Methods of coke quality prediction: a review

Title: Methods of coke quality prediction: a review
Creator: North, Lauren; Blackmore, Karen; Nesbitt, Keith; Mahoney, Merrick R.
Relation: Fuel Vol. 219, Issue 1 May 2018, p. 426-445
Publisher Link: http://dx.doi.org/10.1016/j.fuel.2018.01.090
Publisher: Elsevier
Resource Type: journal article
Date: 2018
Description: The prediction of coke quality from global coal basins is critical to coke producers and steel makers for both the selection and effective utilisation of coals. This review analysed the methods described within published models for the prediction of coke quality. Of particular focus were methods that sought to predict coke strength after reaction (CSR) and the related coke reactivity index (CRI). Using the cross industry standard process for data mining (CRISP-DM) as an analysis framework, the models were compared in terms of their data treatment and use of analytical techniques. On reviewing these papers, our results indicate that it is difficult to apply models beyond the conditions under which they were derived, and that many models do not report enough detail to allow complete replication.
Subject: coking coal; cokemaking; coke quality; prediction
Identifier: http://hdl.handle.net/1959.13/1462773
Identifier: uon:46552
Identifier: ISSN:0016-2361
Language: eng
Reviewed

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