Neurocomputing approach for the prediction of NOx emissions from CFBC in air-fired and oxygen-enriched atmospheres

Jarosław Krzywański, Wojciech Nowak

Abstract


This paper presents a way of predicting NOx emissions from circulating fluidized bed combustors (CFBC) in air-fired and oxyfuel
conditions, using the Artificial Neural Network (ANN) Approach. The Original Neural Networks Model was successfully
applied to calculate the NOx (i.e. NO + NO2) emissions from coal combustion under air-fired and oxygen-enriched conditions
in several CFB boilers. The ANN model was shown to give quick and accurate results in response to the input pattern. The
NOx emissions, evaluated using the developed ANN model are in good agreement with the experimental results.

Keywords


Nitrogen oxides; Circulating fluidized bed; Oxy combustion; Artificial neural networks

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