Advertisement

Effects of fine particle content and sample scale on the failure properties of loose landslide deposits

  • Bin-rui Gan
  • Xing-guo Yang
  • Ming-liang Chen
  • Jia-wen Zhou
Original Paper
  • 177 Downloads

Abstract

A large amount of loose landslide deposits caused by a strong earthquake can cause several mountain disasters (slope failures, debris flows, and others) under heavy rainfall conditions. Loose landslide deposits are sensitive to water due to their special structural properties, such as loose structure and wide grading. There are complex conformational and mechanical responses of loose deposits, but the initial conditions and formation mechanisms of mountain disasters can be described by several different parameters. Among these parameters, the property of failure is one of the most important, and it is used to describe extremely dangerous situations for each kind of disaster. In this study, a two-dimensional particle flow code platform (PFC2D) was used to simulate the failure properties, and a laboratory test verified the validity of the numerical experiments. Different sample scales (S1, 150 × 300 mm; S2, 300 × 600 mm; S3, 600 × 1200 mm) and fine particle contents smaller than 5 mm (f-1, 20%; f-2, 30%; f-3, 40%) were considered. The simulation results show that failure stress increases with increasing sample scale or fine particle content under low confining pressure and decreases under high confining pressure. The tendency of failure stresses to vary mutates with different fine particle contents when the confining pressure changes. The mutation value of the confining pressure is 280 kPa. In addition, the phenomenon of strain softening becomes less obvious when the confining pressure increases.

Keywords

Landslide deposits Failure properties Discrete element method Sample scale Fine particle content Mutation 

Notes

Acknowledgments

Critical comments by the anonymous reviewers greatly improved the initial manuscript.

Funding information

This work was supported by the National Natural Science Foundation of China (51639007, 41472272) and the Youth Science and Technology Fund of Sichuan Province (2016JQ0011).

References

  1. Chang WJ, Phantachang T (2016) Effects of gravel content on shear resistance of gravelly soils. Eng Geol 207:78–90CrossRefGoogle Scholar
  2. Chen N, Peng C, Wang X, Di B (2004) Testing study on strength reduction of gravelly soil in triggering area of debris flow under earthquake. Chin J Rock Mech Eng 23(16):2743–2747Google Scholar
  3. Chen G, Jin D, Mao J, Gao H, Wang Z, Jing L, Li Y, Li X (2014) Seismic damage and behavior analysis of earth dams during the 2008 Wenchuan earthquake, China. Eng Geol 180:99–129CrossRefGoogle Scholar
  4. Chen HX, Zhang S, Peng M, Zhang LM (2015) A physically-based multi-hazard risk assessment platform for regional rainfall-induced slope failures and debris flows. Eng Geol 203:15–29CrossRefGoogle Scholar
  5. Cook BK, Jensen RP (2002) Discrete element methods: numerical modeling of discontinua. ASCE Press, New MexicoCrossRefGoogle Scholar
  6. Cui Y, Nouri A, Chan D, Rahmati E (2016) A new approach to the DEM simulation of sand production. J Pet Sci Eng 147:56–67CrossRefGoogle Scholar
  7. Cui Y, Chan D, Nouri A (2017) Coupling of solid deformation and pore pressure for undrained deformation—a discrete element method approach. Int J Numer Anal Methods Geomech 41(18):1943–1961CrossRefGoogle Scholar
  8. Cundall PA, Strack ODL (1979) A discrete numerical model for granular assemblies. Géotechnique 29(1):47–65Google Scholar
  9. Eser M, Aydemir C, Ekiz I (2011) Effects of soil structure interaction on strength reduction factors. Proc Eng 14(3):1696–1704CrossRefGoogle Scholar
  10. Galavi V, Schweiger HF (2010) Nonlocal multilaminate model for strain softening analysis. Int J Geomech 10(1):30–44CrossRefGoogle Scholar
  11. Gu CS, Wu HZ, Su HZ (2009) Research on stability of the accumulated rock-soil body of reservoir bank under rainfall condition. Sci China Ser E Technol Sci 52(9):2528–2535CrossRefGoogle Scholar
  12. Gui YL, Bui HH, Kodikara J, Zhang QB, Zhao J, Rabczuk T (2016) Modelling the dynamic failure of brittle rocks using a hybrid continuum-discrete element method with a mixed-mode cohesive fracture model. Int J Impact Eng 87:146–155CrossRefGoogle Scholar
  13. Guo D, Hamada M (2013) Qualitative and quantitative analysis on landslide influential factors during Wenchuan earthquake: a case study in Wenchuan County. Eng Geol 152(1):202–209CrossRefGoogle Scholar
  14. Houlsby GT (2009) Potential particles: a method for modelling non-circular particles in DEM. Comput Geotech 36(6):953–959CrossRefGoogle Scholar
  15. Huang R, Li W (2014) Post-earthquake landsliding and long-term impacts in the Wenchuan earthquake area, China. Eng Geol 182:111–120CrossRefGoogle Scholar
  16. Huang Y, Cheng HL, Osada T, Hosoya A, Zhang F (2015) Mechanical behavior of clean sand at low confining pressure: verification with element and model tests. J Geotech Geoenviron 141(8):06015005CrossRefGoogle Scholar
  17. Jin C, Yang X, You Z (2015) Automated real aggregate modelling approach in discrete element method based on x-ray computed tomography images. Int J Pavement Eng 18:837–850.  https://doi.org/10.1080/10298436.2015.1066006 CrossRefGoogle Scholar
  18. Kulatilake PHSW, Shou G, Huang TH (1995) Spectral-based peak-shear-strength criterion for rock joints. J Geotech Eng 121(11):789–796CrossRefGoogle Scholar
  19. Kulatilake PHSW, Liang J, Gao H (2001) Experimental and numerical simulations of jointed rock block strength under uniaxial loading. J Eng Mech 127(12):1240–1247CrossRefGoogle Scholar
  20. Lai HJ, Zheng JJ, Zhang J, Zhang RJ, Cui L (2014) DEM analysis of “soil”-arching within geogrid-reinforced and unreinforced pile-supported embankments. Comput Geotech 61:13–23CrossRefGoogle Scholar
  21. Laloui L, Cekerevac C (2008) Numerical simulation of the non-isothermal mechanical behaviour of soils. Comput Geotech 35(5):729–745CrossRefGoogle Scholar
  22. Li QM, Mines RAW, Birch RS (2000) The crush behaviour of Rohacell-51WF structural foam. Int J Solids Struct 37(43):6321–6341CrossRefGoogle Scholar
  23. Li DQ, Zhang L, Tang XS, Zhou W, Li JH, Zhou CB, Phoon KK (2015) Bivariate distribution of shear strength parameters using copulas and its impact on geotechnical system reliability. Comput Geotech 68:184–195CrossRefGoogle Scholar
  24. Liu G, Rong G, Peng J, Zhou C (2015) Numerical simulation on undrained triaxial behavior of saturated soil by a fluid coupled-DEM model. Eng Geol 193(4):256–266CrossRefGoogle Scholar
  25. Lu X, Yang Z, Zhang J (2000) The instability analysis of saturated soil under shear load. Int J Non-Linear Mech 35(2):355–360CrossRefGoogle Scholar
  26. Monkul MM, Dacic A (2017) Effect of grain size distribution on stress-strain behavior of lunar soil simulants. Adv Space Res 60(3):636–651CrossRefGoogle Scholar
  27. Motamedi MH, Weed DA, Foster CD (2016) Numerical simulation of mixed mode (I and II) fracture behavior of pre-cracked rock using the strong discontinuity approach. Int J Solids Struct 85–86:44–56CrossRefGoogle Scholar
  28. Peters JF, Muthuswamy M, Wibowo J, Tordesillas A (2005) Characterization of force chains in granular material. Phys Rev E Stat Nonlinear Soft Matter Phys 72(1):041307CrossRefGoogle Scholar
  29. Pucker T, Grabe J (2012) Numerical simulation of the installation process of full displacement piles. Comput Geotech 45(9):93–106CrossRefGoogle Scholar
  30. Salazar A, Sáez E, Pardo G (2015) Modeling the direct shear test of a coarse sand using the 3D discrete element method with a rolling friction model. Comput Geotech 67:83–93CrossRefGoogle Scholar
  31. Shen P, Zhang LM, Chen HX, Gao L (2016) Role of vegetation restoration in mitigating hillslope erosion and debris flows. Eng Geol 216:122–133CrossRefGoogle Scholar
  32. Shi ZM, Wang YQ, Peng M, Chen JF, Yuan J (2015) Characteristics of the landslide dams induced by the 2008 Wenchuan earthquake and dynamic behavior analysis using large-scale shaking table tests. Eng Geol 194:25–37CrossRefGoogle Scholar
  33. Sitharam TG, Nimbkar MS (2000) Micromechanical modelling of granular materials: effect of particle size and gradation. Geotech Geol Eng 18(2):91–117CrossRefGoogle Scholar
  34. Song Y, Huang D, Cen D (2016) Numerical modeling of the 2008 Wenchuan earthquake-triggered daguangbao landslide using a velocity and displacement dependent friction law. Eng Geol 215:50–68CrossRefGoogle Scholar
  35. Su LJ, Xu XQ, Geng XY, Liang SQ (2016) An integrated geophysical approach for investigating hydro-geological characteristics of a debris landslide in the Wenchuan earthquake area. Eng Geol 219:52–63CrossRefGoogle Scholar
  36. Tang XS, Li DQ, Rong G, Phoon KK, Zhou CB (2013) Impact of copula selection on geotechnical reliability under incomplete probability information. Comput Geotech 49(4):264–278CrossRefGoogle Scholar
  37. Vanapalli SK, Fredlund DG, Pufahl DE, Clifton AW (1996) Model for the prediction of shear strength with respect to soil suctio. Can Geotech J 33(3):379–392CrossRefGoogle Scholar
  38. Wada K, Senshu H, Matsui T (2006) Numerical simulation of impact cratering on granular material. Icarus 180(2):528–545CrossRefGoogle Scholar
  39. Wang G, Sassa K, (2003) Pore-pressure generation and movement of rainfall-induced landslides: effects of grain size and fine-particle content. Engineering Geology 69(1-2):109–125CrossRefGoogle Scholar
  40. Wang P, Du J, Feng X, Hu S (2007) Effect of DEM uncertainty on the distributed hydrological model TOPMODEL. IEEE International Conference on Geoscience and Remote Sensing Symposium 1074–1077Google Scholar
  41. Wei M, Wu Z, Zhang L, Chang X (1999) Analyses of process on the strength decrease in frozen soils under high confining pressures. Cold Reg Sci Technol 29(1):1–7CrossRefGoogle Scholar
  42. Yang SQ, Jiang YZ, Xu WY, Chen XQ (2008) Experimental investigation on strength and failure behavior of pre-cracked marble under conventional triaxial compression. Int J Solids Struct 45(17):4796–4819CrossRefGoogle Scholar
  43. Yimsiri S, Soga K (2011) Effects of soil fabric on behaviors of granular soils: microscopic modeling. Comput Geotech 38(7):861–874CrossRefGoogle Scholar
  44. Zhang N, Matsushima T (2016) Simulation of rainfall-induced debris flow considering material entrainment. Eng Geol 214:107–115CrossRefGoogle Scholar
  45. Zhou M, Song E (2016) A random virtual crack dem model for creep behavior of rockfill based on the subcritical crack propagation theory. Acta Geotech 11(4):827–847CrossRefGoogle Scholar
  46. Zhou JW, Cui P, Yang XG, Su ZM, Guo XJ (2013) Debris flows introduced in landslide deposits under rainfall conditions: the case of Wenjiagou gully. J Mt Sci 10(2):249–260CrossRefGoogle Scholar
  47. Zhou JW, Cui P, Yang XG (2016a) Effects of material composition and water content on the mechanical properties of landslide deposits triggered by the Wenchuan earthquake. Acta Geol Sinica (English Edition) 90(1):242–257CrossRefGoogle Scholar
  48. Zhou JW, Xu FG, Guo CX (2016b) Effects of model parameters, topography, and scale on the mass movement processes of debris avalanches using the discrete element method. Arab J Geosci 9(5):418CrossRefGoogle Scholar
  49. Zhou W, Wu W, Ma G, Huang Y, Chang X (2017) Study of the effects of anisotropic consolidation on granular materials under complex stress paths using the DEM. Granul Matter 19:76CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  • Bin-rui Gan
    • 1
  • Xing-guo Yang
    • 2
  • Ming-liang Chen
    • 2
  • Jia-wen Zhou
    • 1
  1. 1.State Key Laboratory of Hydraulics and Mountain River EngineeringSichuan UniversityChengduChina
  2. 2.College of Water Resource and HydropowerSichuan UniversityChengduChina

Personalised recommendations