https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52083 A vital input for steel manufacture is a coal-derived solid fuel called coke. Digital reconstructions and simulations of coke are valuable tools to analyse and test coke properties. We implement biased voxel iteration into a simulated annealing method via a kernel convolution to reduce the number of iterations required to generate a digital coke microstructure. We demonstrate that voxel connectivity assumptions impact the number of iterations and reduce the normalised computation time required to generate a digital microstructure by as much as 70%. References L. De Floriani, U. Fugacci, and F. Iuricich. Homological shape analysis through discrete morse theory. Perspectives in Shape Analysis. Ed. by M. Breuss, A. Bruckstein, P. Maragos, and S. Wuhrer. Springer, 2016, pp. 187–209. doi: 10.1007/978-3-319-24726-7_9 M. A. Diez, R. Alvarez, and C. Barriocanal. Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking. Int. J. Coal Geol. 50.1–4 (2002), pp. 389–412. doi: 10.1016/S0166-5162(02)00123-4 D. T. Fullwood, S. R. Kalidindi, S. R. Niezgoda, A. Fast, and N. Hampson. Gradient-based microstructure reconstructions from distributions using fast Fourier transforms. Mat. Sci. Eng. A 494.1–2 (2008), pp. 68–72. doi: 10.1016/j.msea.2007.10.087 E.-Y. Guo, N. Chawla, T. Jing, S. Torquato, and Y. Jiao. Accurate modeling and reconstruction of three-dimensional percolating filamentary microstructures from two-dimensional micrographs via dilation-erosion method. Mat. Character. 89 (2014), pp. 33–42. doi: 10.1016/j.matchar.2013.12.011 Y. Jiao, F. H. Stillinger, and S. Torquato. Modeling heterogeneous materials via two-point correlation functions: Basic principles. Phys. Rev. E 76.3, 031110 (2007). doi: 10.1103/PhysRevE.76.031110 H. Kumar, C. L. Briant, and W. A. Curtin. Using microstructure reconstruction to model mechanical behavior in complex microstructures. Mech. Mat. 38.8–10 (2006), pp. 818–832. doi: 10.1016/j.mechmat.2005.06.030 Z. Ma and S. Torquato. Generation and structural characterization of Debye random media. Phys. Rev. E 102.4, 043310 (2020). doi: 10.1103/PhysRevE.102.043310 F. Meng, S. Gupta, D. French, P. Koshy, C. Sorrell, and Y. Shen. Characterization of microstructure and strength of coke particles and their dependence on coal properties. Powder Tech. 320 (2017), pp. 249–256. doi: 10.1016/j.powtec.2017.07.046 M. G. Rozman and M. Utz. Uniqueness of reconstruction of multiphase morphologies from two-point correlation functions. Phys. Rev. Lett. 89.13, 135501 (2002). doi: 10.1103/PhysRevLett.89.135501 T. Tang, Q. Teng, X. He, and D. Luo. A pixel selection rule based on the number of different-phase neighbours for the simulated annealing reconstruction of sandstone microstructure. J. Microscopy 234.3 (2009), pp. 262–268. doi: 10.1111/j.1365-2818.2009.03173.x S. Torquato. Microstructure characterization and bulk properties of disordered two-phase media. J. Stat. Phys. 45.5 (1986), pp. 843–873. doi: 10.1007/BF01020577 S. Torquato and H. W. Haslach Jr. Random heterogeneous materials: microstructure and macroscopic properties. Appl. Mech. Rev. 55.4 (2002), B62–B63. doi: 10.1115/1.1483342 S. Torquato and C. L. Y. Yeong. Reconstructing random media.II: three-dimensional media from two-dimensional cuts. Phys. Rev. E 58.1 (1998), pp. 224–233. doi: 10.1103/PhysRevE.58.224 on p. C128). C. L. Y. Yeong and S. Torquato. Reconstructing random media. Phys. Rev. E 57.1, 495 (1998). doi: 10.1103/PhysRevE.57.495 ]]> Thu 28 Sep 2023 14:21:37 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:55682 Mon 17 Jun 2024 10:20:10 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53144 Fri 17 Nov 2023 12:03:23 AEDT ]]>