A novel analytical model of particle size distributions in granular materials

被引:0
|
作者
Yang, Lifu [1 ,2 ,3 ]
Troemner, Matthew [4 ]
Cusatis, Gianluca [5 ]
Su, Huaizhi [1 ,2 ]
机构
[1] Hohai Univ, Natl Key Lab Water Disaster Prevent, Nanjing 210098, Peoples R China
[2] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Nanjing 210098, Peoples R China
[3] Hunan Univ, Coll Civil Engn, Changsha 410082, Peoples R China
[4] North Fracture Grp, Houghton, MI USA
[5] Northwestern Univ, Dept Civil & Environm Engn, Evanston, IL 60208 USA
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Particle size distribution; Particle generation; Piecewise linear sieve curve; Probability density function; Fuller curve; FRACTURE; AGGREGATE; TOMOGRAPHY; POROSITY;
D O I
10.1007/s00366-024-02042-7
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The analysis of particle size distributions is important to better understand the relation between the microstructure and the heterogenous physical behavior of granular materials, including soils, sands, and concrete. This paper presents a novel analytical model, entitled piecewise linear sieve curve, to accurately reproduce the complicated and wide-ranging particle size distribution of granular materials. The model assumes that the passing percentage varies linearly with aggregate size between two adjacent sieves. The probability density function and cumulative distribution function of the piecewise linear sieve curve can be determined directly once the experimental particle gradation is known. Several types of concrete with different mix designs were taken as numerical examples, and the particle modeling based on piecewise linear sieve curve and the classical Fuller curve were compared. The results show that the piecewise linear sieve curve provides a much better representation of different aggregate particle size distributions than the Fuller curve, and the proposed model achieves the goal to reproduce the experimental aggregate gradation in an efficient and accurate way.
引用
收藏
页数:21
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