Computers and Concrete

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Two-dimensional concrete meso-modeling research based on pixel matrix and skeleton theory

  • Jingwei Ying (College of Civil Engineering and Architecture, Guangxi University) ;
  • Yujun Jian (College of Civil Engineering and Architecture, Guangxi University) ;
  • Jianzhuang Xiao (Institute of Science and Technology for Carbon Peak & Neutrality, Guangxi University)
  • Received : 2022.07.05
  • Accepted : 2023.11.06
  • Published : 2024.06.25
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Abstract

The modeling efficiency of concrete meso-models close to real concrete is one of the important issues that limit the accuracy of mechanical simulation. In order to improve the modeling efficiency and the closeness of the numerical aggregate shape to the real aggregate, this paper proposes a method for generating a two-dimensional concrete meso-model based on pixel matrix and skeleton theory. First, initial concrete model (a container for placing aggregate) is generated using pixel matrix. Then, the skeleton curve of the residual space that is the model after excluding the existing aggregate is obtained using a thinning algorithm. Finally, the final model is obtained by placing the aggregate according to the curve branching points. Compared with the traditional Monte Carlo placement method, the proposed method greatly reduces the number of overlaps between aggregates by up to 95%, and the placement efficiency does not significantly decrease with increasing aggregate content. The model developed is close to the actual concrete experiments in terms of aggregate gradation, aspect ratio, asymmetry, concavity and convexity, and old-new mortar ratio, cracking form, and stress-strain curve. In addition, the cracking loss process of concrete under uniaxial compression was explained at the mesoscale.

Keywords

Acknowledgement

The research described in this paper was financially supported by the Natural Science Foundation of China (Grant No. 52168015, No. 51768005), Natural Science Foundation of Guangxi (Grant No. 2018GXNSFAA281333), Interdisciplinary Scientific Research Foundation of Guangxi University (Grant No. 202200227).

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