A Regression Model for Predicting the Subgrade Modulus of Geocell-Reinforced Sand Beds
文献类型：期刊论文
| 作者 | Zhao, Yang2,5; Lu, Zheng1,5; Yao, Hailin5; Ye, Lei3; Cheng, Ming4; Tang, Chuxuan2,5; Qiu, Yu2,5; Yuan, Xuze2,5 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOMECHANICS
 |
| 出版日期 | 2024 |
| 卷号 | 24期号:1页码:9 |
| 关键词 | Geocells Subgrade modulus Bearing capacity Predicted model FLAC3D |
| ISSN号 | 1532-3641 |
| DOI | 10.1061/IJGNAI.GMENG-7378 |
| 英文摘要 | Geocells have recently been widely used to reinforce subgrade/foundation soil beds. The honeycomb-shaped cells can significantly improve the apparent cohesion and stiffness of soil due to the lateral limitation. This paper aims to predict the subgrade modulus of geocell-reinforced sand beds according to the unreinforced soil and the properties of geocells. Numerical technology was adopted to obtain the original data used for building the predicted model. A laboratory plate load test was initially cited to validate the calculated results obtained using FLAC3D. The validated model was subsequently extended to the baseline model of geocell-reinforced sand beds. The influence of reinforced parameters on bearing capacity and subgrade modulus was discussed deeply. The results revealed that only sufficient lateral deformation could increase the passive resistance of geocells. Based on this, the predicted model was proposed by considering the applied load, unreinforced soil, and geocell parameters. Furthermore, a modified equation was also built to suit all sand with different relative densities. The comparison results showed the suitability and accuracy of this model. |
| 资助项目 | The research described in this paper was financially supported by the National Natural Science Foundation of China (Nos. 42077262, 42077261, and 41972294), the Sichuan Transportation Science and Technology Project (No. KJFZ-2022Y-022), the 2022 Annual Tran[42077262] ; The research described in this paper was financially supported by the National Natural Science Foundation of China (Nos. 42077262, 42077261, and 41972294), the Sichuan Transportation Science and Technology Project (No. KJFZ-2022Y-022), the 2022 Annual Tran[42077261] ; The research described in this paper was financially supported by the National Natural Science Foundation of China (Nos. 42077262, 42077261, and 41972294), the Sichuan Transportation Science and Technology Project (No. KJFZ-2022Y-022), the 2022 Annual Tran[41972294] ; National Natural Science Foundation of China[KJFZ-2022Y-022] ; Sichuan Transportation Science and Technology Project[2022-ZD-017] ; Sichuan Transportation Science and Technology Project[2022-ZD-018] ; 2022 Annual Transportation Industry Science and Technology Project[KY2022042504] ; 2022 Annual Transportation Industry Science and Technology Project[KY2022042501] ; Research Fund Project of Xinjiang Transportation Planning Survey and Design Institute Co., Ltd. |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001113892600012 |
| 出版者 | ASCE-AMER SOC CIVIL ENGINEERS |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/40229]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Lu, Zheng |
| 作者单位 | 1.Hubei Key Lab Geoenvironm Engn, Wuhan 430071, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Anhui He Chuang New Synthet Mat Co Ltd, Huainan 232221, Peoples R China 4.Jilin Prov Transport Sci Res Inst, Changchun 130012, Peoples R China 5.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Yang,Lu, Zheng,Yao, Hailin,et al. A Regression Model for Predicting the Subgrade Modulus of Geocell-Reinforced Sand Beds[J]. INTERNATIONAL JOURNAL OF GEOMECHANICS,2024,24(1):9. |
| APA | Zhao, Yang.,Lu, Zheng.,Yao, Hailin.,Ye, Lei.,Cheng, Ming.,...&Yuan, Xuze.(2024).A Regression Model for Predicting the Subgrade Modulus of Geocell-Reinforced Sand Beds.INTERNATIONAL JOURNAL OF GEOMECHANICS,24(1),9. |
| MLA | Zhao, Yang,et al."A Regression Model for Predicting the Subgrade Modulus of Geocell-Reinforced Sand Beds".INTERNATIONAL JOURNAL OF GEOMECHANICS 24.1(2024):9. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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