms has been undertaken and the results presented in this thesis have shown that flow cytometry can been successfully used to enumerate, sort and image the bacteria and amoebae in biofilms and water distribution systems as a rapid and sensitive semiautomated technique compared with conventional microbiology. It has been shown that the results of flow cytometric analysis of total Legionella pneumophila cells have a strong statistical correlation with the numbers of Legionella cfu by BCYE plate counting (BCYE PC) methods for biofilms and planktonic phases. There are also strong statistical correlations between flow cytometric analysis and epifluorescent microscopic (EFM) analysis (direct counting) for determination of bacteria, including Legionella, Escherichia coli, Salmonella, Pseudomonas and amoebae, and total and viable cells in pure cultures, water distribution systems and biofilms. The flow cytometric protocols have been set up and optimised for the analysis of environmental microorganisms. The novel fluorescent dyes and immunofluorescence antibodies from the most current commercial dyes also have been screened and the staining protocols have been optimised and adopted for flow cytometric analysis and direct counting by epifluorescent microscopy. The tap water biofilms and river water biofilms were analysed by the flow cytometer and direct counting methods as well as by conventional microbiological methods (plate counting). The bacterial populations in real water distribution systems have been fully investigated and the total, viable bacteria were determined by the above methods. The findings of this work have practical implications with respect to the rapid and automatic detection and predictions of Legionella spp. and the risk assessment from biofilms and water environments.

Multi-objective design or extended design of Water Distribution Systems (WDSs) has received more attention in recent years. It is of particular interest for obtaining the trade-offs between cost and hydraulic benefit to support the decision-making process. The design problem is usually formulated as a multi-objective optimisation problem, featuring a huge search space associated with a great number of constraints. Multi-objective evolutionary algorithms (MOEAs) are popular tools for addressing this kind of problem because they are capable of approximating the Pareto-optimal front effectively in a single run. However, these methods are often held by the “No Free Lunch” theorem (Wolpert and Macready 1997) that there is no guarantee that they can perform well on a wide range of cases. To overcome this drawback, many hybrid optimisation methods have been proposed to take advantage of multiple search mechanisms which can synergistically facilitate optimisation. In this thesis, a novel hybrid algorithm, called Genetically Adaptive Leaping Algorithm for approXimation and diversitY (GALAXY), is proposed. It is a dedicated optimiser for solving the discrete two-objective design or extended design of WDSs, minimising the total cost and maximising the network resilience, which is a surrogate indicator of hydraulic benefit. GALAXY is developed using the general framework of MOEAs with substantial improvements and modifications tailored for WDS design. It features a generational framework, a hybrid use of the traditional Pareto-dominance and the epsilon-dominance concepts, an integer coding scheme, and six search operators organised in a high-level teamwork hybrid paradigm. In addition, several important strategies are implemented within GALAXY, including the genetically adaptive strategy, the global information sharing strategy, the duplicates handling strategy and the hybrid replacement strategy. One great advantage of GALAXY over other state-of-the-art MOEAs lies in the fact that it eliminates all the individual parameters of search operators, thus providing an effective and efficient tool to researchers and practitioners alike for dealing with real-world cases. To verify the capability of GALAXY, an archive of benchmark problems of WDS design collected from the literature is first established, ranging from small to large cases. GALAXY has been applied to solve these benchmark design problems and its achievements in terms of both ultimate and dynamic performances are compared with those obtained by two state-of-the-art hybrid algorithms and two baseline MOEAs. GALAXY generally outperforms these MOEAs according to various numerical indicators and a graphical comparison tool. For the largest problem considered in this thesis, GALAXY does not perform as well as its competitors due to the limited computational budget in terms of number of function evaluations. All the algorithms have also been applied to solve the challenging Anytown rehabilitation problem, which considers both the design and operation of a system from the extended period simulation perspective. The performance of each algorithm is sensitive to the quality of the initial population and the random seed used. GALAXY and the Pareto-dominance based MOEAs are superior to the epsilon-dominance based methods; however, there is a tie between GALAXY and the Pareto-dominance based approaches. At the end, a summary of this thesis is provided and relevant conclusions are drawn. Recommendations for future research work are also made.

Spring water bottled and sold for human consumption can only be subjected to certain treatment processes such as separation from unstable constituents by decantation, filtration and aeration, ultraviolet irradiation and ozonation. A spring water distribution system in the Western Cape, South Africa was experiencing microbiological problems. The aim of the study was to investigate bacterial contamination in the spring water distribution system and the application of bioremediation as treatment technology. Sampling at various points in the spring water distribution bottling system started in February 2004 and continued until November 2004. The acceptable microbiological limits for bottled spring water clearly states that the total viable colony count should be < 100 organisms per ml of water. Analysis of samples by the heterotrophic plate count (HPC) technique indicated significantly (p < 0.05) high counts which did not conform to the microbiological limit. The heterotrophic plate counts recorded for weeks one, four, eight & 46 in the final bottled water (Site J) were 3.66 x 107 cfu/ml, 9.0 x 106cfu/ml, 2.35 x 107 cfu/ml and 5.00 x 104 cfu/ml, respectively. The total cell counts [Flow cytometry analyses (FCM)] recorded for week one, four, eight & 46 in the final bottled water (Site J) were 5.44 x 107 microorganisms/ml, 8.36 x 107 microorganisms/ml, 9.09 x 107 microorganisms/ml and 5.70 x 107 microorganisms/ml, respectively. The higher viable total cell counts(FCM) indicate that flow cytometry was able to detect cells in the water sample that enter a viable but not culturable state and that the heterotrophic plate count technique only allowed for the growth of the viable and culturable cells present in the water samples. This indicated that the HPC is not a clear indication of the actual microbial population in the water samples. It could be concluded that FCM technique was a more reliable technique for the enumeration of microbial populations in bottled water samples. Various organisms were identified by means of the Polymerase Chain Reaction (PCR) using 16S rRNA specific primers. Purified PCR amplicons were sequenced and Phylogenetic trees were constructed. Neighbour-joining phylogenetic tree analysis of the bacterial species present in the water samples was performed. The dominant bacterial isolates that were sequenced from the various water samples throughout weeks one, four, eight and 46 were Bacillus sp. and Enterobacteriaceae. The pathogenic species isolated throughout the sampling period included Escherichia sp., Pseudomonas sp., Shigella boydii, Bacillus and Staphylococcus sp. A laboratory-scale bioreactor was constructed and water samples were analysed over a period of two weeks. Water samples were analysed using FCM and Direct Acridine Orange Count (DAOC) in conjunction with epiflourescence microscopy (EM). The FCM counts ranged from 1.53 x 107 microorganisms/ml in the initial sample (Day 0) to 1.16 x 107 microorganisms/mℓ in the final sample (Day 13). The results indicated a 24% decrease in the microbial numbers however, it was still above the limit of < 100 organisms/ml as set out by the South African Standards of Bottled Water, (2003). The total cell counts obtained by the DAOC method ranged from 1.43 x 106 microorganisms/ml to 9.54 x 105 microorganism/ml on day 13 (final). The results indicated a 33% decrease in microbial numbers. The total cell counts analysed by flow cytometry fluctuated throughout the sampling period. The total cell counts obtained from the DAOC method were lower in all the water samples when compared to the total counts obtained by flow cytometric analyses. Even though the FCM counts fluctuated throughout the sampling period, results clearly show that the FCM method yielded more accurate data for total cell counts than the DAOC method. Due to external environmental conditions such as changes in the weather conditions the results fluctuated and the final results clearly indicated that further studies are required to optimise the bioreactor system for its application in the spring water industry.

Mathematical models of water distribution systems (WDS) serve as tools to represent the real systems for many different purposes. Calibration is the process of fine tuning the model parameters so that the real system is well-represented. In practice, calibration is performed considering all information is deterministic. Recent researches have incorporated uncertainties caused by field measurements into the calibration process. Parameter (D-optimality) and predictive (I-optimality) uncertainties have been used as indicators of how well a system is calibrated.This study focuses on a methodology that extends previous work by considering the impact of uncertainty on decisions that are made using the model. A new sampling strategy that would take into account the accuracy needed for different model objectives is proposed.The methodology uses an optimization routine that minimizes square differences between the observed and model calculated head values by adjusting the model parameters. Given uncertainty in measurements, the parameters from this nonlinear regression are imprecise and the model parameter uncertainties are computed using a first order second moment (FOSM) analysis. Parameter uncertainties are then propagated to model prediction uncertainties through a second FOSM analysis. Finally, the prediction uncertainty relationships are embedded in optimization problems to assess the effect of the uncertainties on model-based decisions. Additional data is collected provided that the monetary benefits of reducing uncertainties can be addressed.The proposed procedure is first applied on a small hypothetical network for a system expansion design problem using a steady state model. It is hypothesized that the model accuracy and data required calibrating WDS models with different objectives would require different amount of data. A real-scale network for design and operation problems is studied using the same methodology for comparison. The effect of a common practice, grouping pipes in the system, is also examined in both studies.Results suggest that the cost reductions are related to the convergence of the mean parameter estimates and the reduction of parameter variances. The impact of each factor changes during the calibration process as the parameters become more precise and the design is modified. Identification of the cause of cost changes, however, is not always obvious.