Models of coke quality prediction and the relationships to input variables: A review. (1st May 2018)

• Record Type: Journal Article
• Authors: North, Lauren; Blackmore, Karen; Nesbitt, Keith; Mahoney, Merrick R.
• Is Part Of: Fuel. Volume 219(2018)
• Page Start: 446
• Page End: 466
• Publication Date: 2018-05-01
• Subjects: Coking coal -- Cokemaking -- Coke quality -- Prediction -- Strength -- Reactivity; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2018.01.062
• Languages: English
• ISSNs: 0016-2361

Abstract

Highlights: Coke quality prediction models are reviewed. Most models rely on rank, and/or ash chemistry, and/or thermoplastic properties. The influence of coal properties on coke quality is inconsistent between models. Models are limited in their prediction to the coal(s) for which they were derived. Abstract: Within the coke making industry, the ability to accurately predict the quality of the coke produced from a variety of global coal basins is critical in both coal selection and blast furnace control. However, due to the complexity of the coke making process, the prediction of the resulting coke properties is a difficult task. This review analysed published models for the prediction of various measures of coke quality, with a particular emphasis on coke strength after reaction (CSR) and the related coke reactivity index (CRI). Focus was placed on the coal parameters selected as model inputs, and their reported behaviour with respect to the predicted coke quality. This review draws similar conclusions to previous analysis, namely there is a limited range of model applicability beyond the specific range of coals for which each model was derived. This conclusion is extended to suggest that the inconsistent utilisation of key attributes contributes to these limitations.