Performance prediction of metallurgical coke using image analysis - Goonetilleke-Rezel, Teshan (2024)
This thesis investigates the thermal behaviour and petrographic characteristics of coke, employing manual point counting (MPC), advanced image analysis (IA), visual reactivity analysis (VRA), and thermogravimetric analysis (TGA) to establish correlations with the Coke Reactivity Index (CRI). The study demonstrates that automated thresholding of petrographic mosaics can effectively predict coke reflectance and CRI, with a reflectance quotient offering insights into anisotropic and dark texture contributions to coke reactivity.