椭球体
原子堆积因子
级配
介观物理学
骨料(复合)
蒙特卡罗方法
包装问题
粒子(生态学)
算法
数学优化
计算机科学
物理
数学
材料科学
复合材料
统计
人工智能
地质学
海洋学
量子力学
核磁共振
天文
作者
Changhong Chen,Songlin Bai,Ying Huang,L. Lam,Yao Yao,L. M. Keer
标识
DOI:10.1680/jmacr.20.00228
摘要
The random packing of aggregate particles is an important factor affecting the mechanical properties of concrete at the mesoscopic scale. In the current study, a meso-mechanical pretreatment algorithm is developed to construct the random ellipsoidal aggregate model for the mesoscopic structure of fully graded concrete. The Fuller curve combined with equivalent diameter is adopted to ensure equality between the gradation and content of the random ellipsoidal aggregates and those of the actual geometric aggregates. A ‘removing occupied space’ method is proposed to improve the packing efficiency based on the background grids strategy. A modified search algorithm consisting of rough and fine detection for determining the overlaps is proposed to improve the optimised simulation of the meso-structure of cement-based composites. A random ellipsoidal aggregate model with different aspect ratios of ellipsoid is developed and compared with the existing algorithms to test the efficiency of the new pretreatment algorithm. The effect of the ellipsoidal shape on the random packing fraction is investigated based on the proposed pretreatment algorithm. The pretreatment algorithm proposed greatly improves the efficiency of packing and provides a powerful tool for the realisation of three-dimensional large-scale numerical meso-concrete.
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