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

Yildiz Z., Uzun H., Ceylan S., Topcu Y.

BIORESOURCE TECHNOLOGY, cilt.200, ss.42-47, 2016 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 200
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.biortech.2015.09.114
  • Dergi Adı: BIORESOURCE TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.42-47
  • Anahtar Kelimeler: Co-combustion, Hazelnut husk, Lignite coal, TGA, Artificial neural network, THERMOGRAVIMETRIC ANALYSIS, COMBUSTION BEHAVIOR, PYROLYSIS KINETICS, TORREFIED BIOMASS, BITUMINOUS COAL, SLUDGE, WASTE
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000 degrees 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. (C) 2015 Elsevier Ltd. All rights reserved.