School of Civil & Environmental Engineering (ETDs)

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Start date: 2024Subject: search.filters.subject.SDG-6: Clean water and sanitation

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    Effect of pipeline pigging on raw water pipeline flow rate and energy consumption
    (University of the Witwatersrand, Johannesburg, 2024-02) Phillip, Neil Claude; Ndiritu, John
    Pipeline pigging is a widely used method of pipeline cleaning to improve the hydraulic efficiency of a pipeline system, reduce deposits within a pipeline, reduce operational costs and improve water quality. With insufficient pipe cleaning, pipeline deposits accumulate within the pipeline which reduces the cross-sectional flow area of the pipeline and increases the friction losses in the pipeline. This subsequently reduces the operating flow rate, increases the pumping cost of the system, and reduces the water supply to the surrounding area. Therefore, the study aimed to investigate the hydraulic improvements and operational cost savings of a pipeline system after pigging and to determine when pigging should be done. A case study of the Tayside high lift pump station in South Africa was used for this investigation. Results indicate that pigging removes deposits and sediments from the pipelines thereby increasing the flow rate while reducing the cost of pumping substantially. The increase in flow rate calculated from the case study was 23.9% after one of the pigging operations in 2016. In addition, the pigging operations completed yearly also indicated a flow rate increase after pigging. The study showed that the increase in sediment levels of the raw water in the rainy season led to a reduction in the hydraulic capacity of the pipeline indicating an increase in sediment deposition in the pipeline. Life cycle cost analysis of the case study system obtained annual cost savings of R991,800.59 over a 50-year period. Based on the findings, a flexible routine for pigging based on the reduction in the hydraulic capacity of the pipeline is proposed to cater for the variability in levels of sediment in the raw water in alignment to the rainfall and streamflow patterns. This allows the pipeline to operate at the lowest energy cost and at the highest possible flow rate.
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    Addressing high dimensionality in water quality modelling in water distribution networks
    (University of the Witwatersrand, Johannesburg, 2024-02) Machweu, Morongwa Ednah; Taigbenu, Akpofure
    Water quality models are the most effective tools for characterizing water quality conditions, assessing the effects of water pollution, and supporting decision-makers with water quality management. They can be utilised for detecting the variations in the water quality parameters. Despite the usefulness of water quality models, an appropriate and simple water quality descriptor for a particular application, considering the high dimensionality of various water quality parameters, remains a challenge (Chapman, 1992). To address this high dimensionality, a single dimensionless index is commonly used to describe water quality for a particular application. While pollution loads at various points in a river reach have been widely assessed by studies using water quality indices, little research has been done on water distribution networks with service reservoirs and a variation of loading conditions. In a water distribution network, service reservoirs function similarly to rivers in that they have complicated mixing mechanisms, are subject to a variety of water quality factors, and are sized and located differently. The most common water quality indices require the formation of subindices and weights to avoid ambiguity, eclipsing and rigidity. The Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) does not require the formation of sub-indices and weights, thus providing a simplified way of describing water quality. This study investigates the use of the CCME WQI to address high dimensionality in water quality modelling of water distribution networks, taking into consideration the locations of multiple service reservoirs. This study was carried out primarily for decision-making and design optimization purposes only. Using EPANET 2.2, four hydraulically optimised solutions (which satisfied minimum pressure requirements) were further analysed for water quality performance. This was achieved by incorporating simulated data on three water quality variables (chlorine residual, water age and THM concentration) into the CCME WQI for a hypothetical water distribution network, Anytown. The results indicate that two of the four hydraulically optimised solutions achieved excellent water quality levels. This study has demonstrated the usefulness of a dimensionless index as a proxy for multiple water quality variables of a water distribution system in facilitating decision-making.
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    Improving the Penalty-Free Multi-Objective Evolutionary Design Optimization of Water Distribution Systems
    (University of the Witwatersrand, Johannesburg, 2024-02) Kambalame, Emily; Ndiritu, John
    Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions out performed other retention allocations by identifying the optimal solution with the fewest function evaluations.