3D random packing algorithm of ellipsoidal particles based on the Monte Carlo method

Chen, Changhong1; Bai, Songlin1; Huang, Ying2; Lam, Lik3; Yao, Yao2; Keer, Leon M.4

2021-04-01

10.1680/jmacr.20.00228

MAGAZINE OF CONCRETE RESEARCH   影响因子和分区

0024-9831

1751-763X

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.

aggregates composite materials finite element methods

SCI ; EI

英语

其他

National Natural Science Foundation of China[51408489,51248007,51308448,51301136,51508464] ; Shanxi National Science Foundation of China[2017JM5007] ; Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University[CX2020122] ; Fundamental Research Funds for the Central Universities[3102014JCQ01047]

Construction & Building Technology ; Materials Science

Construction & Building Technology ; Materials Science, Multidisciplinary

WOS:000623368200002

ICE PUBLISHING

20211010028180

Aggregates ; Aspect ratio ; Composite structures ; Concrete aggregates ; Efficiency ; Monte Carlo methods ; Superconducting materials

Highway Engineering:406 ; Structural Members and Shapes:408.2 ; Concrete:412 ; Superconducting Materials:708.3 ; Production Engineering:913.1 ; Mathematical Statistics:922.2

MATERIALS SCIENCE

Web of Science

1.Northwestern Polytech Univ, Sch Mech & Civil Engn, Xian, Peoples R China
2.Xian Univ Architecture & Technol, Sch Civil Engn, Xian, Peoples R China
3.Southern Univ Sci & Technol, Dept Ocean Sci & Engn, Shenzhen, Peoples R China
4.Northwestern Univ, Civil & Environm Engn, Evanston, IL USA

Chen, Changhong,Bai, Songlin,Huang, Ying,et al. 3D random packing algorithm of ellipsoidal particles based on the Monte Carlo method[J]. MAGAZINE OF CONCRETE RESEARCH,2021,73(7):343-355.

Chen, Changhong,Bai, Songlin,Huang, Ying,Lam, Lik,Yao, Yao,&Keer, Leon M..(2021).3D random packing algorithm of ellipsoidal particles based on the Monte Carlo method.MAGAZINE OF CONCRETE RESEARCH,73(7),343-355.

Chen, Changhong,et al."3D random packing algorithm of ellipsoidal particles based on the Monte Carlo method".MAGAZINE OF CONCRETE RESEARCH 73.7(2021):343-355.