Process Modeling And Control Of Enhanced Coagulation

Process Modeling and Control of Enhanced Coagulation

Develops and evaluates artificial neural network (ANN) models for clarified water turbidity and total organic carbon. Determines which factors are most important in optimizing enhanced coagulation. Also develops protocols for source data analysis, model architecture selection, model training, and model evaluation. Studies the use of ANN models in process control.

Artificial Intelligence Systems for Water Treatment Plant Optimization

Guidance Manual for Coagulant Changeover

This manual is a source document for utilities that are considering a coagulant changeover. It is intended to provide an appreciation of what must be considered for a successful changeover based on the input of U.S. and Canadian utilities (Chapters 1 and 6). New regulatory requirements will likely have the broadest and most substantial impact on primary coagulant use (Chapter 3). The Interim Enhanced Surface Water Treatment Rule (IESWTR) and Stage 1 Disinfectant and Disinfection Byproducts Rule (Stage 1 DBPR) will make finished water requirements more stringent to address microbial removal and the impacts of disinfection. Enhanced Coagulation and/or other operational and treatment practices will be used to achieve these requirements. The science of coagulation (Chapter 4) requires a special focus to address the intricacies of coagulation chemistry. The manual provides a step-by-step methodology to conduct a coagulant changeover using a detailed protocol (Chapter 5) -- background, executive summary.