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Original Article

A kinetic model approach for predicting coke reactivity index from coal and coal blend properties

, , , , , & show all
Pages 1318-1335 | Received 29 Aug 2019, Accepted 27 Dec 2019, Published online: 24 Jan 2020
 

ABSTRACT

A novel method has been developed to estimate coke reactivity index (CRI) from coal properties through a kinetic approach. The model was derived from mass balance with a kinetic model of batch reactor CRI test. The parameters of kinetic model were optimized using non-linear least squared method. Three main properties of coals, i.e., Fe2O3 content, volatile matter, and coal rank were selected to predict the CRI. The predicted CRI value was in a good agreement with the CRI data. The standard error was less than 5. Coke strength after reaction (CSR) was predicted using linear regression of the CSR and CRI data. The estimated CSR was in good agreement with the CSR data. The sensitivity analysis of coal properties to CRI was also performed using the developed kinetic model. The model was successfully applied for coal blending to predict CRI of the produced coke with standard error 3.7. This model can explain well the catalytic effect of coal and coal blend properties to coke reactivity during the CRI test.

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