Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
584647 | Journal of Hazardous Materials | 2007 | 7 Pages |
Abstract
In this work a new technique dealing with differential neural network observer (DNNO), which is related with differential neural networks (DNN) approach, is applied to estimate the anthracene dynamics decomposition and to identify the kinetic parameters in a contaminated model soil treatment by simple ozonation. To obtain the experimental data set, the model soil (sand) is combined with an initial anthracene concentration of 3.24Â mg/g and treated by ozone (with the ozone initial concentration 16Â mg/L) during 90Â min in a reactor by the “fluid bed” principle. The anthracene degradation degree was controlled by UV-vis spectrophotometry and HPLC techniques. Based on the HPLC data, the obtained results confirm that anthracene may be decomposed completely in the solid phase by simple ozonation during 20Â min and by-products of ozonation are started to be destroyed after 30Â min of treatment. In the ozonation process the ozone concentration in the gas phase at the reactor outlet is registered by an ozone detector. The variation of this parameter is used to obtain the summary characteristic curve of the anthracene ozonation (ozonogram). Then, using the experimental decomposition dynamics of anthracene and the ozonogram, the proposed DNNO is trained to reconstruct the anthracene decomposition and to estimate the anthracene ozonation constant using the DNN technique and a modified Least Square method.
Keywords
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Health and Safety
Authors
Tatyana Poznyak, Alejandro GarcÃa, Isaac Chairez, Miriam Gómez, Alexander Poznyak,