期刊
FUEL PROCESSING TECHNOLOGY
卷 91, 期 8, 页码 831-836出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.fuproc.2009.10.013
关键词
Slag; Viscosity; Artificial neural network; Model
资金
- Natural Sciences and Engineering Research Council of Canada
Threshold slag viscosity heuristics are often used for the initial assessment of coal gasification projects. Slag viscosity predictions are also required for advanced combustion and gasification models. Due to unsatisfactory performance of theoretical equations, an artificial neural network model was developed to predict slag viscosity over a broad range of temperatures and slag compositions. This model outperforms other slag viscosity models, resulting in an average error factor of 5.05 which is lower than the best obtained with other available models. Genesee coal ash viscosity predictions were made to investigate the effect of adding Canadian limestone and dolomite. The results indicate that magnesium in the fluxing agent provides a greater viscosity reduction than calcium for the threshold slag tapping temperature range. (C) 2009 Published by Elsevier B.V.
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