Application of artificial neural networks to co-combustion of hazelnut husk–lignite coal blends

•First study on application of ANN model to co-combustion process.•The coefficient of determination for the developed model was 0.9995.•ANN model predicted TG curves for co-combustion of blends effectively. The artificial neural network (ANN) theory is applied to thermal data obtained by non-isother...

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Bibliographic Details
Published in:Bioresource technology 2016-01, Vol.200, p.42-47
Main Authors: Yıldız, Zeynep, Uzun, Harun, Ceylan, Selim, Topcu, Yıldıray
Format: Article
Language:English
Subjects:
Artificial neural network
Co-combustion
Coal - analysis
Corylus - chemistry
Hazelnut husk
Lignite coal
Neural Networks (Computer)
Renewable Energy
Temperature
TGA
Thermogravimetry
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Summary:•First study on application of ANN model to co-combustion process.•The coefficient of determination for the developed model was 0.9995.•ANN model predicted TG curves for co-combustion of blends effectively. The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000°C at different heating rates in air to study co-combustion of hazelnut husk (HH)–lignite coal (LC) blends of various composition. The heating rate, blend ratio and temperature were used in the ANN analysis to predict the TG curves of the blends as parameters that affect the thermal behavior during combustion. The ANN model provides a good prediction of the TG curves for co-combustion with a coefficient of determination for the developed model of 0.9995. The agreement between the experimental data and the predicted values substantiated the accuracy of the ANN calculation.
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2015.09.114