Development of a two-tier prioritisationalgorithm for the replacement of water reticulation pipes
Thesis (MEng)--Stellenbosch University, 2018.
ENGLISH ABSTRACT: Water pipe replacement in ageing water networks needs to be prioritised within constraints of limited municipal budgets. Relatively higher water pipe failure frequency in a distribution zone could point to a higher replacement priority. Priorities are typically determined based on historically recorded pipe failures, but actual pipe failure data is often not available – especially in developing countries. Pipe failure records may be available for certain zones in a particular system, while no data may be available in other zones of the same system. Replacement priority cannot be limited exclusively to zones with failure data, so a method was devised to spatially extrapolate pipe failures from zones with failure data to other zones where no knowledge of historical failures is available. An algorithm was developed for this purpose to prioritise pipe replacement based on a two-tier structure, comprising physical and hydraulic characteristics. The following model parameters were incorporated: pipe material, diameter, remaining useful life, static pressure, residual pressure and reserve pressure ratio. Actual pipe failure frequency data for a South African study site with 2021 km of pipes and 12802 reported failure events over a period of 180 consecutive months was obtained and used to devise the model. Actual pipe failures were linked to the different model parameters, with all parameter values known per pipe in the case study area. Pipe failure likelihood index values were then calculated for each pipe element in the water network model (as failure/year/meter). Each pipe was then prioritised for replacement in terms of a failure likelihood index, and grouped per water distribution zone. The water distribution zones were ranked for replacement prioritisation. The model was verified by evaluating failure likelihood index values and comparing replacement priority per zone based on actual data to the model results (for those zones with known data). The model was subsequently used to extrapolate the replacement priority to other zones without failure records in the case study area, with acknowledgement of in accuracy due to the lack of model validation. The model results are illustrative and apply to the specific study site – results should not be generalised. The results were represented spatially in GIS format, allowing the user to visually identify the most critical areas for pipe replacement. Future research could involve model validation and possible application beyond the study sample.
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