Prediction via neural networks of the residual hydrogen peroxide used in photo-fenton processes for effluent treatment
Nenhuma Miniatura disponível
Data
2007-08-01
Autores
Guimaraes, Oswaldo L. C.
Queiroz de Aquino, Henrique Otavio
Oliveira, Ivy S.
Villela, Darcy Nunes
Izario, Helcio Jose
Siqueira, Adriano Francisco
Silva, Messias Borges
Título da Revista
ISSN da Revista
Título de Volume
Editor
Wiley-Blackwell
Resumo
This communication proposes the use of neural networks in the prediction of residual concentrations of hydrogen peroxide from the treatment of effluents through Advanced Oxidative Processes (AOP's), in particular, the photo-Fenton process. To verify the efficiency of the oxidative process, the Chemical Oxygen Demand (COD) parameter, the values of which may be modified by the presence of oxidizing agents such as residual hydrogen peroxide, is frequently taken in account. The analysis of the H2O2 interference was performed by spectrophotometry at 450 nm wavelength, via the monitoring of the reaction of ammonia with metavanadate. The results of the hydrogen peroxide residual concentration were modeled via a feedforward neural network, with the correlation coefficients between actual and predicted values above 0.96, indicating good prediction capacity.
Descrição
Palavras-chave
hydrogen peroxide, neural networks, photo-Fenton
Como citar
Chemical Engineering & Technology. Weinheim: Wiley-v C H Verlag Gmbh, v. 30, n. 8, p. 1134-1139, 2007.