|Table of Contents|

Discrete element simulation and process parameter optimization for continuous mixing uniformity of multi-component pavement materials(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2026年01期
Page:
199-210
Research Field:
汽车与机械工程
Publishing date:

Info

Title:
Discrete element simulation and process parameter optimization for continuous mixing uniformity of multi-component pavement materials
Author(s):
ZHANG Ze-yu1; 2; 3;  MU Shao-ping1;  HUI Ji-zhuang1*;  REN Yu1;  LIU Yong1; 4
(1. Engineering Research Center of Ministry of Education of Construction and Maintenance Equipment and Technology of Expressway, Chang'an University, Xi'an 710064, Shaanxi, China; 2. Key Laboratory of Road Construction Technology and Equipment of Ministry of Education, Chang'an University, Xi'an 710064,Shaanxi, China; 3. Research Center, Xizang Tianlu Co., Ltd., Lhasa 850000, Xizang, China; 4. Zhonghang Electronic Measuring Instruments(Xi'an)Co., Ltd., Xi'an 710064, Shaanxi, China)
Keywords:
mixing equipment;  multi-component pavement material;  mixing uniformity;  similarity theory;  dispersion coefficient
PACS:
U415.52
DOI:
10.19721/j.cnki.1671-8879.2026.01.015
Abstract:
To investigate the particle motion characteristics and the effects of operational parameters on the mixing uniformity of multi-component pavement materials in continuous mixing equipment, the semi-flexible pavement material was taken as an example, and a model of continuous mixing equipment was established based on similarity theory. The discrete element method(DEM)was used to simulate the distribution, motion trajectories and velocity characteristics of particles with different sizes inside the equipment. The dispersion coefficient was served as the evaluation index. The effects of mixing shaft rotational speed and particle feed rate on the mixing uniformity of particles at the discharge outlet were analyzed. The optimal combination of parameters was determined. The most significant influencing factor was identified through analysis of variance(ANOVA). The research results show that compared with the Hertz model, particles in the Hertz-Mindlin with JKR contact model are subjected to adhesive forces. They exhibit higher cohesion and lower dispersion. This condition is closer to the actual situation of concrete slump. Particles with the same size have the maximum aggregation at the feed inlet of the continuous mixing equipment. After mixing, they gradually distribute uniformly along the axis. The best mixing degree is achieved at the discharge outlet. The mixture shows aggregation in the middle region of the mixing equipment. A boiling effect is generated under the driving action of the mixing blades. Particle velocities are larger at the feed inlet and in the gap between the mixing shaft and the equipment inner wall. The velocity is smaller in the middle region along the mixing shaft. The average particle velocity fluctuates near 0.09 m/s around 8 s after the start of mixing work. At this time, the particles inside the mixing equipment are basically full. The mixing equipment enters a stable working state. Driven by the mixing blades, gaps exist between particles. This can increase the opportunity for particles to contact other types of particles during motion and promote mixing uniformity. The mixing uniformity continuously increases from the feed inlet to the discharge outlet. The best mixing uniformity is achieved when the particle feed rate is 164 t/h and the mixing shaft rotational speed is 160 r/min. The two-factor ANOVA shows that the effect of particle feed rate on the mixing uniformity is greater than that of the mixing shaft rotational speed.11 tabs, 13 figs, 30 refs.

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Last Update: 2026-02-20