Artificial neural network approach for rheological characteristics of coal-water slurry using microwave pre-treatment

摘要

Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level（900 W） in microwave oven. The microwave exposure times were fixed at60 s and 120 s. A rheology characteristic for microwave pre-treatment of coal-water slurry（CWS） was performed in an online Bohlin viscometer. The non-Newtonian character of the slurry follows the rheological model of Ostwald de Waele. The values of n and k vary from 0.31 to 0.64 and 0.19 to 0.81 Pa·sn,respectively. This paper presents an artificial neural network（ANN） model to predict the effects of operational parameters on apparent viscosity of CWS. A 4-2-1 topology with Levenberg-Marquardt training algorithm（trainlm） was selected as the controlled ANN. Mean squared error（MSE） of 0.002 and coefficient of multiple determinations（R~2） of 0.99 were obtained for the outperforming model. The promising values of correlation coefficient further confirm the robustness and satisfactory performance of the proposed ANN model.