Skip to main content
SpringerLink
Log in

Research on dynamic characteristics of granular flow based on the material point method

  • Published:
Computational Particle Mechanics Aims and scope Submit manuscript

Abstract

The dynamic characteristics of granular flow is very important to improve the understanding of disaster development. The material point method was used to study the dynamic characteristics of granular flow, and the analytical and experimental examples were used to verify the correctness of the numerical simulation. Numerical result shows that the material point method has high accuracy and resolution when simulating the dam-break problem with discontinuous characteristic. The numerical information provided can be used to study the dynamic characteristics of the granular flow, but the numerical information is not easy to be measured by experiment. The numerical result shows that with the change of Froude number, the granular flow mainly goes through several stages: initial start-up, accelerated development, full development and deceleration deposition. The velocity profile changes from the power function distribution in the initial start-up stage to the linear distribution in the accelerated development stage, and forms a more uniform velocity profile in the full development stage. In the deceleration deposition stage, the velocity approaches zero to complete the final deposition. In different development stages, the lateral pressure coefficient of the section is associated with the motion state, but the lateral pressure coefficient is between the limit active state and the limit passive state obtained by the Savage and Hutter theory (SH theory). Unlike SH theory, which assumes that the lateral pressure coefficient can only be selected from two limit values, the lateral pressure coefficient should be continuously changed, which is reflected in the material point method. For large granular flow moving at high speed, the traditional depth-integrated model is effective because the main motion is in the full development stage. However, for complex granular flow processes, the material point method has wider applicability with fewer assumptions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Chen XZ, Cui YF (2017) The formation of the Wulipo landslide and the resulting debris flow in Dujiangyan City, China. J Mt Sci 14:1100–1112

    Article  Google Scholar 

  2. Köhler A, McElwaine JN, Sovilla B (2018) GEODAR Data and the flow regimes of snow avalanches. J Geophys Res Earth Surf 123:1272–1294

    Article  Google Scholar 

  3. Huang Y, Zhang B (2022) Challenges and perspectives in designing engineering structures against debris-flow disaster. Eur J Environ Civ Eng 26:4476–4497

    Article  Google Scholar 

  4. Duan Z, Cheng WC, Peng JB, Rahman MM, Tang H (2021) Interactions of landslide deposit with terrace sediments: perspectives from velocity of deposit movement and apparent friction angle. Eng Geol 280:105913

    Article  Google Scholar 

  5. Zhang W, Ji J, Gao Y (2020) SPH-based analysis of the post-failure flow behavior for soft and hard interbedded earth slope. Eng Geol 267:105446

    Article  Google Scholar 

  6. Zhang Z, Wang T, Wu S, Tang H, Liang C (2017) The role of seismic triggering in a deep-seated mudstone landslide, China: historical reconstruction and mechanism analysis. Eng Geol 226:122–135

    Article  Google Scholar 

  7. Lu CY, Tang CL, Chan YC, Hu JC, Chi CC (2014) Forecasting landslide hazard by the 3D discrete element method: a case study of the unstable slope in the Lushan hot spring district, central Taiwan. Eng Geol 183:14–30

    Article  Google Scholar 

  8. Luo Y, Zhang Y, Wang Y, He Y, Zhang Y, Cao H (2021) A unique failure model for a landslide induced by the Wenchuan earthquake in the Liujiawan area, Qingchuan County. China Eng Geol 295:106412

    Article  Google Scholar 

  9. Teufelsbauer H, Wang Y, Pudasaini SP, Borja R, Wu W (2011) DEM simulation of impact force exerted by granular flow on rigid structures. Acta Geotech 6:119–133

    Article  Google Scholar 

  10. Zhou GG, Du J, Song D, Choi CE, Hu H, Jiang C (2020) Numerical study of granular debris flow run-up against slit dams by discrete element method. Landslides 17:585–595

    Article  Google Scholar 

  11. Leonardi A, Goodwin G, Pirulli M (2019) The force exerted by granular flows on slit dams. Acta Geotech 14:1949–1963

    Article  Google Scholar 

  12. Zhu C, Huang Y, Sun J (2020) Solid-like and liquid-like granular flows on inclined surfaces under vibration-Implications for earthquake-induced landslides. Comput Geotech 123:103598

    Article  Google Scholar 

  13. Zhou Y, Shi Z, Zhang Q, Liu W, Peng M, Wu C (2019) 3D DEM investigation on the morphology and structure of landslide dams formed by dry granular flows. Eng Geol 258:105151

    Article  Google Scholar 

  14. Gong S, Zhao T, Zhao J, Dai F, Zhou GG (2021) Discrete element analysis of dry granular flow impact on slit dams. Landslides 18:1143–1152

    Article  Google Scholar 

  15. Li P, Shen W, Hou X, Li T (2019) Numerical simulation of the propagation process of a rapid flow-like landslide considering bed entrainment: a case study. Eng Geol 263:105287

    Article  Google Scholar 

  16. Li X, Wu Y, He S, Su L (2016) Application of the material point method to simulate the post-failure runout processes of the Wangjiayan landslide. Eng Geol 212:1–9

    Article  Google Scholar 

  17. Ma Z, Liu J (2022) Dynamic simulation and analysis of large-scale debris flow field. Geofluids 2022:2663551

    Article  Google Scholar 

  18. Yavari-Ramshe S, Ataie-Ashtiani B, Sanders B (2015) A robust finite volume model to simulate granular flows. Comput Geotech 66:96–112

    Article  Google Scholar 

  19. Savage SB, Hutter K (1989) The motion of a finite mass of granular material down a rough incline. J Fluid Mech 199:177–215

    Article  MathSciNet  MATH  Google Scholar 

  20. Yin Y, Xing A, Wang G, Feng Z, Li B, Jiang Y (2017) Experimental and numerical investigations of a catastrophic long-runout landslide in Zhenxiong, Yunnan, southwestern China. Landslides 14:649–659

    Article  Google Scholar 

  21. Yang L, Wei Y, Wang W, Zhu S (2019) Numerical runout modeling analysis of the loess landslide at Yining, Xinjiang. China Water 11:1324

    Article  Google Scholar 

  22. Xia X, Liang Q (2018) A new depth-averaged model for flow-like landslides over complex terrains with curvatures and steep slopes. Eng Geol 234:174–191

    Article  Google Scholar 

  23. Hu YX, Yu ZY, Zhou JW (2020) Numerical simulation of landslide-generated waves during the 11 October 2018 Baige landslide at the Jinsha river. Landslides 17:2317–2328

    Article  Google Scholar 

  24. Rahman MA, Tabassum N, Islam MR (2021) Seismic slope failures: a numerical investigation by the smoothed particle hydrodynamics (SPH). Innovat Infrastruct Solut 6:1–17

    Google Scholar 

  25. Liang D, He X, Zhang JX (2017) An ISPH model for flow-like landslides and interaction with structures. J Hydrodynam, Ser B 29:894–897

    Article  Google Scholar 

  26. Yang E, Bui HH, Nguyen GD, Choi CE, Ng CW, De Sterck H, Bouazza A (2021) Numerical investigation of the mechanism of granular flow impact on rigid control structures. Acta Geotech 16:2505–2527

    Article  Google Scholar 

  27. Nguyen CT, Nguyen CT, Bui HH, Nguyen GD, Fukagawa R (2017) A new SPH-based approach to simulation of granular flows using viscous damping and stress regularisation. Landslides 14:69–81

    Article  Google Scholar 

  28. Li L, Zhai M, Ling X, Chu X, Hu B, Cheng Y (2020) On the location of multiple failure slip surfaces in slope stability problems using the meshless SPH algorithm. Adv Civil Eng. https://doi.org/10.1155/2020/6821548

    Article  Google Scholar 

  29. Zhang X, Chen Z, Liu Y (2016) The material point method—A continuum-based particle method for extreme loading cases. Academic Press

    Google Scholar 

  30. Xu X, Jin F, Sun Q, Soga K, Zhou GG (2019) Three-dimensional material point method modeling of runout behavior of the Hongshiyan landslide. Can Geotech J 56:1318–1337

    Article  Google Scholar 

  31. Li X, Yan Q, Zhao S, Luo Y, Wu Y, Wang D (2020) Investigation of influence of baffles on landslide debris mobility by 3D material point method. Landslides 17:1129–1143

    Article  Google Scholar 

  32. Dunatunga S, Kamrin K (2015) Continuum modelling and simulation of granular flows through their many phases. J Fluid Mech 779:483–513

    Article  MathSciNet  MATH  Google Scholar 

  33. Li X, Tang X, Zhao S, Yan Q, Wu Y (2021) MPM evaluation of the dynamic runout process of the giant Daguangbao landslide. Landslides 18:1509–1518

    Article  Google Scholar 

  34. Shi B, Zhang Y, Zhang W (2019) Run-out of the 2015 shenzhen landslide using the material point method with the softening model. Bull Eng Geol Env 78:1225–1236

    Article  Google Scholar 

  35. Yerro A, Soga K, Bray J (2019) Runout evaluation of Oso landslide with the material point method. Can Geotech J 56:1304–1317

    Article  Google Scholar 

  36. Ying C, Zhang K, Wang ZN, Siddiqua S, Makeen GMH, Wang L (2021) Analysis of the run-out processes of the Xinlu Village landslide using the generalized interpolation material point method. Landslides 18:1519–1529

    Article  Google Scholar 

  37. Soga K, Alonso E, Yerro A, Kumar K, Bandara S (2016) Trends in large-deformation analysis of landslide mass movements with particular emphasis on the material point method. Géotechnique 66:248–273

    Article  Google Scholar 

  38. Wu F, Chen J, Fan Y, Zhang G, Zhao Z, Wang J (2021) Simulation of the flow dynamics of a dry granular flow and force interaction with a rigid wall using the material point method. Comput Partic Mech 9(4):673–692

    Article  Google Scholar 

  39. Bardenhagen SG (2002) Energy conservation error in the material point method for solid mechanics. J Comput Phys 180(1):383–403

    Article  MATH  Google Scholar 

  40. Pirulli M, Mangeney A (2008) Results of back-analysis of the propagation of rock avalanches as a function of the assumed rheology. Rock Mech Rock Eng 41:59–84

    Article  Google Scholar 

  41. Juez C, Murillo J, García-Navarro P (2013) 2D simulation of granular flow over irregular steep slopes using global and local coordinates. J Comput Phys 255:166–204

    Article  MathSciNet  MATH  Google Scholar 

  42. Mangeney A, Heinrich P, Roche R (2000) Analytical solution for testing debris avalanche numerical models. Pure Appl Geophys 157:1081–1096

    Article  Google Scholar 

  43. Huang Y, Zhang B, Zhu CQ (2020) Computational assessment of baffle performance against rapid granular flows. Landslides 18(1):485–501

    Article  Google Scholar 

  44. Jiang YJ, Towhata I (2013) Experimental study of dry granular flow and impact behavior against a rigid retaining wall. Rock Mech Rock Eng 46:713–729

    Article  Google Scholar 

  45. Shen W, Li T, Li P, Guo J (2018) A modified finite difference model for the modeling of flowslides. Landslides 15:1577–1593

    Article  Google Scholar 

  46. Armanini A, Larcher M, Nucci E, Dumbser M (2014) Submerged granular channel flows driven by gravity. Adv Water Resour 63:1–10

    Article  Google Scholar 

  47. Goodwin SR, Choi CE (2021) Translational inertial effects and scaling considerations for coarse granular flows impacting landslide-resisting barriers. J Geotech Geoenviron Eng 147:04021153

    Article  Google Scholar 

  48. Shen WG, Zhao T, Zhao JD, Dai F, Zhou GGD (2018) Quantifying the impact of dry debris flow against a rigid barrier by DEM analyses. Eng Geol 241:86–96

    Article  Google Scholar 

  49. Wang X, Morgenstern NR, Chan DH (2010) A model for geotechnical analysis of flow slides and debris flows. Can Geotech J 47:1401–1414

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the Fundamental Research Funds for the Central Universities of China (Grant No. N2201021), the National Key Research and Development Program of China (Grant No. 2017YFC1503101), the National Natural Science Foundation of China (Grant No. 41201007), and the Research Fund for General Science Project of Department of Education of Liaoning Province (Grant No. L2013103).

Funding

The Funding was provided by the Fundamental Research Funds for the Central Universities of China, (N2201021), Yunyun Fan, the National Key Research and Development Program of China, (2017YFC1503101), Yunyun Fan, the National Natural Science Foundation of China, (41201007), Yunyun Fan, the Research Fund for General Science Project of Department of Education of Liaoning Province, (L2013103), Yunyun Fan

Author information

Authors and Affiliations

  1. School of Resource and Civil Engineering, Northeastern University, Shenyang, 110004, China

    Yunyun Fan & Fuxuan Wang

  2. Shenyang Branch of Lanzhou Engineering and Research Institute of Nonferrous Metallurgy Co., Ltd., Shenyang, 110180, China

    Fang Zhang

Authors
  1. Yunyun Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fuxuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yunyun Fan.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, Y., Wang, F. & Zhang, F. Research on dynamic characteristics of granular flow based on the material point method. Comp. Part. Mech. (2023). https://doi.org/10.1007/s40571-023-00670-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40571-023-00670-2

Keywords

Search

Navigation