Longitudinal deformation profile of a tunnel in weak rock mass by using the back analysis method

Abstract Analysis of the rock mass deformation behavior is a very important aspect of the safety assessment for tunnel construction in weak rock mass. In this paper, the deformation characteristics of a soft rock mass tunnel using three beaches construction method were investigated, which include the crown settlement and horizontal displacement and have 9 sections with 3 different construction schemes. The optimized construction schemes by decreasing the beaches length and changing the geologist of primary support were proposed. Then, applying the displacement back analysis method to calculate the rock mass parameters, double parameters were analyzed by using the golden section method. Results show that the tunnel deformations were affected by the elastic modulus E and the lateral pressure coefficient λ of rock mass, and the change of E has greater influence than λ on the tunnel deformation. The change of λ has greater influence on the crown settlement than that on the horizontal displacement. Furthermore, the regularity and characteristics of longitudinal deformation profile (LDP) in a weak rock mass tunnel was studied by utilizing the Fast Lagrangian Analysis of Continua (FLAC), and the LDP of the three long-beach construction scheme and the three short-beach construction scheme were compared. The results show that the complete displacements of tunnel under the three short-beach construction scheme condition by decreasing the lengths of the middle and lower benches are smaller than that under the three short-beach construction scheme condition, however the pre-deformation of the tunnel deformation under this two construction scheme conditions is nearly the same. The extrusion deformation at the tunnel face of the three short-beach construction scheme is larger than that of the three long-beach construction scheme. Therefore, increasing the area of the core soil is a feasible measure to control the extrusion deformation on the tunnel face. Finally, the tunnel optimized construction scheme was verified benefit the tunnel stability. The measures of decreasing the length of middle and lower bench and closing the invert early and immediately will benefit the tunnel stability.

[1]  Xia-Ting Feng,et al.  Identification of visco-elastic models for rocks using genetic programming coupled with the modified particle swarm optimization algorithm , 2006 .

[2]  Li-ping Li,et al.  Study on Longitudinal Deformation Profile of Rock Mass in a Subsea Tunnel , 2016 .

[3]  W. Schubert,et al.  Displacement Monitoring in Tunnels - an Overview , 2002 .

[4]  Yanbin Luo,et al.  Analysis of tunnel displacement accuracy with total station , 2016 .

[5]  Louis Ngai Yuen Wong,et al.  Shallow tunnelling method (STM) for subway station construction in soft ground , 2012 .

[6]  Yi Min Xie,et al.  Underground excavation shape optimization using an evolutionary procedure , 2005 .

[7]  William W.-G. Yeh,et al.  Aquifer parameter identification with optimum dimension in parameterization , 1981 .

[8]  Giancarlo Gioda,et al.  Back analysis procedures for the interpretation of field measurements in geomechanics , 1987 .

[9]  Yu-Yong Jiao,et al.  Numerical investigation of joint effect on shock wave propagation in jointed rock masses , 2005 .

[10]  Li Xiaohong Intelligent Back Analysis of Tunnel Rock Displacement and Its Application , 2001 .

[11]  Zhu He-hua Back-analysis of Elastoplastic Model of Soil , 2004 .

[12]  G. Hocking,et al.  Three-dimensional elastic stress distribution around the flat end of a cylindrical cavity , 1976 .

[13]  K. Takeuchi,et al.  Back analysis of measured displacements of tunnels , 1983 .

[14]  C. Fairhurst,et al.  APPLICATION OF THE CONVERGENCE-CONFINEMENT METHOD OF TUNNEL DESIGN TO ROCK MASSES THAT SATISFY THE HOEK-BROWN FAILURE CRITERION , 2000 .

[15]  Jianxun Chen,et al.  Application of a Total Station with RDM to Monitor Tunnel Displacement , 2017 .

[16]  Mostafa Sharifzadeh,et al.  Design of sequential excavation method for large span urban tunnels in soft ground – Niayesh tunnel , 2013 .

[17]  Yuzhen Yu,et al.  An intelligent displacement back-analysis method for earth-rockfill dams , 2007 .

[18]  Huang Pei,et al.  Deformation and mechanical model of temporary support sidewall in tunnel cutting partial section , 2017 .

[19]  Seyed Rahman Torabi,et al.  Improving the Performance of Intelligent Back Analysis for Tunneling Using Optimized Fuzzy Systems: Case Study of the Karaj Subway Line 2 in Iran , 2015, J. Comput. Civ. Eng..

[20]  Ying Wang,et al.  Damage Identification Scheme Based on Compressive Sensing , 2015, J. Comput. Civ. Eng..

[21]  C. F. Lee,et al.  Displacement back analysis for a steep slope at the Three Gorges Project site , 2001 .

[22]  Jorge G. Zornberg,et al.  Numerical Analysis of a Tunnel in Residual Soils , 2002 .

[23]  Nick Barton,et al.  Back-analysis of Shimizu Tunnel No. 3 by distinct element modeling , 2007 .

[24]  Giulio Maier,et al.  Parameter estimation of a static geotechnical model using a Bayes' approach , 1983 .

[25]  Louis Ngai Yuen Wong,et al.  Structural Responses of Secondary Lining of High-Speed Railway Tunnel Excavated in Loess Ground , 2013 .

[26]  Peng-fei Li,et al.  Displacement characteristics of high-speed railway tunnel construction in loess ground by using multi-step excavation method , 2016 .

[27]  Ryozo Ooka,et al.  Optimum design for smoke-control system in buildings considering robustness using CFD and Genetic Algorithms , 2009 .

[28]  Lorenzo Jurina,et al.  SOME ASPECTS OF CHARACTERIZATION PROBLEMS IN GEOMECHANICS , 1981 .

[29]  John A. Hudson,et al.  Updated flowcharts for rock mechanics modelling and rock engineering design , 2007 .

[30]  Hiroshi Morioka,et al.  Back-analysis of rock mass strength parameters using AE monitoring data , 2007 .

[31]  Shinji Takasugi,et al.  Inversion of drilling-induced tensile fracture data obtained from a single inclined borehole , 1998 .

[32]  Qian Zhang,et al.  Fiber Bragg Grating Sensors-Based In Situ Monitoring and Safety Assessment of Loess Tunnel , 2016, J. Sensors.

[33]  Jianxun Chen,et al.  Investigation Progresses and Applications of Fractional Derivative Model in Geotechnical Engineering , 2016 .

[34]  Xu Han,et al.  Neural identification of rock parameters using fuzzy adaptive learning parameters , 2003 .

[35]  Takeshi Matsunaga,et al.  Estimation of model parameters and ground movement in shallow NATM tunnel by means of neural network , 2006 .

[36]  Zhenchang Guan,et al.  Rheological parameter estimation for the prediction of long-term deformations in conventional tunnelling , 2009 .

[37]  P. Borne,et al.  Lyapunov analysis of sliding motions: Application to bounded control , 1996 .

[38]  E. Hoek Tunnel support in weak rock , 1998 .

[39]  Zhao Yong Study on Dynamic Deformation Rules and Control Technology of Surrounding Rock for Tunnel , 2010 .

[40]  Daniel Dias,et al.  Back analysis of geomechanical parameters by optimisation of a 3D model of an underground structure , 2011 .

[41]  P. K. Kaiser,et al.  Stress determination by back-analysis of excavation-induced stress changes — a case study , 1990 .

[42]  Yonghong Wu,et al.  A no-tension elastic-plastic model and optimized back-analysis technique for modeling nonlinear mechanical behavior of rock mass in tunneling , 2010 .