Characterization and rheological studies of Indian high ash coal water slurries: effect of particle size distribution with artificial neural network (ANN) analysis

In present work, rheological behavior of coal-water slurries (CWSs), prepared using high-ash coal taken from Sijua (SJ) coal field area in Jharkhand (India), was analyzed. Consistency in particle size distribution is challenging for rheological studies. Different particle size distributions were made to evaluate their impact on slurry flow properties. Slurries prepared from these particle size distributions were tested at concentrations of 44-56%, and their rheological behaviors were analyzed across temperatures ranging from 25 degrees C to 55 degrees C using an Anton Paar MCR 102 rheometer over a shear rate range of 1-1000 s(-1). The findings exhibit that all slurry formulations show pseudoplastic behavior; concentration of 52% shows superior fluidity at 30 degrees C, which is evidenced by the lowest yield stress (0.8471 Pa) and moderate apparent viscosity (similar to 75 mPa.s) at a shear rate of 100 s(-1). Temperature influences flow behavior, reducing pseudoplasticity at higher temperatures. Herschel - Bulkley model accurately describes the flow behavior of the slurries, offering precise predictions of yield stress, consistency, and flow indices. This was further corroborated by artificial neural network (ANN) analysis, highlighting robustness of the model. Results underscore the importance of optimizing particle size distribution and concentration for improved CWS performance, offering insights into efficient slurry design for industrial applications.