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

被引：85

作者：

Yildiz, Zeynep ^{[1
]}

Uzun, Harun ^{[1
]}

Ceylan, Selim ^{[1
]}

Topcu, Yildiray ^{[1
]}

机构：

[1] Ondokuz Mayis Univ, Dept Chem Engn, TR-55139 Samsun, Turkey

来源：

BIORESOURCE TECHNOLOGY | 2016年 / 200卷

关键词：

Co-combustion; Hazelnut husk; Lignite coal; TGA; Artificial neural network; THERMOGRAVIMETRIC ANALYSIS; COMBUSTION BEHAVIOR; PYROLYSIS KINETICS; TORREFIED BIOMASS; BITUMINOUS COAL; SLUDGE; WASTE;

D O I：

10.1016/j.biortech.2015.09.114

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

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.

引用

页码：42 / 47

页数：6

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