Mechanical Parameter Inversion in Sandstone Diversion Tunnel and Stability Analysis during Operation Period

Zhaoqiang Wang, Xin Chen, Xinhua Xue, Lei Zhang, Wenkai Zhu


A large number of experimental studies show that the mechanical parameters of deep buried surrounding rock show significant attenuation characteristics with the increase of strain from the rheological acceleration stage to the attenuation stage. However, the existing numerical models all take mechanical parameters as constants when describing the rheological behavior of surrounding rocks, which can only be applied to the stability analysis of the shallowly buried tunnel. Therefore, this work proceeding from the actual project, improved the sandstone rheological constitutive model and optimized the algorithm of parameter inversion, and put forward a long-term stability analysis model that can accurately reflect the rheological characteristics of surrounding rocks under the complex geological condition including high stress induced by great depth and high seepage pressure. In the process, a three-dimensional nonlinear rheological damage model was established based on Burgers rheological model by introducing damage factors into the derivation of the sandstone rheological constitutive model to accurately describe the rheological behaviors of the deep buried tunnel. And BP (Back Propagation) neural network optimized by the multi-descendant genetic algorithm is used to invert the mechanical parameters in the model, which improves the efficiency and precision of parameter inversion. Finally, the rheological equation was written by using parametric programming language and incorporated into the general finite element software ANSYS to simulate the rheological behavior of the tunnel rock mass at runtime. The results of the model analysis are in good agreement with the monitoring data in the later stage. The research results can provide a reference for the stability analysis of similar projects.


Deep Buried Tunnel; Rheological Deformation; Creep Damage Model; Parametric Inversion; Runtime Stability Analysis.


Chen, Guoqin, Xiating Feng, Hui Zhou, Bingrui Chen, Shuling Huang, and Chuanqing Zhang. “Numerical analysis of the long-term stability of the seepage tunnel in Jinping II Hydropower Station.” Rock and Soil Mechanics 28, no. S1 (October 2007): 417-422. doi:10.16285/j.rsm.2007.s1.186.

Hu, Quanguang, Haosen Xiong, and Qinzhi Xing. “Numerical Analysis of the Long-term Stabiliy of the Water diversion tunnel of N-J Hydropower Station.” Soil Eng. and Foundation 32, no. 2(April 2018): 189-193.

Liu, Zhiyong, Mingli Xia, Zhuo Li, Hongqiang Xie, and Jiangda He. “Aging Characteristics of Quartz Mica Schist and Back-analysis of Rheological Parameters.” Water Resources and Power 34, no. 7 (July 2018): 138-142.

Jin, Peng, Liquan Xie, Bowen Jiang, and Yifan Ji. “Numerical Analysis of the Long-Term Stability of Water Diversion Tunnel Crossing Rock Layers.” Modern Tunneling Technology 55, no. S2 (November 2018): 916-921. doi:10.13807/j.cnki.mtt.2018.S2.119.

Feng, Shiguo, Jie Liu, Ruihong Wang, and Yunan Yang. “Safety of lining structure and stability its surrounding rocks for the diversion tunnel of Danba Hydropower Station.” South-to-North Water Transfers and Water Science & Technology 17, no. 3(June 2019): 128-138. doi:10.13476/j.cnki.nsbdqk.2019.0068.

Ru, Long, and Haohao Deng. “Simulation and Analysis of the Stability at the Fork of Deep Diversion Tunnel.” Northern Communications no. 3 (March 2019): 72-75. doi:10.15996 /j.cnki.bfjt.2019.03.019.

SHI, Kun. “Equivalent Characteristic Parameters of Mechanical Joints.” Journal of Mechanical Engineering 54, no. 19 (2018): 144. doi:10.3901/jme.2018.19.144.

Saxena, Nitin Kumar, and Ashwani Kumar. “Analytical Approach to Estimate Mechanical Parameters in Induction Machine Using Transient Response Parameters.” International Transactions on Electrical Energy Systems 29, no. 3 (October 22, 2018): e2751. doi:10.1002/etep.2751.

Kumar, Ravinder, and Dr. Dinesh Kumar. “Optimization of Process Parameters on Tig Welding to Enhance Mechanical Properties of AA-6351 T6 Alloy.” International Journal of Trend in Scientific Research and Development Volume-3, no. Issue-4 (June 30, 2019): 505–509. doi:10.31142/ijtsrd23831.

Ebrahimi, Mahmoud, Kamal Hamed Tabei, Reza Naseri, and Faramarz Djavanroodi. “Effect of Flow-Forming Parameters on Surface Quality, Geometrical Precision and Mechanical Properties of Titanium Tube.” Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 232, no. 6 (October 25, 2017): 702–708. doi:10.1177/0954408917738126.

Manea, Dragos, Mihai Gidea, Eugen Marin, and Marinela Mateescu. “Simulation of Mechanical Parameters of Sprayer Boom” (May 23, 2018). doi:10.22616/erdev2018.17.n048.

Cui, Kai, and Xiang Jing. “Research on Prediction Model of Geotechnical Parameters Based on BP Neural Network.” Neural Computing and Applications (November 26, 2018). doi:10.1007/s00521-018-3902-6.

Muniyappan, S., and P. Rajendran. “Contrast Enhancement of Medical Images through Adaptive Genetic Algorithm (AGA) over Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).” Multimedia Tools and Applications 78, no. 6 (July 22, 2018): 6487–6511. doi:10.1007/s11042-018-6355-0.

Sobey, A J, and P A Grudniewski. “Re-Inspiring the Genetic Algorithm with Multi-Level Selection Theory: Multi-Level Selection Genetic Algorithm.” Bioinspiration & Biomimetics 13, no. 5 (July 31, 2018): 056007. doi:10.1088/1748-3190/aad2e8.

Arun, J., and M. Karthikeyan. “Optimized Cognitive Radio Network (CRN) Using Genetic Algorithm and Artificial Bee Colony Algorithm.” Cluster Computing (March 8, 2018). doi:10.1007/s10586-018-2350-5.

Barbero, Ever J., and Mehdi Shahbazi. “Determination of Material Properties for ANSYS Progressive Damage Analysis of Laminated Composites.” Composite Structures 176 (September 2017): 768–779. doi:10.1016/j.compstruct.2017.05.074.

Zhiltsov, Yuri V., and Viktor V. Elshin. “Use of Ansys CFX Software for Combined Boiler Model Development.” Proceedings of Irkutsk State Technical University 21, no. 3 (March 2017): 81–90. doi:10.21285/1814-3520-2017-3-81-90.

Голубев, А.Г., and О.И. Ремизова. “Cones in ANSYS Fluent with the Usage of Two Different Methods for Constructing a Computational Grid.” Engineering Journal: Science and Innovation no. 83 (November 2018). doi:10.18698/2308-6033-2018-11-1821.

Pise, Shyamal, and G. R. Patil. “Numerical Study of Gravity Dam with Gallery Study under Influence of Sloshing Wave Using Ansys.16.” Journal of Advances and Scholarly Researches in Allied Education (April 1, 2018): 266–270. doi:10.29070/15/56829.

Кожанов, Д.А., and А.К. Любимов. “Import Model of Flexible Woven Composites in ANSYS Mechanical APDL.” Computer Research and Modeling 10 no.6 (December 2018): 789–799. doi:10.20537/2076-7633-2018-10-6-789-799.

Wagner, Horst. “Deep Mining: A Rock Engineering Challenge.” Rock Mechanics and Rock Engineering 52, no. 5 (April 13, 2019): 1417–1446. doi:10.1007/s00603-019-01799-4.

Basahel, Hassan, and Hani Mitri. “Probabilistic Assessment of Rock Slopes Stability Using the Response Surface Approach – A Case Study.” International Journal of Mining Science and Technology 29, no. 3 (May 2019): 357–370. doi:10.1016/j.ijmst.2018.11.002.

Bautmans, Peter, Erling Fjær, and Per Horsrud. “The Effect of Weakness Patches on Wellbore Stability in Anisotropic Media.” International Journal of Rock Mechanics and Mining Sciences 104 (April 2018): 165–173. doi:10.1016/j.ijrmms.2018.01.016.

Basarir, Hakan, Yuantian Sun, and Guichen Li. “Gateway Stability Analysis by Global-Local Modeling Approach.” International Journal of Rock Mechanics and Mining Sciences 113 (January 2019): 31–40. doi:10.1016/j.ijrmms.2018.11.010.

Ramadasan, Datta, Marc Chevaldonné, and Thierry Chateau. “LMA: A Generic and Efficient Implementation of the Levenberg-Marquardt Algorithm.” Software: Practice and Experience 47, no. 11 (April 26, 2017): 1707–1727. doi:10.1002/spe.2497.

Ramadasan, Datta, Marc Chevaldonné, and Thierry Chateau. “LMA: A Generic and Efficient Implementation of the Levenberg-Marquardt Algorithm.” Software: Practice and Experience 47, no. 11 (April 26, 2017): 1707–1727. doi:10.1002/spe.2497.

Park, Jo Eun, and Sang Hyun Kim. “Application of Levenberg Marquardt Method for Calibration of Unsteady Friction Model for a Pipeline System.” Journal of Korea Water Resources Association 46, no. 4 (April 30, 2013): 389–400. doi:10.3741/jkwra.2013.46.4.389.

Yogi, I B S, and Widodo. “Central Loop Time Domain Electromagnetic Inversion Based on Born Approximation and Levenberg-Marquardt Algorithm.” IOP Conference Series: Earth and Environmental Science 62 (April 2017): 012029. doi:10.1088/1755-1315/62/1/012029.

Kim, Yeonjo, Byungjin Lee, and Sangkyung Sung. “Performance Analysis on Attitude Estimation Using Levenberg-Marquardt Optimization Method for Integrated Navigation System.” Journal of Institute of Control, Robotics and Systems 24, no. 3 (March 31, 2018): 284–289. doi:10.5302/j.icros.2018.18.0002.

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DOI: 10.28991/cej-2019-03091382


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