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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/31630

Title: Coagulation Optimization to Minimize and Predict the Formation of Disinfection By-products
Authors: Wassink, Justin
Advisor: Andrews, Robert C.
Department: Civil Engineering
Keywords: water treatment
drinking water
coagulation
disinfection by-products
process optimization
artificial neural network
Issue Date: 4-Jan-2012
Abstract: The formation of disinfection by-products (DBPs) in drinking water has become an issue of greater concern in recent years. Bench-scale jar tests were conducted on a surface water to evaluate the impact of enhanced coagulation on the removal of organic DBP precursors and the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). The results of this testing indicate that enhanced coagulation practices can improve treated water quality without increasing coagulant dosage. The data generated were also used to develop artificial neural networks (ANNs) to predict THM and HAA formation. Testing of these models showed high correlations between the actual and predicted data. In addition, an experimental plan was developed to use ANNs for treatment optimization at the Peterborough pilot plant.
URI: http://hdl.handle.net/1807/31630
Appears in Collections:Master

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