Published

2019-10-01

The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model

El tratamiento integral del antiguo cuerpo deformable por deslizamiento de tierra en el lecho de roca profunda gigante basado en el modelo de análisis FLAC

DOI:

https://doi.org/10.15446/esrj.v23n4.84008

Keywords:

FLAC, Neural Network, Landslide, Deformable Body, Jm Tunnel (en)
FLAC, Red neuronal, Deslizamiento de tierra, Cuerpo deformable, Túnel JM (es)

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Authors

  • Hongsheng Zhou State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610000, China
  • Yunsheng Wang State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610000, China
  • Tong Shen State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610000, China
  • Qianqian Feng State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610000, China

In previous studies, most of the studies are based on the failure mechanism of the landslide deformable body on tunnel and the safety monitoring and early warning after the completion of the tunnel, while there is less research on tunnel construction. In order to study the comprehensive treatment of the deformable body of the ancient landslide in the giant deep rock bedding better, the treatment of JM tunnel landslide deformable body was selected to carry on the empirical study. After a detailed analysis of the geological characteristics of JM tunnel engineering landslide, the stability analysis of the landslide and the deformation body and the calculation of the thrust value based on the FLAC model were carried out on the basis of the monitoring data. After the construction of the model, the intensity parameters of the slip mass deformation and the sliding zone were obtained from the back analysis. On the basis of the above, the comprehensive treatment scheme for the rear side of the old landslide deformation body was determined, including earthwork cleanup, grading supporting, and the back pressure by abandoning the cleaned earthwork at the leading edge. The study is of great significance to the design of the construction of undercrossing tunnel of landslide under the complicated geological conditions.

En estudios anteriores, la mayoría se basa en el mecanismo de falla del cuerpo deformable por deslizamiento de tierra en el túnel y el monitoreo de seguridad y alerta temprana después de la finalización del túnel, mientras que hay menos investigación sobre la construcción del túnel. Para estudiar mejor el tratamiento integral del cuerpo deformable del antiguo deslizamiento de tierra en el lecho de roca profunda gigante, se seleccionó el tratamiento del cuerpo deformable de deslizamiento de túnel del túnel JM para llevar a cabo el estudio empírico. Después de un análisis detallado de las características geológicas del deslizamiento de tierra de ingeniería de túneles JM, el análisis de estabilidad del deslizamiento de tierra y el cuerpo de deformación y el cálculo del valor de empuje basado en el modelo FLAC se llevaron a cabo sobre la base de los datos de monitoreo. Después de la construcción del modelo, los parámetros de intensidad de la deformación de la masa de deslizamiento y la zona de deslizamiento se obtuvieron del análisis posterior. Sobre la base de lo anterior, se determinó el esquema de tratamiento integral para la parte posterior del antiguo cuerpo de deformación por deslizamiento de tierra, incluida la limpieza del movimiento de tierras, el soporte de nivelación y la contrapresión al abandonar el movimiento de tierra limpio en el borde de ataque. El estudio es de gran importancia para el diseño de la construcción del túnel de deslizamiento de tierra bajo condiciones geológicas complicadas.

References

Chen, C., Xiao, B., Sun, X., & Fang, G. (2014). Causes Analysis and Treatment of the Landslide of a Highway Tunnel Entrance. Construction Technology, S2, 165-168.

Deng, X. P. (2014). Analysis and Comprehensive Treatment of Landslide for Wenling Tunnel. Highway, 5, 119-122.

Jiang, B. (2010). Diversion tunnel landslide treatment of Bulungkol-Gongur Hydropower Station. Guangxi Water Resources & Hydropower Engineering, 2010-01.

Lin, X. (2011). Long deep highway landslide disaster action mountain and treatment project countermeasures. Fujian Architecture & Construction, 2, 67-69.

Liu, H. (2012). Geological problems and treatment measures for highway tunnel through ancient landslide. Journal of Engineering Geology, 20(4), 540-546.

Liu, J. & Qian, Y. (2014). Cause Analysis of Qingfeng Landslide and its Treatment Measures of Gu-Zhu Highway. Transportation Science & Technology, 2014-3.

Mei, L., Peng, J. L., & Xiao-Hong, H. U. (2008). Research on Present Situation of Highway Tunnel Landslide and its Treating Method. Storage Transportation & Preservation of Commodities, 30(4), 41-42.

Ming-Zhu, H. U., Kong, D. G., & Zheng, J. (2011). Stability Evaluation and Treatment Measures of Miyi Landslide along Xichang-Panzhihua Highway. Subgrade Engineering, 6, 169-173.

Shi, X. (2012). Landslide Treatment and Safety Monitoring Research of Lower-imbedding Unsymmetrical-pressure Qing-ping Tunnel. Highway Engineering, 4, 157-160.

Shuan-Cheng, G. U., Wang, B. Q., Wang, J., & He, W. G. (2015). Comprehensive Treatment Technology and Evaluation for Tangjiayuan Tunnel Through the Landslide Section. Journal of Railway Engineering Society, 2015-01.

Shuanping, L. I. (2010). Analysis and Treatment for Arch Landslide on Emergency Lay-by on Dawangding Tunnel. Technology of Highway & Transport, 2010-06.

Song-Yue, Y. E., Cao, R. H., Hong, H. T., & Zhou, Z. Q. (2008). Analysis of Reviviscence Characteristic and Optimal Selection of Treatment Projects of Ancient Landslide Body Located on the Exit of Zhangping Tunnel. Communications Standardization, 7.

Sun, H. Y., Wong, L. N. Y., Shang, Y. Q., Shen, Y. J., & Lü, Q. (2010). Evaluation of drainage tunnel effectiveness in landslide control. Landslides, 7(4), 445-454.

Wang, K., Kang, H. G., & Wang, H. T. (2011). Recovery Execution in Landslide at the Portal of Highway Tunnel. Advanced Materials Research, 250-253, 1823-1826.

Xiao, Z. W. & Huang, L. (2013). Analysis and Treatment of Landslide at the Tunnel Portal in Nanjing Road. Applied Mechanics & Materials, 353-356, 686-691.

Xueyong, Y. U., Cai, Q., Zhao, D., & Zhu, D. (2013). Analysis on Genesis of Landslide at the Exit of Wusha Tunnel and the Treatment Design. Subgrade Engineering, 4, 167-171.

Yang, X. G., Peng, J. G., Gong, X. W., & Wu, S. (2012). Comprehensive Treatment on Landslide at the Entrance of Shejiapo Tunnel on Xuyong-Gulin Railway. Subgrade Engineering, 2012-05.

Yan, L. I., Guan, Z. H., Xie, Z. W. (2006). Analysis on the Causes of landslide in Beihai Road Tunnel and the plans of Emergency Repair. West-China Exploration Engineering, 18, 164-166.

Zhenyu, Y. I., Chen, H., & Wan, P. (2014). Discussion of Treatment Techhique on Great Collapse of Hanlinjie Tunnel. Highway Engineering, 1, 177-179.

Zhou, K., Zeng, Y., & Zhu, W. (2012). Slope treatment of highway tunnel with water-softening surrounding rock under complex geological conditions. Journal of Water Resources & Water Engineering, 23(6).

How to Cite

APA

Zhou, H., Wang, Y., Shen, T. and Feng, Q. (2019). The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model. Earth Sciences Research Journal, 23(4), 303–308. https://doi.org/10.15446/esrj.v23n4.84008

ACM

[1]
Zhou, H., Wang, Y., Shen, T. and Feng, Q. 2019. The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model. Earth Sciences Research Journal. 23, 4 (Oct. 2019), 303–308. DOI:https://doi.org/10.15446/esrj.v23n4.84008.

ACS

(1)
Zhou, H.; Wang, Y.; Shen, T.; Feng, Q. The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model. Earth sci. res. j. 2019, 23, 303-308.

ABNT

ZHOU, H.; WANG, Y.; SHEN, T.; FENG, Q. The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model. Earth Sciences Research Journal, [S. l.], v. 23, n. 4, p. 303–308, 2019. DOI: 10.15446/esrj.v23n4.84008. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/84008. Acesso em: 14 jul. 2024.

Chicago

Zhou, Hongsheng, Yunsheng Wang, Tong Shen, and Qianqian Feng. 2019. “The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model”. Earth Sciences Research Journal 23 (4):303-8. https://doi.org/10.15446/esrj.v23n4.84008.

Harvard

Zhou, H., Wang, Y., Shen, T. and Feng, Q. (2019) “The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model”, Earth Sciences Research Journal, 23(4), pp. 303–308. doi: 10.15446/esrj.v23n4.84008.

IEEE

[1]
H. Zhou, Y. Wang, T. Shen, and Q. Feng, “The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model”, Earth sci. res. j., vol. 23, no. 4, pp. 303–308, Oct. 2019.

MLA

Zhou, H., Y. Wang, T. Shen, and Q. Feng. “The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model”. Earth Sciences Research Journal, vol. 23, no. 4, Oct. 2019, pp. 303-8, doi:10.15446/esrj.v23n4.84008.

Turabian

Zhou, Hongsheng, Yunsheng Wang, Tong Shen, and Qianqian Feng. “The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model”. Earth Sciences Research Journal 23, no. 4 (October 1, 2019): 303–308. Accessed July 14, 2024. https://revistas.unal.edu.co/index.php/esrj/article/view/84008.

Vancouver

1.
Zhou H, Wang Y, Shen T, Feng Q. The Comprehensive Treatment of the Ancient Landslide Deformable Body in the Giant Deep Rock Bedding based on the FLAC Analysis Model. Earth sci. res. j. [Internet]. 2019 Oct. 1 [cited 2024 Jul. 14];23(4):303-8. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/84008

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CrossRef citations5

1. Weiji Liu, Hai Hu, Xiaohua Zhu, Bin Tan, Zhilin Li. (2022). Investigation on the Tool-Rock Interaction Using an Extended Grain-Based Model. KSCE Journal of Civil Engineering, 26(6), p.2992. https://doi.org/10.1007/s12205-022-2197-4.

2. Jiawei Fan, Yufang Zhang, Wenjiao Zhou, Chuan Yin. (2022). Landslide-tunnel interaction mechanism and numerical simulation during tunnel construction: a case from expressway in Northwest Yunnan Province, China. Arabian Journal of Geosciences, 15(16) https://doi.org/10.1007/s12517-022-10680-8.

3. Ke-ping ZHOU, Liang LI, Yun LIN, Xin XIONG, Nian-ge YANG, Shu-lin CHEN. (2023). New method and application of disturbance range prediction for caving method of metal ore. Transactions of Nonferrous Metals Society of China, 33(3), p.889. https://doi.org/10.1016/S1003-6326(23)66153-9.

4. Qiang Cheng, Shiguo Xiao, Tianxiang Liu, Tingjun Chen, Shaohong Li, Anhui Wei. (2021). Twin tunneling–induced deep-seated landslide in layered sedimentary rocks. Bulletin of Engineering Geology and the Environment, 80(12), p.9071. https://doi.org/10.1007/s10064-021-02482-1.

5. Yiwen Qin, Yuhua Chen, Jinxing Lai, Junling Qiu, Zhichao Wang, Tong Liu, Wenbo Zan. (2024). Failures in loess slope-tunnel system: An overview of trigging sources, acting mechanism and mitigation strategies. Engineering Failure Analysis, 158, p.107996. https://doi.org/10.1016/j.engfailanal.2024.107996.

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