Investigating the co-combustion characteristics of oily sludge and ginkgo leaves through thermogravimetric analysis coupled with an artificial neural network  

作　　者：LI ShuChen NIU ShengLi HAN KuiHua LI YingJie WANG YongZheng LU ChunMei 

机构地区：[1]Shandong Engineering Laboratory for High-efficiency Energy Conservation and Energy Storage Technology&Equipment,School of Energy and Powering,Shandong University,Jinan 250061,China

出　　处：《Science China(Technological Sciences)》2022年第2期261-271,共11页中国科学（技术科学英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.51876106);the Primary Research&Development Plan of Shandong Province,China(Grant No.2018GGX104027);the Young Scholars Program of Shandong University(Grant No.2015WLJH33)。

摘　　要：The co-combustion characteristics of oily sludge and ginkgo leaves(GL) in an oxy-fuel atmosphere are investigated via thermogravimetric analysis coupled with an artificial neural network. The combustion characteristics of blends improve as the GL mass ratio increases. The interaction indices used to evaluate the interaction between the two solid combustibles present a complex nonlinear relationship in different stages. The Flynn-Wall-Ozawa and Kissinger-Akahira-Sunose methods are used to calculate the activation energy of the blends, which increases with an increase in the oxygen concentration, in different atmospheres. Compared with the radial basis function, the backpropagation neural network performs better in predicting the combustion curve of the blends.

关 键 词：oily sludge CO-COMBUSTION oxy-fuel atmosphere thermogravimetric analysis artificial neural network 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] X703[自动化与计算机技术—控制科学与工程]