Wang Binhui, Song Xiaogang, Weng Chunying, Yan Xiaodong, Zhang Zihua
Department of Civil Engineering, Ningbo University, Ningbo 315211, China.
Digital Business School, Zhejiang Business Technology Institute, Ningbo 315012, China.
Materials (Basel). 2024 Sep 10;17(18):4440. doi: 10.3390/ma17184440.
The modeling of the concrete matrix serves as a foundation for mesoscale analysis of concrete, which provides a crucial avenue for investigating the crack propagation and strength characteristics of concrete. However, the primary prerequisite for conducting such analyses is the generation of aggregate models. By combining the advantages of Voronoi diagrams and the random walk algorithm (RWA), a Voronoi-random walk algorithm is proposed in this paper. The algorithm overcomes the limitations of traditional methods, including constraints on aggregate volume fraction, low computational efficiency, and insufficient randomness in aggregate distribution. The meso-structure of a concrete block was modeled by the proposed method, and then its failure behavior under uniaxial compression was simulated using the finite element method. The numerical results agreed well with the experimental observations, indicating the effectiveness and accuracy of the proposed approach.
混凝土基体的建模是混凝土细观尺度分析的基础，为研究混凝土的裂缝扩展和强度特性提供了关键途径。然而，进行此类分析的首要前提是生成骨料模型。本文结合Voronoi图和随机游走算法（RWA）的优点，提出了一种Voronoi随机游走算法。该算法克服了传统方法的局限性，包括对骨料体积分数的限制、计算效率低以及骨料分布随机性不足等问题。采用该方法对混凝土块体的细观结构进行了建模，然后利用有限元方法模拟了其单轴压缩下的破坏行为。数值结果与试验观测结果吻合良好，表明了该方法的有效性和准确性。
