Author
Listed:
- Yanxia Gao
(School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities, Huaihua 418000, China
Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua 418000, China)
- Yiwen Liu
(School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities, Huaihua 418000, China
Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua 418000, China)
- Pengju Tang
(School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities, Huaihua 418000, China
Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua 418000, China)
- Chunqiao Mi
(School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China
Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities, Huaihua 418000, China
Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province, Huaihua 418000, China)
Abstract
There are few studies on the land subsidence induced by shield tunneling in the water-rich sandy gravel stratum, which is of high research value. Linear regression and measured data were employed in this study to investigate the land subsidence induced by shield tunneling when crossing the water-rich sandy gravel stratum from Mudan Dadao Station to Longmen Dadao station of Luoyang Metro Line 2. The maximum land subsidence correction coefficient, α, and the settlement trough width correction coefficient, β, were introduced to modify the peck formula to predict land subsidence induced by shield tunneling in Luoyang’s water-rich sandy gravel stratum. It was discovered that the original Peck formula needs to be modified because its prediction result was significantly larger than the actual value. When the value ranges of α and β in the modified Peck formula were 0.379~0.690 and 0.455~0.508, respectively, the modified Peck formula presented a minor error, in terms of the prediction curve, compared with the original formula, and the prediction result was more reliable. The best prediction result could be obtained when α = 0.535 and β = 0.482. In addition, Python could effectively improve the calculation efficiency of the Peck formula modification.
Suggested Citation
Yanxia Gao & Yiwen Liu & Pengju Tang & Chunqiao Mi, 2022.
"Modification of Peck Formula to Predict Surface Settlement of Tunnel Construction in Water-Rich Sandy Cobble Strata and Its Program Implementation,"
Sustainability, MDPI, vol. 14(21), pages 1-11, November.
Handle:
RePEc:gam:jsusta:v:14:y:2022:i:21:p:14545-:d:964186
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Cited by:
- Gang Yu & Yucong Jin & Min Hu & Zhisheng Li & Rongbin Cai & Ruochen Zeng & Vijiayan Sugumaran, 2024.
"Improved Machine Learning Model for Urban Tunnel Settlement Prediction Using Sparse Data,"
Sustainability, MDPI, vol. 16(11), pages 1-23, May.
- Lixian Tang & Qiang Zhou & Shoulong Wang & Wenjie Yao & Bowei Zhang & Ke Xiang & Alfrendo Satyanaga & Jin Tao, 2022.
"Evaluation of the Ground Settlement in an Urban Area Resulting from a Small Curvature Tunneling Construction,"
Sustainability, MDPI, vol. 14(23), pages 1-13, December.
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