What is it about?

Artificial neural networks (ANN) are applied to predict the local heat transfer coefficient for heating surfaces in the combustion chamber of the 260 MWe circulating fluidized bed boiler (CFB) boiler.

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Why is it important?

The present work introduces a way of predicting the local heat transfer coefficient in the combustion chamber of the circulating fluidized bed boiler by the ANN approach. After the training ANN model can be used to predict heat transfer coefficient via non-iterative calculations with a low processing time and small memory resources, as an answer to a new stimuli set, not previously presented to the network.

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This page is a summary of: Modeling of heat transfer coefficient in the furnace of CFB boilers by artificial neural network approach, International Journal of Heat and Mass Transfer, July 2012, Elsevier,
DOI: 10.1016/j.ijheatmasstransfer.2012.03.066.
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