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

Advances in Civil Engineering

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

Civil Engineering

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