A Prediction Method for the California Bearing Ratio of Soil-Rock Mixture Based on the Discrete Element Method and CT Scanning
Joint Authors
Li, Shouwei
Hu, Jianming
Ji, Xiaoping
Jiang, Yingjun
Li, Jia
Cui, Zhifei
Xiong, Yue
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-01
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Because of the large amount of gravel with particle sizes over 40 mm in the soil-rock mixture (SRM), it is impossible to determine its California Bearing Ratio (CBR) via the indoor test method, which is a key parameter for designing the backfill in underground mined cavities or the road subgrade constructed with SRM.
In this paper, X-ray computed tomography (CT) scanning and 3D reconstruction technology were used to construct the 3D structure of SRM particles with a particle size greater than 5 mm.
Based on the vertical vibration test method (VVTM) and PFC3D, the numerical simulation method (NSM-CBR) of SRM was established.
The CBR of the SRM with a maximum particle size over 40 mm (SRM-G) was studied by NSM-CBR, and the effects of factors such as maximum particle size, soil content, and large-size particle content (d ≥ 40 mm) on the CBR were investigated via NSM-CBR.
Based on the laboratory tests and NSM-CBR, the prediction model and the determining method of CBR of SRM-G were established and verified.
The results show that the maximum deviation between the CBR obtained from NSM-CBR and laboratory tests was 7.4%.
The CBR of SRM-G decreases linearly with the increase in soil content and increases with the increase in maximum particle size and large-size particle content.
The practical project shows that the maximum deviation between the predictive and measured values of the CBR of SRM-G was less than 1.5%, indicating that the prediction model and the method established in this paper have high reliability.
American Psychological Association (APA)
Ji, Xiaoping& Li, Jia& Cui, Zhifei& Li, Shouwei& Xiong, Yue& Hu, Jianming…[et al.]. 2020. A Prediction Method for the California Bearing Ratio of Soil-Rock Mixture Based on the Discrete Element Method and CT Scanning. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1125984
Modern Language Association (MLA)
Ji, Xiaoping…[et al.]. A Prediction Method for the California Bearing Ratio of Soil-Rock Mixture Based on the Discrete Element Method and CT Scanning. Advances in Civil Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1125984
American Medical Association (AMA)
Ji, Xiaoping& Li, Jia& Cui, Zhifei& Li, Shouwei& Xiong, Yue& Hu, Jianming…[et al.]. A Prediction Method for the California Bearing Ratio of Soil-Rock Mixture Based on the Discrete Element Method and CT Scanning. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1125984
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1125984