Čapek, P., Hejtmánek, V., Brabec, L. et al. Transp Porous Med (2009) 76: 179. doi:10.1007/s11242-008-9242-8
In this contribution the issue of the stochastic reconstruction of particulate media from 2D backscatter SEM images is addressed with particular reference to pore space connectivity. The reconstruction of porous bodies in 2D or 3D space was achieved by using a simulated annealing technique. Two constraints were found to be necessary for the successful reconstruction of well connected pore space: the two-point probability function, and the lineal-path function for the solid phase. Surprisingly, the most commonly used method of reconstruction (common method), consisting of a similar application of both the two-point probability function and the lineal-path function for the void phase, resulted in microstructures characterized by poor pore space connectivity, and by artificial patterns. Since it is desirable to employ the maximum possible number of microstructural descriptors (i.e. to use the lineal-path function for the void phase), we propose a new method of reconstruction. The influence of the lineal-path function for the void phase was suppressed during the initial stages of 2D reconstruction, thereby creating the possibility of obtaining microstructures whose two-point cluster functions match the experimentally measured functions. The effect of the lineal-path function for the void phase on the course of the reconstruction was adjusted by modifying two parameters of the reconstruction procedure. It was tacitly assumed that the parameters adjusted during 2D reconstruction had the same influence on the formation of 3D microstructures. Therefore, the experimental two-point cluster function, extracted from the 2D images, was only used indirectly during 3D reconstruction. 3D replicas obtained using our new method exhibited significantly better pore space connectivity and were more penetrable than porous bodies reconstructed using the common method.
Stochastic reconstruction Simulated annealing Two-point cluster function Connectivity