The main goal of the present study was not only to deshale (remove pure rock) raw coal extracted from Illinois mines but also to assess the maximum ash separation efficiency and sulfur rejection achievable using the FGX Dry Separator for cleaning raw coals of varying cleaning characteristics. A Model FGX-1 Dry Separator with feed throughput capacity of 10 tph was extensively tested at the Illinois Coal Development Park using multiple coal samples having distinctly different cleaning characteristics. Statistically designed experimental programs were conducted to indentify critical process variables and to optimize FGX Dry Separator performance by systematic adjustments of critical process variable parameters.The coal-cleaning performance of the FGX Dry Separator was evaluated for the particle size range of 4.75-63.5 mm in most cases, although FGX Dry Separator feed consisted of nominal 7minus;63.5 mm run-of-mine coals. Deck vibration frequency, longitudinal deck angle, feeder frequency, and baffle plate height were identified as critical process variables for the FGX Dry Separator. The best cleaning performance obtained from the FGX Dry Separator was described by specific gravity of separation (SG 50 ) and probable error (Ep) values of 1.98 and 0.17, respectively. For a relatively easy-to-clean coal (having a Cleaning Index of 0.72), only about 0.42% of the clean coal (i.e., 1.6 float fraction) present in the feed was lost to the tailings stream. For a relatively difficult-to-clean coal (having a Cleaning Index of 0.53), about 0.98% of the clean coal present in the feed was lost to the tailings stream. The positive impact of having fine materials in the FGX feed stream was also noted in this study. A modified log-logistic partition model was developed using experimental data reported in literature and validated using new experimental data generated in this study. The results showed that this model could be effectively used to predict the FGX Dry Separator coal-cleaning performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.