Evaluation of component interface quality in 3D micro-CT images of metallurgical coke

Metallurgical coke is a crucial component in the production of steel worldwide. It is a porous composite material, created by conversion of metallurgical coal in a coke oven. A key property of metallurgical coke is its strength, and there is evidence that poor interface quality between the two key components of coke can have deleterious effect on coke strength. Here we create small samples of coke and image them using high resolution 3D micro-CT, with pixel size of approximately \(8\,\mu\)m. We use a Gabor filter, combined with morphology techniques to isolate the different components in the samples. We then develop a measure, called excess porosity to quantify the quality of the interfaces between components. This measure enables us to highlight problem interactions between components. References R. Barranco, J. Patrick, C. Snape, and A. Thompson. Impact of low-cost filler material on coke quality. Fuel 86.14 (2007), pp. 2179–2185. doi: 10.1016/j.fuel.2007.03.013 C. Barriocanal, S. Hanson, J. W. Patrick, and A. Walker. Reactive-inert interfaces in metallurgical cokes: Effect of added inerts. Fuel 75.2 (1996), pp. 243–245. doi: 10.1016/0016-2361(95)00233-2 C. Barriocanal, S. Hanson, J. W. Patrick, and A. Walker. The characterization of interfaces between textural components in metallurgical cokes. Fuel 73.12 (1994), pp. 1842–1847. doi: 10.1016/0016-2361(94)90209-7 C. Barriocanal, S. Hanson, J. W. Patrick, and A. Walker. The quality of interfaces in metallurgical cokes containing petroleum coke. Fuel Proces. Tech. 45 (1995), pp. 1–10. doi: 10.1016/0378-3820(95)00003-P P. Bennett, F. Shi, and N. Andriopoulos. Determination of a theoretically based coke strength index or indices based on drum tests. ACARP Project C20009 (2013). url: https://www.acarp.com.au/abstracts.aspx?repId=C20009 M. Haghighat, S. Zonouz, and M. Abdel-Mottaleb. CloudID: Trustworthy cloud-based and cross-enterprise biometric identification. Expert Sys. Appl. 42 (2015), pp. 7905–7916. doi: 10.1016/j.eswa.2015.06.025 T. Kanai, Y. Yamazaki, X. Zhang, A. Uchida, Y. Saito, M. Shoji, H. Aoki, S. Nomura, Y. Kubota, H. Hayashizaki, and S. Miyashita. Quantification of the existence ratio of non-adhesion grain boundaries and factors governing the strength of coke containing low-quality coal. J. Therm. Sci. Tech. 7.2 (2012), pp. 351–363. doi: 10.1299/jtst.7.351 Y. Kubota, S. Nomura, T. Arima, and K. Kato. Effects of coal inertinite size on coke strength. ISIJ Int. 48.5 (2008), pp. 563–571. doi: 10.2355/isijinternational.48.563 R. Li, D. R. Jenkins, and R. Pearce. Texture-based identification of inert-maceral derived components in metallurgical coke. MODSIM (2015). url: https://www.mssanz.org.au/modsim2015/A1/li_r.pdf H. Lomas, D. R. Jenkins, M. R. Mahoney, R. Pearce, R. Roest, K. Steel, and S. Mayo. Examining mechanisms of metallurgical coke fracture using micro-CT imaging and analysis. Fuel Proc. Tech. 155 (2017), pp. 183–190. doi: 10.1016/j.fuproc.2016.05.039 N. Otsu. A threshold selection method from gray-level histograms. IEEE Trans. Sys. Man. Cyber 9 (1979), pp. 62–66. doi: 10.1109/TSMC.1979.4310076 R. Roest, H. Lomas, S. Gupta, R. Kanniala, and M. R. Mahoney. Fractographic approach to metallurgical coke failure analysis. Part 3: Characterisation of fracture mechanisms in a blast furnace coke. Fuel 180 (2016), pp. 803–812. doi: 10.1016/j.fuel.2016.04.019 Y. Saito, T. Kanai, D. Igawa, Y. Miyamoto, S. Matsuo, Y. Matsushita, H. Aoki, S. Nomura, H. Hayashizaki, and S. Miyashita. Image recognition method for defect on coke with low-quality coal. ISIJ Int. 54.11 (2014), pp. 2512–2518. doi: 10.2355/isijinternational.54.2512