A Predictive Model for the Anisotropy Index of Semi-Coke Derived from the Properties of Colombia's Eastern Cordillera Coals

Main Article Content

Eliana Romero-Salcedo https://orcid.org/0000-0001-5369-3566
Sandra Manosalva-Sánchez https://orcid.org/0000-0001-9879-0933
Wilson Naranjo-Merchán https://orcid.org/0000-0002-9123-0308
Oscar García-Cabrejo https://orcid.org/0000-0002-7396-8915
Mauricio A Bermúdez https://orcid.org/0000-0003-0584-4790
Juan Gómez-Neita https://orcid.org/0000-0001-9967-7123


Coal, coke anisotropy quotient, semi-coke, principal component analysis, textural component, Colombia Eastern Cordillera


This study developed a theoretical model for the determination of the Coke Anisotropy Quotient (CAQ) of semi-coke from the properties of its precursor coal. This is an useful parameter to define the resistance and reactivity of semi-coke in the blast furnace. For 36 semi-coke samples, a textural analysis was performed alongside a fluidity test to determine the real CAQ. The main textures observed were: isotropic and circular for high volatile bituminous coals (HVB); lenticular and fine ribbons for the medium volatile bituminous coals (MVB); and medium and thick ribbons for the low volatile bituminous coals (LVB). The CAQ varied in a range from 1 to 11. A principal component analysis (PCA) and multiple regression allowed to discriminated the importance of certain coal properties, in determining the CAQ to be recognized and to estimate parameters of the mathematical model. The statistical analysis suggested that CAQ can be best predicted from the fluidity, volatile matter, and Ro of the parent coals. The veracity of this model result was then tested using a second dataset from Poland. This work optimizes the usefulness of standard datasets in the prediction of CAQ's offering a means of quality control that could be implemented in Colombian coke production.


Download data is not yet available.
Abstract 301 | PDF Downloads 32


[1] R. Gray, Chapter 9 - Coal to Coke Conversion, H. Marsh, I. A. Edwards, R. Menendez, B. Rand, S. West, A. J. Hosty, K. Kuo, A. McEnaney, T. Mays, D. J. Johnson, J. W. Patrick, D. E. Clarke, J. C. Crelling, and R. J. Gray, Eds. Butterworth-Heinemann, 1989. https://doi.org/10.1016/B978-0-408-03837-9.50014-2

[2] B. Kwiecińska and H. Petersen, “Graphite, semi-graphite, natural coke, and natural char classification–iccp system,” International Journal of Coal Geology, vol. 57, no. 2, pp. 99 – 116, 2004. https://doi.org/10.1016/j.coal.2003.09.003

[3] N. Choudhury, D. Mohanty, P. Boral, S. Kumar, and S. K. Hazra, “Microscopic evaluation of coal and coke for metallurgical usage,” Current Science, vol. 94, no. 1, pp. 74–81, 2008. http://www.jstor.org/stable/ 24102031

[4] I. Suárez-Ruiz and C. R. Ward, Chapter 2 - Basic Factors Controlling Coal Quality and Technological Behavior of Coal, I. Su’arez-Ruiz and J. C. Crelling, Eds. Burlington: Elsevier, 2008. https://doi.org/10.1016/B978-0-08-045051-3.00002-6

[5] T. Larry, Coal Geology. John Wiley and Sons Ltd, England, 2002.

[6] V. Gulyaev, V. Barskii, and A. Rudnitskii, “European quality requirements on blast-furnace coke,” Coke and Chemistry, vol. 55, no. 10, pp. 372–376, 2012. https://doi.org/10.3103/S1068364X12100043

[7] M. Dıez, R. Alvarez, and C. Barriocanal, “Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking,” International Journal of Coal Geology, vol. 50, no. 1-4, pp. 389–412, 2002. https://doi.org/10.1016/S0166-5162(02)00123-4

[8] J. W. Patrick, M. J. Reynolds, and F. H. Shaw, “Development of optical anisotropy in vitrains during carbonization,” Fuel, vol. 52, no. 3, pp. 198–204, 1973. https://doi.org/10.1016/0016-2361(73)90079-3

[9] A. Moreland, J. W. Patrick, and A. Walker, “Optical anisotropy in cokes from high-rank coals,” Fuel, vol. 67, no. 5, pp. 730–732, 1988. https://doi.org/10.1016/0016-2361(88)90307-9

[10] A. Varma, “Influence of petrographical composition on coking behavior of inertinite-rich coals,” International journal of coal geology, vol. 30, no. 4, pp. 337–347, 1996. https://doi.org/10.1016/0166-5162(95)00053-4

[11] S. Pusz, B. Kwiecińska, A. Koszorek, M. Krzesińska, and B. Pilawa, “Relationships between the optical reflectance of coal blends and the microscopic characteristics of their cokes,” International Journal of Coal Geology, vol. 77, no. 3-4, pp. 356–362, 2009. https://doi.org/10.1016/j.coal. 2008.06.003

[12] K. Hiraki, H. Hayashizaki, Y. Yamazaki, T. Kanai, X. Zhang, M. Shoji, H. Aoki, T. Miura, and K. Fukuda, “The effect of changes in microscopic structures on coke strength in carbonization process,” ISIJ international, vol. 51, no. 4, pp. 538–543, 2011. https://doi.org/10.2355/isijinternational.51.538

[13] M. Piechaczek, A. Mianowski, and A. Sobolewski, “The original concept of description of the coke optical texture,” International journal of coal geology, vol. 139, pp. 184–190, 2015. https://doi.org/10.1016/j.coal.2014.07.002

[14] L. North, K. Blackmore, K. Nesbitt, and M. R. Mahoney, “Models of coke quality prediction and the relationships to input variables: a review,” Fuel, vol. 219, pp. 446–466, 2018. https://doi.org/10.1016/j.fuel.2018.01.062

[15] C. F. Diessel and E. Wolff-Fischer, “Coal and coke petrographic investigations into the fusibility of carboniferous and permian coking coals,” International journal of coal geology, vol. 9, no. 1, pp. 87–108, 1987. https://doi.org/10.1016/0166-5162(87)90066-8

[16] R. Sharma, P. Dash, P. Banerjee, and D. Kumar, “Effect of coke micro-textural and coal petrographic properties on coke strength characteristics,” ISIJ international, vol. 45, no. 12, pp. 1820–1827, 2005. https://doi.org/10.2355/isijinternational.45.1820

[17] J. C. Hower and W. G. Lloyd, “Petrographic observations of gieseler semi-cokes from high volatile bituminous coals,” Fuel, vol. 78, no. 4, pp. 445–451, 1999. https://doi.org/10.1016/S0016-2361(98)00170-7

[18] A. Guerrero, M. A. Diez, and A. G. Borrego, “Influence of charcoal fines on the thermoplastic properties of coking coals and the optical properties of the semicoke,” International Journal of Coal Geology, vol. 147, pp. 105–114, 2015. https://doi.org/10.1016/j.coal.2015.06.013

[19] A. G. Borrego and M. A. Diez, Petrografía del Coque metalúrgico. Incar, Ed. Oviedo, 2014.

[20] V. J. B. Bitencourt and S. R. Dillenburg, “Application of multivariate statistical techniques in alongshore differentiation of coastal barriers,” Marine Geology, vol. 419, p. 106077, 2020. https://doi.org/10.1016/j.margeo.2019.106077

[21] J. Davis, Statistics and Data Analysis in Geology, John Wiley and Sons, New York, 656, 2002.

[22] R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, 2017. https://www.R-project.org/

[23] S. Padoan, A. Zappi, T. Adam, D. Melucci, A. Gambaro, G. Formenton, O. Popovicheva, D.-L. Nguyen, J. Schnelle-Kreis, and R. Zimmermann, “Organic molecular markers and source contributions in a polluted municipality of north-east italy: Extended pca-pmf statistical approach,” Environmental Research, p. 109587, 2020. https://doi.org/10.1016/j.envres.2020.109587

[24] M. Mrówczyńska, J. Sztubecki, and A. Greinert, “Compression of results of geodetic displacement measurements using the pca method and neural networks,” Measurement, vol. 158, pp. 1–12, 2020. https://doi.org/10.1016/j.measurement.2020.107693

[25] S. Makvandi, G. Beaudoin, M. Beth McClenaghan, D. Quirt, and P. Ledru, “Pca of fe-oxides mla data as an advanced tool in provenance discrimination and indicator mineral exploration: Case study from bedrock and till from the kiggavik u deposits area (nunavut, canada),” Journal of Geochemical Exploration, vol. 197, pp. 199 – 211, 2019. https://doi.org/10.1016/j.gexplo.2018.11.013

[26] M. Kutner, J. Neter, C. Nachtsheim, and W. Wasserman, Applied Linear Statistical Model Richard D, 2004.

[27] C. L. Guatame and G. Sarmiento, “Interpretación del ambiente sedimentario de los carbones de la formación guaduas en el sinclinal checua-lenguazaque a partir del análisis petrográfico,” Geología Colombiana, vol. 29, pp. 41–57, 2004.

[28] L. J. M. Umaña, C. E. C. Gómez, and J. F. G. Casallas, “Análisis de microlitotipos en los carbones de la formación guaduas en el sinclinal de sueva, cundinamarca,” Geología Colombiana, vol. 31, pp. 11–26, 2006.

[29] J. S. Gómez-Neita, M. D. López-Carrasquilla, S. R. Manosalva-Sánchez, and W. E. Naranjo-Merchán, “Aportes a la determinación de paleoambientes, carbones del sinclinal checua-lenguazaque. colombia,” Ingeniería Investigación y Desarrollo, vol. 16, no. 2, pp. 32–42, 2016. https://doi.org/10.19053/1900771X.v16.n2.2016.5444

[30] J. S. Gómez-Neita, M. Costa-Pompeu, S. R. Manosalva-Sánchez, A. A. Evangelista-Nogueira, W. E. Naranjo-Merchán, and A. Matos de Lima, “Organic petrography of cretaceous coals in Colombia, Sutatausa-cucunuba region,” Bomgeam, vol. 3, 2019. http://doi.org/10.31419/ISSN.2594-942X. v62019i3a2JSGN

[31] O. P. Gómez Rojas, A. Blandón, C. Perea, and M. Mastalerz, “Petrographic characterization, variations in chemistry, and paleoenvironmental interpretation of colombian coals,” International Journal of Coal Geology, p. 103516, 2020. https://doi.org/10.1016/j.coal.2020.103516

[32] E. Díaz-Faes, C. Barriocanal, M. Diez, and R. Alvarez, “Applying tga parameters in coke quality prediction models,” Journal of analytical and applied pyrolysis, vol. 79, no. 1-2, pp. 154–160, 2007. https://doi.org/10.1016/j.jaap.2006.11.001

[33] Ł. Smędowski and M. Piechaczek, “Impact of weathering on coal properties and evolution of coke quality described by optical and mechanical parameters,” International Journal of Coal Geology, vol. 168, pp. 119–130, 2016. https://doi.org/10.1016/j.coal.2016.08.005

[34] X. Guo, Y. Tang, C. F. Eble, Y. Wang, and P. Li, “Study on petrographic characteristics of devolatilization char/coke related to coal rank and coal maceral,” International Journal of Coal Geology, p. 103504, 2020. https://doi.org/10.1016/j.coal.2020.103504

[35] Y. Yuan, Q. Qu, L. Chen, and M. Wu, “Modeling and optimization of coal blending and coking costs using coal petrography,” Information Sciences, vol. 522, pp. 49 – 68, 2020. https://doi.org/10.1016/j.ins.2020.02.072

[36] B. D. Flores, A. G. Borrego, M. A. Diez, G. L. da Silva, V. Zymla, A. C. Vilela, and E. Osório, “How coke optical texture became a relevant tool for understanding coal blending and coke quality,” Fuel Processing Technology, vol. 164, pp. 13–23, 2017. https://doi.org/10.1016/j.fuproc.2017.04.015

[37] S. Chehreh Chelgani, S. Matin, and J. C. Hower, “Explaining relationships between coke quality index and coal properties by random forest method,” Fuel, vol. 182, pp. 754 – 760, 2016. https://doi.org/10.1016/j.fuel.2016.06.034

[38] R. Morga, I. Jelonek, K. Kruszewska, and W. Szulik, “Relationships between quality of coals, resulting cokes, and micro-raman spectral characteristics of these cokes,” International Journal of Coal Geology, vol. 144-145, pp. 130 – 137, 2015. https://doi.org/10.1016/j.coal.2015.04.006

[39] R. J. Gray, “Some petrographic applications to coal, coke and carbons,” Organic Geochemistry, vol. 17, no. 4, pp. 535 – 555, 1991. https://doi.org/10.1016/0146-6380(91)90117-3

[40] T. Gentzis and P. Rahimi, “A microscopic approach to determine the origin and mechanism of coke formation in fractionation towers☆,” Fuel, vol. 82, no. 12, pp. 1531 – 1540, 2003. https://doi.org/10.1016/S0016-2361(03) 00032-2

[41] C. Barriocanal, S. Hanson, J. W. Patrick, and A. Walker, “The characterization of interfaces between textural components in metallurgical cokes,” Fuel, vol. 73, no. 12, pp. 1842 – 1847, 1994. https://doi.org/10.1016/0016-2361(94)90209-7

[42] M. Lundgren, L. Sundqvist Ökvist, and B. Björkman, “Coke reactivity under blast furnace conditions and in the csr/cri test,” steel research international, vol. 80, no. 6, pp. 396–401, 2009. https://onlinelibrary.wiley. com/doi/abs/10.1002/srin.201090020

[43] D. Vogt and M. Depoux, “Coke reactivity prediction by texture analysis,” Fuel Processing Technology, vol. 24, pp. 99 – 105, 1990, coal Characterisation for Conversion Processes II. https://doi.org/10.1016/0378-3820(90)90046-U