Soil spatial variability impact on the behavior of a reinforced earth wall

Abstract

This article presents the soil spatial variability effect on the performance of a reinforced earth wall. The serviceability limit state is considered in the analysis. Both cases of isotropic and anisotropic non-normal random fields are implemented for the soil properties. The Karhunen-Loève expansion method is used for the discretization of the random field. Numerical finite difference models are considered as deterministic models. The Monte Carlo simulation technique is used to obtain the deformation response variability of the reinforced soil retaining wall. The influences of the spatial variability response of the geotechnical system in terms of horizontal facing displacement is presented and discussed. The results obtained show that the spatial variability has an important influence on the facing horizontal displacement as well as on the failure probability.

Keywords

reinforced earth wall / geosynthetic / random field / spatial variability / Monte Carlo simulation

References

[1] Griffiths D V, Fenton G A. Bearing capacity of spatially random soil: The undrained clay Prandtl problem revisited. Geotechnique, 2001, 51(4): 351–359

[2] Griffiths D V, Fenton G A, Manoharan N. Bearing capacity of rough rigid strip footing on cohesive soil: Probabilistic study. Journal of Geotechnical and Geoenvironmental Engineering, 2002, 128(9): 743–755

[3] Fenton G A, Griffiths D V. Bearing capacity prediction of spatially random c-ϕ soils. Canadian Geotechnical Journal, 2003, 40(1): 54–65

[4] Popescu R, Deodatis G, Nobahar A. Effect of random heterogeneity of soil properties on bearing capacity. Probabilistic Engineering Mechanics, 2005, 20(4): 324–341

[5] Ahmed A, Soubra A H. Extension of subset simulation approach for uncertainty propagation and global sensitivity analysis. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 2012, 6(3): 162–176

[6] Al-Bittar T, Soubra A H. Bearing capacity of strip footing on spatially random soils using sparse polynomial chaos expansion. International Journal for Numerical and Analytical Methods in Geomechanics, 2013, 37(13): 2039–2060

[7] Gheris A, Hamrouni A. Treatment of an expansive soil using vegetable (DISS) fibre. Innovative Infrastructure Solutions, 2020, 5: 34

[8] Luo N, Bathurst R J, Javankhoshdel S. Probabilistic stability analysis of simple reinforced slopes by finite element method. Computers and Geotechnics, 2016, 77: 45–55

[9] Pan Q, Dias D. An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation. Structural Safety, 2017, 67: 85–95

[10] Pan Q, Dias D. Sliced inverse regression-based sparse polynomial chaos expansion for reliability analysis in high dimensions. Reliability Engineering & System Safety, 2017, 167: 484–493

[11] Hamrouni A, Dias D, Sbartai B. Probabilistic analysis of a piled earth platform under a concrete floor slab. Soils Found, 2017, 57(5): 828–839

[12] Hamrouni A, Dias D, Sbartai B. Reliability analysis of shallow tunnels using the response surface methodology. Underground Space, 2017, 2(4): 246–258

[13] Pan Q, Dias D. Probabilistic analysis of a rock tunnel face using polynomial chaos expansion method. International Journal of Geomechanics, 2018, 18(4): 04018013

[14] Kroetz H, Do N A, Dias D, Beck A T. Reliability of tunnel lining design using the hyperstatic reaction method. Tunnelling and Underground Space Technology, 2018, 77: 59–67

[15] Guo X, Dias D, Carvajal C, Peyras L, Breul P. Reliability analysis of embankment dam sliding stability using the sparse polynomial chaos expansion. Engineering Structures, 2018, 174: 295–307

[16] Hamrouni A, Sbartai B, Dias D. Probabilistic analysis of ultimate seismic bearing capacity of strip foundations. Journal of Rock Mechanics and Geotechnical Engineering, 2018, 10(4): 717–724

[17] Guo X, Dias D, Carvajal C, Peyras L, Breul P. A comparative study of different reliability methods for high dimensional stochastic problems related to earth dam stability analyses. Engineering Structures, 2019, 188: 591–602

[18] Hamrouni A, Dias D, Sbartai B. Probability analysis of shallow circular tunnels in homogeneous soil using the surface response methodology optimized by a genetic algorithm. Tunnelling and Underground Space Technology, 2019, 86: 22–33

[19] Schlosser F, Elias V. Friction in Reinforced Earth. Pittsburgh: A.S.C.E. Convention, 1978, 24–28

[20] Abdelouhab A, Dias D, Freitag N. Numerical analysis of the behavior of mechanically stabilized earth walls reinforced with different types of strips. Geotextiles and Geomembranes, 2011, 29(2): 116–129

[21] Abdelouhab A, Dias D, Freitag N. Two-dimensional numerical modeling of Reinforced Earth walls. European Journal of Environmental and Civil Engineering, 2012, 16(10): 1143–1167

[22] Riccio M, Ehrlich M, Dias D. Field monitoring and analyses of the response of a block-faced geogrid wall using fine-grained tropical soils. Geotextiles and Geomembranes, 2014, 42(2): 127–138

[23] Chun B S, Kim K M, Min D K. A study on reliability analysis for reinforced earth retaining walls. In: The Third Asian Geotechnical Conference on Geosynthetics. Seoul: Millpress Science Publishers, 2004, 248–254

[24] Sayed S, Dodagoudar G R, Rajagopal K. Reliability analysis of reinforced soil walls under static and seismic forces. Geosynthetics International, 2008, 15(4): 246–257

[25] Sayed S, Dodagoudar G R, Rajagopal K. Finite element reliability analysis of reinforced retaining walls. Geomechanics and Geoengineering, 2010, 5(3): 187–197

[26] Miyata Y, Bathurst R J. Reliability analysis of soil-geogrid pullout models in Japan. Soil and Foundation, 2012, 52(4): 620–633

[27] Miyata Y, Bathurst R J, Allen T M. Reliability analysis of geogrid creep data in Japan. Soil and Foundation, 2014, 54(4): 608–620

[28] Miyata Y, Bathurst R J. Reliability-based analysis of combined installation damage and creep for the tensile rupture limit state of geogrid reinforcement in Japan. Soils and Foundations, 2015, 55(2): 437–446

[29] Chalermyanont T, Benson C H. Reliability-based design for internal stability of mechanically stabilized earth walls. Journal of Geotechnical and Geoenvironmental Engineering, 2004, 130(2): 163–173

[30] Sia A H I, Dixon N. Deterministic and reliability-based design: Veneer cover soil stability. Geosynthetics International, 2008, 15(1): 1–13

[31] Thurner R, Schweiger H F. Reliability analysis for geotechnical problems via finite elements—A practical application. In: ISRM International Symposium. Melbourne: International Society for Rock Mechanics and Rock Engineering, 2000, 19–24

[32] Lin B H, Yu Y, Bathurst R J, Liu C N. Deterministic and probabilistic prediction of facing deformations of geosynthetic-reinforced MSE walls using a response surface approach. Geotextiles and Geomembranes, 2016, 44(6): 813–823

[33] Yu Y, Bathurst R J. Probabilistic assessment of reinforced soil wall performance using response surface method. Geosynthetics International, 2017, 24(5): 524–542

[34] Hamrouni A, Dias D, Sbartai B. Reliability analysis of a mechanically stabilized earth wall using the surface response methodology optimized by a genetic algorithm. Geomechanics and Engineering, 2018, 15(4): 937–945

[35] Dodagoudar G, Sayed S, Rajagopal K. Random field modeling of reinforced retaining walls. International Journal of Geotechnical Engineering, 2015, 9(3): 229–238

[36] Ning L, Bathurst R J. Probabilistic analysis of reinforced slopes using RFEM and considering spatial variability of frictional soil properties due to compaction. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 2017, 12(2): 87–108

[37] Griffiths D V, Fenton G A. Probabilistic slope stability analysis by finite elements. Journal of Geotechnical and Geoenvironmental Engineering, 2004, 130(5): 507–518

[38] Gay O. Physical and numerical modeling of the effect of a slow slide on foundations of structures. Dissertation for the Doctoral Degree. Grenoble: Joseph Fourier University, 2000

[39] Flavigny E, Desrues J, Palayer B. Technical note: Hostun RF sand. Revue Française de Géotechnique, 1990, 53: 67–70

[40] Itasca Consulting Group, Inc. FLAC2D–Fast Lagrangian Analysis of Continua in 2 Dimensions. Ver. 7, User’s Manual. Minneapolis: Itasca, 2011

[41] Abdelouhab A, Dias D, Freitag N. Physical and analytical modelling of geosynthetic strip pull-out behaviour. Geotextiles and Geomembranes, 2010, 28(1): 44–53

[42] Der Kiureghian A, Ke J B. The stochastic finite element method in structural reliability. Probabilistic Engineering Mechanics, 1988, 3(2): 83–91

[43] Vu-Bac N, Rafiee R, Zhuang X, Lahmer T, Rabczuk T. Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters. Composites. Part B, Engineering, 2015, 68: 446–464

[44] Vu-Bac N, Lahmer T, Zhuang X, Nguyen-Thoi T, Rabczuk T. A software framework for probabilistic sensitivity analysis for computationally expensive models. Advances in Engineering Software, 2016, 100: 19–31

[45] Spanos P D, Ghanem R. Stochastic finite element expansion for random media. Journal of Engineering Mechanics, 1989, 115(5): 1035–1053

[46] Sahraoui Y, Chateauneuf A. the effects of spatial variability of the aggressiveness of soil on system reliability of corroding underground pipelines. International Journal of Pressure Vessels and Piping, 2016, 146: 188–197

[47] Cho S E. Effect of spatial variability of soil properties on slope stability. Engineering Geology, 2007, 92(3–4): 97–109

[48] Cho S E, Park H C. Effect of spatial variability of cross-correlated soil properties on bearing capacity of strip footing. International Journal for Numerical and Analytical Methods in Geomechanics, 2010, 34: 1–26

[49] Ghanem R G, Spanos P D. Stochastic Finite Elements: A Spectral Approach. New York: Springer, 1991

[50] Sudret B, Berveiller M. Stochastic finite element methods in geotechnical engineering. In: Reliability-based Design in Geotechnical Engineering: Computations and Applications. Oxford: Taylor & Francis, 2008

[51] Shinozuka M, Dasgupta G. Stochastic fields and their digital simulation. In: Stochastic Methods in Structural Dynamics. Boston: Martinus Nijhoff Publishers, 1987, 93–133

[52] Deodatis G. Stochastic FEM sensitivity analysis of nonlinear dynamic problems. Probabilistic Engineering Mechanics, 1989, 4(3): 135–141

[53] Vanmarcke E. Probabilistic modeling of soil profiles. Journal of Geotechnical Engineering, 1977, 103: 1227–1246

[54] Vanmarcke E. Random Fields: Analysis and Synthesis. Cambridge: MIT press, 1983

[55] Popescu R. Stochastic variability of soil properties: Data analysis, digital simulation, effects on system behaviour. Dissertation for the Doctoral Degree. Princeton, NJ: Princeton University, 1995

RIGHTS & PERMISSIONS

2020 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature