Abstract
Tunnel excavations in heavily fractured rock masses are often subjected to the high risk of face instability. To solve this problem, the probabilistic stability analysis of tunnel face is performed in this contribution, in which the fractured rock masses are modelled as spatially random media that follow the Hoek–Brown failure criterion. The method of Karhunen–Loève expansion is adopted to characterize the spatial variabilities of Hoek–Brown parameters. Under this circumstance, the conventional tangent technique fails to integrate the Hoek–Brown failure criterion into the kinematical approach of limit analysis framework. Thus, the multi-tangent method which permits to use multiple tangent lines to represent the nonlinear Hoek–Brown failure envelope is proposed. A discretized three-dimensional failure mechanism of tunnel face is adopted to determine critical face pressures within the framework of limit analysis. Due to a large number of input variables required by the generation of random fields, the global sensitivity analysis and a sparsity scheme are employed to reduce the problem dimension. The method of spare polynomial chaos expansion is then employed to perform Monte Carlo simulation with a significant reduction of calls to the computationally expensive original model. Finally, the parametric analysis on the deterministic model and probabilistic model is performed to gain an insight into the proposed approach.
Highlights
-
The three-dimensional stability of a tunnel face driven in Hoek-Brown rock masses is evaluated by combining the limit analysis and random field theory.
-
The method of Karhunen-Loève expansion is adopted to characterize the spatial variabilities of Hoek-Brown parameters.
-
A multi-tangent method is proposed to determine the equivalent shear strength parameters of rock masses.
-
A fast and accurate probabilistic model for tunnel face reliability analysis is obtained with the sparse polynomial chaos expansion method.
Similar content being viewed by others
Abbreviations
- σ 1 :
-
Maximum principle stress
- σ 3 :
-
Minimum principle stress
- σ c :
-
Uniaxial compressive strength
- m i :
-
Constant related to the hardness of the rock masses
- GSI:
-
Geological strength index
- D :
-
Artificial disturbance factor
- c t :
-
Equivalent cohesion of rock masses
- φ t :
-
Equivalent internal friction angle of rock masses
- G i :
-
Lognormal random field of parameter i
- G ln i :
-
Normal random field of parameter lni
- μ i :
-
Mean value of parameter i
- σ i :
-
Standard deviation of parameter i
- M :
-
Number of truncation terms in Karhunen–Loève expansion
- ξ j :
-
Independent variable of standard normal distribution
- λ j :
-
Eigenvalue of the autocorrelation function
- ψ j :
-
Eigenfunction of the autocorrelation function
- ε err :
-
Error of the Karhunen–Loève expansion
- Ω:
-
Domain of the random field
- ρ i :
-
Autocorrelation function
- ρ i , j :
-
Cross-correlation between random fields of i and j
- θ h :
-
Horizontal autocorrelation distance
- θ v :
-
Vertical autocorrelation distance
- COV:
-
Coefficient of variation
- ω :
-
Angular velocity of the failure mechanism
- O :
-
Rotation center
- E :
-
Center of the circular tunnel face
- r E :
-
Length of OE
- β E :
-
Rotation angle of OE
- d :
-
Tunnel diameter
- δ :
-
Side length of discretized element
- [σ 3]n :
-
Minimum principle stress of the element n
- γ :
-
Unit weight of rock masses
- l :
-
Number of layers in the domain Ω
- h n :
-
Burial depth of the element n
- F :
-
Computational model
- Y :
-
Model response
- L :
-
Number of input variables
- ψ α :
-
Multivariate polynomial
- η j :
-
Unknown coefficients of the PCE
- P :
-
Number of terms in the truncated PCE
- H α :
-
Univariate polynomial
- α :
-
Degree of the univariate polynomial
- p :
-
PCE order
- ||α||q :
-
q-Quasi-norm of α
- χ :
-
Experimental design
- N :
-
Size of experimental design
- Ψ :
-
Space-independent matrix with dimensions of N × P
- S :
-
Sobol’s indices
- R 2 :
-
Coefficient of determination
- ε cut :
-
Cutoff value:
- \(Q_{tgt}^{2}\) :
-
Target accuracy
- p max :
-
Maximum PCE order
- g T :
-
Performance function
- σ U :
-
Applied face pressure
- σ T :
-
Critical face pressure
- N MCS :
-
Size of MCS population
- I :
-
Indicator function
- P f :
-
Failure probability
References
Al-Bittar T, Soubra AH (2014) Efficient sparse polynomial chaos expansion methodology for the probabilistic analysis of computationally-expensive deterministic models. Int J Numer Anal Meth Geomech 38(12):1211–1230
Al-Bittar T, Soubra AH (2017) Bearing capacity of spatially random rock masses obeying Hoek-Brown failure criterion. Georisk Assess Manag Risk Eng Syst Geohazards 11(2):215–229
Blatman G, Sudret B (2010) An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis. Probab Eng Mech 25(2):183–197
Blatman G, Sudret B (2011) Adaptive sparse polynomial chaos expansion based on least angle regression. J Comput Phys 230(6):2345–2367
Chen F, Wang L, Zhang W (2019) Reliability assessment on stability of tunnelling perpendicularly beneath an existing tunnel considering spatial variabilities of rock mass properties. Tunn Undergr Space Technol 88:276–289
Dadashzadeh N, Duzgun HSB, Yesiloglu-Gultekin N (2017) Reliability-based stability analysis of rock slopes using numerical analysis and response surface method. Rock Mech Rock Eng 50(8):2119–2133
Fenton GA, Griffiths DV (2003) Bearing-capacity prediction of spatially random c φ soils. Can Geotech J 40(1):54–65
Fenton GA, Griffiths DV (2008) Risk assessment in geotechnical engineering. Wiley, Hoboken
Gong W, Juang CH, Wasowski J (2021) Geohazards and human settlements: lessons learned from multiple relocation events in Badong China-Engineering geologist’s perspective. Eng Geol 285:106051
Guo X, Du D, Dias D (2019) Reliability analysis of tunnel lining considering soil spatial variability. Eng Struct 196:109332
Hoek E, Brown ET (1997) Practical estimates of rock mass strength. Int J Rock Mech Min Sci 34(8):1165–1186
Hoek E, Carranza-Torres C, Corkum B (2002) Hoek-Brown failure criterion-2002 edition. Proc NARMS-Tac 1(1):267–273
Hoek E, Brown ET (1980) Empirical strength criterion for rock masses. J Geotech Geoenviron Eng 106(ASCE 15715)
Huang F, Wang D, Xiao N, Ou RC (2021) Upper bound limit analysis of blow-out failure mode of excavation face of shield tunnel considering groundwater seepage. Geomech Eng 26(3):227–234
Jiang SH, Li DQ, Cao ZJ, Zhou CB, Phoon KK (2015) Efficient system reliability analysis of slope stability in spatially variable soils using Monte Carlo simulation. J Geotech Geoenviron Eng 141(2):04014096
Leca E, Dormieux L (1990) Upper and lower bound solutions for the face stability of shallow circular tunnels in frictional material. Geotechnique 40(4):581–606
Li AJ, Cassidy MJ, Wang Y, Merifield RS, Lyamin AV (2012) Parametric Monte Carlo studies of rock slopes based on the Hoek-Brown failure criterion. Comput Geotech 45:11–18
Li T, Gong W, Tang H (2021) Three-dimensional stochastic geological modeling for probabilistic stability analysis of a circular tunnel face. Tunn Undergr Space Technol 118:104190
Lü Q, Low BK (2011) Probabilistic analysis of underground rock excavations using response surface method and SORM. Comput Geotech 38(8):1008–1021
Lü Q, Xiao Z, Zheng J, Shang Y (2018) Probabilistic assessment of tunnel convergence considering spatial variability in rock mass properties using interpolated autocorrelation and response surface method. Geosci Front 9(6):1619–1629
Luo WJ, Yang XL (2018) 3D stability of shallow cavity roof with arbitrary profile under influence of pore water pressure. Geomech Eng 16(6):569–575
Michalowski RL, Park D (2020) Stability assessment of slopes in rock governed by the Hoek-Brown strength criterion. Int J Rock Mech Min Sci 127:104217
Mollon G, Dias D, Soubra AH (2009) Face stability analysis of circular tunnels driven by a pressurized shield. J Geotech Geoenviron Eng 136(1):215–229
Mollon G, Dias D, Soubra AH (2011a) Rotational failure mechanisms for the face stability analysis of tunnels driven by a pressurized shield. Int J Numer Anal Meth Geomech 35(12):1363–1388
Mollon G, Dias D, Soubra AH (2011b) Probabilistic analysis of pressurized tunnels against face stability using collocation-based stochastic response surface method. J Geotech Geoenviron Eng 137(4):385–397
Pan Q, Dias D (2017) Probabilistic evaluation of tunnel face stability in spatially random soils using sparse polynomial chaos expansion with global sensitivity analysis. Acta Geotech 12(6):1415–1429
Pan Q, Dias D (2018) Probabilistic analysis of a rock tunnel face using polynomial chaos expansion method. Int J Geomech 18(4):04018013
Pan Q, Dias D, Sun Z (2017) A new approach for incorporating Hoek-Brown failure criterion in kinematic approach—case of a rock slope. Int J Struct Stab Dyn 17(7):1771008
Phoon KK, Huang SP (2007) Uncertainty quantification using multi-dimensional Hermite polynomials. Probab Appl Geotech Eng 1–10
Phoon KK, Ching J (2014) Risk and reliability in geotechnical engineering. CRC Press, Boca Raton
Renani HR, Martin CD (2020) Slope stability analysis using equivalent Mohr-Coulomb and Hoek-Brown criteria. Rock Mech Rock Eng 53(1):13–21
Saada Z, Maghous S, Garnier D (2013) Pseudo-static analysis of tunnel face stability using the generalized Hoek-Brown strength criterion. Int J Numer Anal Meth Geomech 37(18):3194–3212
Sari M, Karpuz C, Ayday C (2010) Estimating rock mass properties using Monte Carlo simulation: Ankara andesites. Comput Geosci 36(7):959–969
Senent S, Mollon G, Jimenez R (2013) Tunnel face stability in heavily fractured rock masses that follow the Hoek-Brown failure criterion. Int J Rock Mech Min Sci 60:440–451
Shen J, Karakus M (2014) Simplified method for estimating the Hoek-Brown constant for intact rocks. J Geotech Geoenviron Eng 140(6):04014025
Shokri S, Shademan M, Rezvani M, Javankhoshdel S, Cami B, Yacoub T (2019) A review study about spatial correlation measurement in rock mass. In: Rock Mechanics for Natural Resources and Infrastructure Development-Full Papers: Proceedings of the 14th International Congress on Rock Mechanics and Rock Engineering, Foz do Iguassu, Brazil. CRC Press
Song KI, Cho GC, Lee SW (2011) Effects of spatially variable weathered rock properties on tunnel behavior. Probab Eng Mech 26(3):413–426
Sow D, Carvajal C, Breul P, Peyras L, Rivard P, Bacconnet C (2017) Modeling the spatial variability of the shear strength of discontinuities of rock masses: application to a dam rock mass. Eng Geol 220:133–143
Su L, Wan HP, Li Y, Ling XZ (2018) Soil-pile-quay wall system with liquefaction-induced lateral spreading: experimental investigation, numerical simulation, and global sensitivity analysis. J Geotech Geoenviron Eng 144(11):04018087
Sun Z, Li J, Pan Q, Dias D, Li S, Hou C (2018) Discrete kinematic mechanism for nonhomogeneous slopes and its application. Int J Geomech 18(12):04018171
Xu J, Wang D (2019) Structural reliability analysis based on polynomial chaos, Voronoi cells and dimension reduction technique. Reliab Eng Syst Saf 185:329–340
Yang XL, Huang F (2011) Collapse mechanism of shallow tunnel based on nonlinear Hoek-Brown failure criterion. Tunn Undergr Space Technol 26(6):686–691
Yang XL, Wang JM (2011) Ground movement prediction for tunnels using simplified procedure. Tunn Undergr Space Technol 26(3):462–471
Yang XL, Yin JH (2004) Slope stability analysis with nonlinear failure criterion. J Eng Mech 130(3):267–273
Yang XL, Yin JH (2010) Slope equivalent Mohr-Coulomb strength parameters for rock masses satisfying the Hoek-Brown criterion. Rock Mech Rock Eng 43(4):505–511
Zeng P, Senent S, Jimenez R (2016) Reliability analysis of circular tunnel face stability obeying Hoek-Brown failure criterion considering different distribution types and correlation structures. J Comput Civ Eng 30(1):04014126
Zhang W, Goh ATC (2012) Reliability assessment on ultimate and serviceability limit states and determination of critical factor of safety for underground rock caverns. Tunn Undergr Space Technol 32:221–230
Acknowledgements
This study was financially supported by National Natural Science Foundation of China (Grant No. 42102321 and Grant No. 52108388), The National Key Research and Development Program of China (Grant No. 2017YFE0119500) and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (Grant No. CUGGC09). The financial funding is greatly appreciated.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix: Work rate equation for face stability analysis
Appendix: Work rate equation for face stability analysis
Let σT denotes the pressure provided by the shield machine to retain tunnel face stability, so its work rate can be calculated by
where Sj0 is the area of the j-th element on tunnel face; Rj0 is the corresponding rotation radius; βj0 is the angle between the rotation radius and the negative direction of the Y-axis.
The work rate done by gravity of rock masses can be calculated as
where γ is the unit weight of rock masses; Vij is the volume of the element determined by local coordinate system; Rij is the corresponding rotation radius; βij is the angle between the rotation radius and the negative direction of the Y-axis.
The internal energy dissipation can be expressed by
where [ct]ij and [φt]ij represent the corresponding equivalent cohesion and internal friction angle of the element; Sij denotes the elementary area on the failure surface and Rij is the corresponding rotation radius.
By equating the internal energy dissipation and external work rate, the required face pressure can be obtained as
where Nγ, Nc are non-dimensional coefficients as
The expressions of [ct]ij and [φt]ij are specified by Eqs. (5) and (6). They are determined by the Hoek–Brown parameters and the stress state of the element of interest. More details for the derivation can be obtained from (Mollon et al. 2011a).
Rights and permissions
About this article
Cite this article
Li, T., Pan, Q., Shen, Z. et al. Probabilistic Stability Analysis of a Tunnel Face in Spatially Random Hoek–Brown Rock Masses with a Multi-Tangent Method. Rock Mech Rock Eng 55, 3545–3561 (2022). https://doi.org/10.1007/s00603-022-02821-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00603-022-02821-y