Porous concrete has a high void ratio with continuously interconnected void clusters. The void distribution in concrete strongly affects its physical properties, such as strength and percolation. To investigate and quantify the spatial distribution of voids inside porous concrete specimens, computed tomography (CT) images and low-order probability functions can be used. In this study, we reconstruct porous concrete specimens with different void distributions using low-order probability functions. The void distributions of the original and reconstructed porous concrete specimens should exhibit almost the same statistical characteristics. We confirm that reconstructed porous concrete specimens generated using the proposed probabilistic optimization process have statistically identical characteristics, and exhibit similar material behaviors as with the original model. These reconstructed specimens can be utilized for numerical experiments so as to reduce the number of time-consuming real experiments.
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Building and Construction
- Materials Science(all)