Mechanical response and data-driven fatigue model of interlayer soils in track-bed considering multi-factor coupling effect
文献类型：期刊论文
| 作者 | Duan, Shuqian3; Zhang, Minghuan3; Xu, Dingping1; Xiong, Jiecheng3; Cui, Yujun4; Su, Yu2 |
| 刊名 | COMPUTERS AND GEOTECHNICS
 |
| 出版日期 | 2023-11-01 |
| 卷号 | 163页码:18 |
| 关键词 | Interlayer soils Cyclic triaxial tests Fatigue model Data-driven approach Permanent strain |
| ISSN号 | 0266-352X |
| DOI | 10.1016/j.compgeo.2023.105749 |
| 英文摘要 | This study delves into the mechanical behavior of interlayer soils in conventional French railway track beds. The focus is on the influence of four key factors: volumetric coarse grains content, stress state, number of cycles, and water content. Comprehensive analysis of experimental results reveals that permanent deformation and resilient modulus are significantly affected by the interplay of these factors. Notably, the relationship between these factors and the permanent deformation of interlayer soils is sophisticated and coupled, and more advanced models may be required to sufficiently reflect their behavior. To better understand the complex relationships among these factors and accurately predict the behavior of interlayer soil, a fatigue model based on Artificial Neural Networks (ANN, i.e. a classical data-driven approach) was developed. The model demonstrates high prediction reliability and accuracy, with a determination coefficient (R2) of 0.9996, a mean absolute error (MAE) of 0.0044, and a root mean square error (RMSE) of 0.006629. Thereafter, the proposed model was compared with the laboratory cyclic test results as well as with the commonly-used empirical fatigue models, and a permanent strain curve of the interlayer soil were also successfully predicted by using test set. Results show that the proposed model could effectively capture the influence of multiple coupled factors on permanent plastic strain, adapting to a wide range of interlayer soil conditions. In conclusion, the data-driven fatigue model provides valuable insights into the combined effects of various factors on interlayer soil behavior, offering an effective tool for evaluating the performance of French traditional track beds under different conditions. |
| 资助项目 | National Natural Science Foundation of China[52279114] ; National Natural Science Foundation of China[51909241] ; National Natural Science Foundation of China[52279117] ; National Natural Science Foundation of China[52008376] ; Henan Province Science and Technology Innovation Talent Program[2023HYTP002] ; China Postdoctoral Science Foundation[2023T160200] |
| WOS研究方向 | Computer Science ; Engineering ; Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001062897300001 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/39415]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Xu, Dingping |
| 作者单位 | 1.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Hubei, Peoples R China 2.Nanchang Univ, Sch Infrastruct Engn, Nanchang 330031, Peoples R China 3.Zhengzhou Univ, Sch Hydraul & Civil Engn, Zhengzhou 450001, Henan, Peoples R China 4.Ecole Ponts ParisTech ENPC, Lab Navier, CERMES, 6-8 Av Blaise Pascal, F-77455 Champs Sur Marne 2, Marne La Vallee, France |
| 推荐引用方式 GB/T 7714 | Duan, Shuqian,Zhang, Minghuan,Xu, Dingping,et al. Mechanical response and data-driven fatigue model of interlayer soils in track-bed considering multi-factor coupling effect[J]. COMPUTERS AND GEOTECHNICS,2023,163:18. |
| APA | Duan, Shuqian,Zhang, Minghuan,Xu, Dingping,Xiong, Jiecheng,Cui, Yujun,&Su, Yu.(2023).Mechanical response and data-driven fatigue model of interlayer soils in track-bed considering multi-factor coupling effect.COMPUTERS AND GEOTECHNICS,163,18. |
| MLA | Duan, Shuqian,et al."Mechanical response and data-driven fatigue model of interlayer soils in track-bed considering multi-factor coupling effect".COMPUTERS AND GEOTECHNICS 163(2023):18. |
入库方式： OAI收割
来源：武汉岩土力学研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。