Establishing a 3D aggregates database from X-ray CT scans of bulk concrete

A computational sequence to extract individual 3D aggregate from computed tomography (CT) scans of bulk concrete is presented in this paper. The technique adopted a combination of computer vision algorithms customized for concrete composite along with the originally proposed algorithm. The computational technique efficiently establishes a database of 1442 aggregates with individual 3D printable volume and surface. The presented work can be used to perform heterogeneous modelling with realistic aggregates input and distributive analysis of a specific constituent of interest. The necessity of customizing the computer vision in the application of concrete composite is discussed with evidenced digital damage in the non-destructive measurement. A comparison with available reconstruction methods with feasibility is performed to demonstrate that characterizing concrete composite with detailed information of each constituent can provide a more realistic representation of the composite. The vision of digital concrete with realistic aggregates input is further demonstrated with the example application.

Automated summary

This study proposes a computational sequence to extract individual 3D concrete aggregates from computed tomography scans, establishing a database of 1442 aggregates with detailed information. Comparisons with existing reconstruction methods demonstrate that characterizing concrete composite with detailed information of each constituent can provide a more realistic representation of the composite. The vision of digital concrete with realistic aggregates input is further demonstrated through an example application.