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|Title:||DrCT®: Developing tools for improved disinfection control within water distribution systems|
|Other Titles:||DrCT(R): Developing tools for improved disinfection control within water distribution systems|
|Citation:||Disinfection 2005: Sharing Disinfection Technologies: Water, Wastewater, Water Reuse and Biosolids, Mesa, Arizona, USA, Feb.6–9 2005 / Water Environment Federation & American Water Works Association & International Water Association, Session 11: Innovative Technologies: pp.1-29|
|Publisher:||Water Environment Federation/American Water Works Association/International Water Association|
|Conference Name:||Disinfection 2005 Conference (2005 : Mesa, Arizona)|
|Mike Holmes, Chris Chow, Robert May, Alex Badalyan, Fiona Fitzgerald, John Nixon, Graeme Dandy, and Holger R. Maier|
|Abstract:||The challenging operating conditions experienced by many water utilities in Australia make the supply of good quality drinking water at the customer tap difficult. Effective and well-operated treatment and distribution barriers are needed, as: raw water can be high in dissolved organic carbon (DOC); water distribution systems (WDSs) can cover large distances; water temperatures can exceed 30oC; and variation in summer–winter flows can be large. In many cases, the maintenance of a positive disinfectant residual throughout the WDS is a critical barrier if microbiological compliance is to be achieved. Establishing the optimum disinfectant dose/residual set-point at the outlet of the water treatment plant (WTP) is a complex task. If the dose/set-point is too low, disinfectant residual may not be present at the end of the WDS and bacterial regrowth can occur. If it is too high, increased disinfection byproduct formation, customer complaints, and excessive operating costs may occur. This paper describes progress in a 3½-year collaborative research project undertaken by a number of Australian universities and water utilities aimed at developing tools to improve control of secondary disinfection. The project is investigating if it is possible to use data from locations in the WDS, measured using online sensors, to predict in advance water quality at those and at other points in the WDS, using a range of tools including artificial neural networks (ANN), and then to use these predictions to optimise disinfection dosing regimes at the WTP and/or booster stations using control theory.|
|Keywords:||Secondary disinfection; control; chlorine demand; chloramine demand; artificial neural network; onlinesensors; DrCT®|
|Appears in Collections:||Civil and Environmental Engineering publications|
Environment Institute publications
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