| Summary: | 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.
TGA experiments reveal the thermal decomposition characteristics of coke, with correlations to CRI validating thermal analysis as a predictive tool despite discrepancies due to pre-combusted samples and inter-laboratory variations.
Introducing VRA, the thesis analyses shape changes of coke samples under controlled atmospheres, showing the impact of oxidising and reducing conditions on coke reactivity. The VRA data provides a detailed temporal profile of the combustion process. The thesis addresses methodological limitations and proposes future research, including integrating VRA with isothermal programmes and combining VRA and TGA analysis for comprehensive coke characterisation.
This work lays the foundation for enhanced predictive models of coke performance, offering valuable tools for optimising fuel efficiency and reducing emissions in the steel and metallurgical industries.
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