Optimization of mixing chamber parameters of pavement recycling machine under engineered particle model analysis

• Published in: Journal of the Chinese Institute of Engineers Vol. 45; no. 6; pp. 521 - 531
• Main Authors: Cheng, Haiying, Fan, Kangkang, Feng, Shiming, Seliverstov, N.D, Makarova, D.A
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 18.08.2022
• Subjects: discrete element method; engineered particles; multi-parameter optimization; particle swarm optimization; Pavement recycling machine
• ISSN: 0253-3839; 2158-7299
• DOI: 10.1080/02533839.2022.2078419

The structural parameters of the mixing chamber of a pavement recycling machine affect the mixing behavior of an asphalt mixture. Most of the existing studies have used spherical particle models to analyze the mixing behavior, and it is difficult to truly understand the mechanical properties of asphalt mixtures in the mixing chamber. In this study, the discrete element similarity theory and dimensional analysis method were used to establish an engineered asphalt mixture particle model, and the validity of the model was verified by conducting a slump test. Based on these test results, the discrete element method was used to analyze the mixing behavior of the asphalt mixture, and the effect of the structural parameters of the mixing chamber on the mixing time of the asphalt mixture was investigated. The experiment was designed using the orthogonal test method, and a regression model was established based on the experimental data. The PSO algorithm was used to optimize the structural parameters of the mixing chamber. The results show that the mixing time of the coarse aggregate is reduced by 19.31%, the mixing time of the fine aggregate is reduced by 36.36%, and the mixing time of the powder is reduced by 33.33%.