Coal ash fusion temperature forecast based on Gaussian regularization RBF neural network

2011 ◽  
Author(s):  
WeiMing Ding ◽  
XiaoLi Wu ◽  
HaiKun Wei
Keyword(s):  
Neural Network ◽  
Rbf Neural Network ◽  
Coal Ash ◽  
Fusion Temperature ◽  
Temperature Forecast ◽  
Ash Fusion Temperature

scholarly journals Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

2016 ◽  
Vol 40 ◽  
pp. 05010 ◽  
Author(s):  
Suzhen Miao ◽  
Qingyin Jiang ◽  
Hua Zhou ◽  
Jia Shi ◽  
Zhikai Cao
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Coal Ash ◽  
Fusion Temperature ◽  
Modeling And Prediction ◽  
Ash Fusion Temperature

A Thermodynamically Based Model for Ash Fusion Temperature

1987 ◽  
Vol 109 (3) ◽  
pp. 124-128 ◽  
Author(s):  
R. R. Rhinehart ◽  
A. A. Attar
Keyword(s):  
Standard Error ◽  
Coal Ash ◽  
Model Parameters ◽  
Fusion Temperature ◽  
Ash Composition ◽  
Parameter Correlation ◽  
Ash Fusion Temperature ◽  
Wide Range

This paper describes a thermodynamically based correlation between coal ash fusion temperatures and ash composition. A wide range of data from the literature was used to obtain the values of model parameters. A seven-parameter correlation is proposed which permits predicting the ash fusion temperature with a standard error ± 65°C or better.

Effect of High-Efficiency Flux on the Melting Characteristics of Coal Ash

2013 ◽  
Vol 295-298 ◽  
pp. 3094-3097 ◽  
Author(s):  
Han Xu Li ◽  
Zi Li Zhang ◽  
Yong Xin Tang
Keyword(s):  
Melting Temperature ◽  
Coal Gasification ◽  
High Efficiency ◽  
Coal Ash ◽  
Fusion Temperature ◽  
Gasification Process ◽  
Ash Fusion Temperature ◽  
Melting Characteristics ◽  
Temperature Detector ◽  
Ash Melting

High-efficiency flux was developed to lower the ash fusion temperature of coal LQ and reduce the addition content in coal gasification process. The effect of high-efficiency flux on the coal ash melting temperature and mineral transformation were studied by ash fusion temperature detector and XRD (X-ray diffractometer) respectively in reducing atmosphere. Compared with limestone flux, the high-efficiency flux can decrease the coal ash melting temperature effectively with half addition content. The ash flow temperature (FT) of coal LQ can be lowered to less than 1350°C with the addition of 3% high-efficiency flux ,while limestone flux need to add more than 8% to reach to this temperature. With the high-efficiency flux added, cordierite, anorthite and Mg-Fe-Al oxide were formed at high temperature, which is the main reason to sharply decrease the ash fusion temperature.

Ash Composition Influence on Fusibility of Coal Ash

2013 ◽  
Vol 448-453 ◽  
pp. 3009-3012
Author(s):  
Na Gao ◽  
Sheng Hua Liu ◽  
Yan Hong Guo
Keyword(s):  
High Temperature ◽  
Physical Properties ◽  
Mineral Composition ◽  
General Trend ◽  
Coal Ash ◽  
Xrd Analysis ◽  
Fusion Temperature ◽  
Basic Oxide ◽  
Ash Composition ◽  
Ash Fusion Temperature

The coal of Zichang was selected as the sample coal, the physical properties of the ash is analyzed with ICP-AES. The ash fusion temperature was researched by adding different basic oxide contents. The results show that the general trend is decrease firstly, and then increase when adding basic oxides. Blended ash fusion temperatures do not change linearly with blending ratios and ash fusion will decrease when adding the contents of CaO, Na2O and MgO, but the effect is different. Na2O is best and CaO is second. Mineral composition and type at addition oxides were determined by XRD analysis. Some combinations of component coals mineral produce eutectic minerals at high temperature;It can explain the reason of oxides decrease the ash fusion. Vitreous minerals are formed to explain increase the fusion temperature.

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