Journal
CHEMICAL ENGINEERING & TECHNOLOGY
Volume 35, Issue 12, Pages 2125-2132Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/ceat.201200269
Keywords
Modeling and simulation; Neural networks; Photochemical treatment; Solar reactor design
Categories
Funding
- CAPES
- CNPq
- FAPESP
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Solar reactors can be attractive in photodegradation processes due to lower electrical energy demand. The performance of a solar reactor for two flow configurations, i.e., plug flow and mixed flow, is compared based on experimental results with a pilot-scale solar reactor. Aqueous solutions of phenol were used as a model for industrial wastewater containing organic contaminants. Batch experiments were carried out under clear sky, resulting in removal rates in the range of 96100?%. The dissolved organic carbon removal rate was simulated by an empirical model based on neural networks, which was adjusted to the experimental data, resulting in a correlation coefficient of 0.9856. This approach enabled to estimate effects of process variables which could not be evaluated from the experiments. Simulations with different reactor configurations indicated relevant aspects for the design of solar reactors.
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