Neurocomputing approach for the prediction of NOx emissions from CFBC in air-fired and oxygen-enriched atmospheres
Abstract
This paper presents a way of predicting NOx emissions from circulating fluidized bed combustors (CFBC) in air-fired and oxyfuelconditions, using the Artificial Neural Network (ANN) Approach. The Original Neural Networks Model was successfullyapplied to calculate the NOx (i.e. NO + NO2) emissions from coal combustion under air-fired and oxygen-enriched conditionsin several CFB boilers. The ANN model was shown to give quick and accurate results in response to the input pattern. TheNOx emissions, evaluated using the developed ANN model are in good agreement with the experimental results.References
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fluidized bed combustion process and no x emissions using selforganizing
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Published
2017-07-21
How to Cite
KRZYWAŃSKI, Jarosław; NOWAK, Wojciech.
Neurocomputing approach for the prediction of NOx emissions from CFBC in air-fired and oxygen-enriched atmospheres.
Journal of Power Technologies, [S.l.], v. 97, n. 2, p. 75--84, july 2017.
ISSN 2083-4195.
Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/646>. Date accessed: 20 apr. 2024.
Issue
Section
Combustion and Fuel Processing
Keywords
Nitrogen oxides; Circulating fluidized bed; Oxy combustion; Artificial neural networks
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