Extracting three-dimensional Cellular Automaton for cement microstructure development using Gene Expression Programming

A three-dimensional CA model for the simulation of Portland cement microstructure development has been developed in this paper. The Gene Expression Programming (GEP) algorithm is employed as the learning algorithm to evolve the transition rule reversely from the microstructure development characteristic data due to hydration reactions. The characteristic data is extracted from 8-bit gray images that based on the processing of real cement acquired by Micro Computed Tomography (micro-CT) technology. Starting with initial micro-CT image, cement microstructure evolution images of 28 days is constructed through CA rule discovered by GEP. The experimental results show that this model with the CA rule designed by GEP has higher agreement between the model predictions and experimental measurements for degree of hydration than other models. Furthermore, this model still has good generalization ability when changing the water-cement ratio and chemical composition.