Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6631789 | Fuel | 2018 | 20 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Lauren North, Karen Blackmore, Keith Nesbitt, Merrick R. Mahoney,