Relationship Between CSR/CRI and Coal Properties via Principal Component Analysis Approach

Using mathematical models to predict CSR/CRI for aiding in the selection of coals for formulating suitable blends is a common practice in the cokemaking industry. These models are usually developed using a limited set of data and validity of the predicted results becomes questionable when applying to coals from different origins and formations. In this work, a dataset containing 279 samples was used to develop a CSR/CRI prediction model using Principle Component Analysis modelling technique. Measured CSR/CRI was correlated with a total of 35 coal properties. It was concluded that coal ash chemistry and rheological properties were the most influential factors on CSR/CRI. It was also identified that the lack of coal ash mineralogical composition and poor repeatability of CSR/CRI measurement limit the accuracy and applicability of the model.