Skip to main content
SpringerLink
Log in

Calibration method of mesoscopic parameter in sandy cobble soil triaxial test based on PFC3D

  • Research Article
  • Published:
Frontiers of Structural and Civil Engineering Aims and scope Submit manuscript

Abstract

This paper presents a rapid and effective calibration method of mesoscopic parameters of a three-dimensional particle flow code (PFC3D) model for sandy cobble soil. The method is based on a series of numerical tests and takes into account the significant influence of mesoscopic parameters on macroscopic parameters. First, numerical simulations are conducted, with five implementation steps. Then, the multi-factor analysis of variance method is used to analyze the experimental results, the mesoscopic parameters with significant influence on the macroscopic response are singled out, and their linear relations to macroscopic responses are estimated by multiple linear regression. Finally, the parameter calibration problem is transformed into a multi-objective function optimization problem. Numerical simulation results are in good agreement with laboratory results both qualitatively and quantitatively. The results of this study can provide a basis for the calibration of microscopic parameters for the investigation of sandy cobble soil mechanical behavior.

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

Similar content being viewed by others

References

  1. Huang J Z, Xu G U, Wang Y, Ouyang X W. Equivalent deformation modulus of sandy pebble soil—Mathematical derivation and numerical simulation. Mathematical Biosciences and Engineering, 2019, 16(4): 2756–2774

    Article  MathSciNet  PubMed  Google Scholar 

  2. Zhao B Y, Liu D Y, Jiang B. Soil conditioning of waterless sand-pebble stratum in EPB tunnel construction. Geotechnical and Geological Engineering, 2018, 36(4): 2495–2504

    Article  Google Scholar 

  3. Akram M S, Sharrock G B. Physical and numerical investigation of a cemented granular assembly of steel spheres. International Journal for Numerical and Analytical Methods in Geomechanics, 2010, 34(18): 1896–1934

    Article  ADS  Google Scholar 

  4. Bahaaddini M, Hagan P, Mitra R, Hebblewhite B. Numerical study of the mechanical behavior of nonpersistent jointed rock masses. International Journal of Geomechanics, 2016, 16(1): 04015035

    Article  Google Scholar 

  5. Bahaaddini M, Hagan P C, Mitra R, Khosravi M H. Experimental and numerical study of asperity degradation in the direct shear test. Engineering Geology, 2016, 204: 41–52

    Article  Google Scholar 

  6. Bahaaddini M. Effect of boundary condition on the shear behaviour of rock joints in the direct shear test. Rock Mechanics and Rock Engineering, 2017, 50(5): 1141–1155

    Article  ADS  Google Scholar 

  7. Abdoulaye H N, Ouahbi T, Taibi S, Souli H, Marie J, Pantet A. Relationships between the internal erosion parameters and the mechanical properties of granular materials. European Journal of Environmental and Civil Engineering, 2019, 23(11): 1368–1380

    Article  Google Scholar 

  8. Cui Z, Sheng Q, Leng X L, Ma Y L. Investigation of the long-term strength of Jinping marble rocks with experimental and numerical approaches. Bulletin of Engineering Geology and the Environment, 2019, 78(2): 877–882

    Article  Google Scholar 

  9. Di Q G, Li P F, Zhang M J, Cui X P. Influence of relative density on deformation and failure characteristics induced by tunnel face instability in sandy cobble strata. Engineering Failure Analysis, 2022, 141: 106641

    Article  Google Scholar 

  10. Di Q G, Li P F, Zhang M J, Cui X P. Investigation of progressive settlement of sandy cobble strata for shield tunnels with different burial depths. Engineering Failure Analysis, 2022, 141: 106708

    Article  Google Scholar 

  11. Lei H Y, Zhang Y J, Hu Y, Liu Y N. Model test and discrete element method simulation of shield tunneling face stability in transparent clay. Frontiers of Structural and Civil Engineering, 2021, 15(1): 147–166

    Article  Google Scholar 

  12. Zhang X Y, Wang T C, Zhao C Y, Jiang M J, Xu M J, Mei G X. Supporting mechanism of rigid-flexible composition retaining structure in sand ground using discrete element method. Computers and Geotechnics, 2022, 151: 104967

    Article  Google Scholar 

  13. Potyondy D O, Cundall P A. A bonded-particle model for rock. International Journal of Rock Mechanics and Mining Sciences, 2004, 41(8): 1329–1364

    Article  Google Scholar 

  14. Fan X, Yang Z J, Li K H. Effects of the lining structure on mechanical and fracturing behaviors of four-arc shaped tunnels in a jointed rock mass under uniaxial compression. Theoretical and Applied Fracture Mechanics, 2021, 112: 102887

    Article  Google Scholar 

  15. Xu Z H, Wang Z Y, Wang W Y, Lin P, Wu J. An integrated parameter calibration method and sensitivity analysis of microparameters on mechanical behavior of transversely isotropic rocks. Computers and Geotechnics, 2022, 142: 104573

    Article  Google Scholar 

  16. Van M J. Fracture Processes of Concrete. Boca Raton, FL: CRC Press, Inc., 1997

    Google Scholar 

  17. Mier V, Jan G M. Microstructural effects on fracture scaling in concrete, rock and ice. In: IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics. Dordrecht: Springer Netherlands, 2001, 171–182

    Chapter  Google Scholar 

  18. Jensen R P, Bosscher P J, Plesha M E, Edil T B. DEM simulation of granular media–structure interface: Effects of surface roughness and particle shape. International Journal for Numerical and Analytical Methods in Geomechanics, 1999, 23(6): 531–547

    Article  ADS  Google Scholar 

  19. Yang S Q, Huang Y H, Jing H W, Liu X R. Discrete element modeling on fracture coalescence behavior of red sandstone containing two unparallel fissures under uniaxial compression. Engineering Geology, 2014, 178: 28–48

    Article  Google Scholar 

  20. Xia L, Zeng Y W. Parametric study of smooth joint parameters on the mechanical behavior of transversely isotropic rocks and research on calibration method. Computers and Geotechnics, 2018, 98: 1–7

    Article  ADS  Google Scholar 

  21. Zhang Y L, Shao J F, de Saxcé G, Shi C, Liu Z B. Study of deformation and failure in an anisotropic rock with a three-dimensional discrete element model. International Journal of Rock Mechanics and Mining Sciences, 2019, 120: 17–28

    Article  Google Scholar 

  22. Yoon J. Application of experimental design and optimization to PFC model calibration in uniaxial compression simulation. International Journal of Rock Mechanics and Mining Sciences, 2007, 44(6): 871–889

    Article  Google Scholar 

  23. Hanley K J, O’sullivan C, Oliveira J C, Cronin K, Byrne E P. Application of Taguchi methods to DEM calibration of bonded agglomerates. Powder Technology, 2011, 210(3): 230–240

    Article  CAS  Google Scholar 

  24. Chehreghani S, Noaparast M, Rezai B, Ziaedin S. Bonded-particle model calibration using response surface methodology. Particuology, 2017, 32: 141–152

    Article  Google Scholar 

  25. Li K H, Yin Z Y, Cheng Y M, Cao P, Meng J J. Three-dimensional discrete element simulation of indirect tensile behaviour of a transversely isotropic rock. International Journal for Numerical and Analytical Methods in Geomechanics, 2020, 44(13): 1812–1832

    Article  ADS  Google Scholar 

  26. Xu Z H, Wang W Y, Lin P, Xiong Y, Liu Z Y, He S J. A parameter calibration method for PFC simulation: Development and a case study of limestone. Geomechanics and Engineering, 2020, 22(1): 97–108

    CAS  Google Scholar 

  27. Lu Y, Tan Y, Li X, Liu C. Methodology for simulation of irregularly shaped gravel grains and its application to DEM modeling. Journal of Computing in Civil Engineering, 2017, 31(5): 04017023

    Article  Google Scholar 

  28. Cui S W, Tan Y, Lu Y. Algorithm for generation of 3D polyhedrons for simulation of rock particles by DEM and its application to tunneling in boulder-soil matrix. Tunnelling and Underground Space Technology, 2020, 106: 103588

    Article  Google Scholar 

  29. Wu Z Y, Zhang J H, Yu H F, Fang Q, Ma H Y. Specimen size effect on the splitting-tensile behavior of coral aggregate concrete: A 3D mesoscopic study. Engineering Failure Analysis, 2021, 127: 105395

    Article  Google Scholar 

  30. Chen B Y, Yu H F, Zhang J H, Ma H Y, Tian F M. Effects of the embedding of cohesive zone model on the mesoscopic fracture behavior of concrete: A case study of uniaxial tension and compression tests. Engineering Failure Analysis, 2022, 142: 106709

    Article  Google Scholar 

  31. Elices M, Guinea G V, Gomez J, Planas J. The cohesive zone model: Advantages, limitations and challenges. Engineering Fracture Mechanics, 2002, 69(2): 137–163

    Article  Google Scholar 

  32. Shi C, Yang W K, Yang J X, Chen X. Calibration of micro-scaled mechanical parameters of granite based on a bonded-particle model with 2D particle flow code. Granular Matter, 2019, 21(2): 1–13

    Article  ADS  Google Scholar 

  33. Kwok C Y, Bolton M D. DEM simulations of thermally activated creep in soils. Geotechnique, 2010, 60(6): 425–433

    Article  Google Scholar 

  34. Bahrani N, Kaiser P K. Estimation of confined peak strength of crack-damaged rocks. Rock Mechanics and Rock Engineering, 2017, 50(2): 309–326

    Article  ADS  Google Scholar 

  35. Mehranpour M H, Kulatilake P H. Improvements for the smooth joint contact model of the particle flow code and its applications. Computers and Geotechnics, 2017, 87: 163–177

    Article  Google Scholar 

  36. PFC-Particle FLOW Code. Version 5.0. Minnesota: Itasca Consulting Group, Inc., 2014

  37. Zhang Z H, Zhang X D, Tang Y, Cui Y F. Discrete element analysis of a cross-river tunnel under random vibration levels induced by trains operating during the flood season. Journal of Zhejiang University—Science A, 2018, 19(5): 346–366

    Article  ADS  Google Scholar 

  38. Wu L, Zhang X D, Zhang Z H, Sun W C. 3D discrete element method modelling of tunnel construction impact on an adjacent tunnel. KSCE Journal of Civil Engineering, 2020, 24(2): 657–669

    Article  Google Scholar 

  39. Cheng P P, Zhuang X Y, Zhu H H, Li Y H. The construction of equivalent particle element models for conditioned sandy pebble. Applied Sciences, 2019, 9(6): 1137

    Article  Google Scholar 

  40. Huang Z Q, Wang C, Dong J Y, Zhou J J, Yang J H, Li Y W. Conditioning experiment on sand and cobble soil for shield tunneling. Tunnelling and Underground Space Technology, 2019, 87: 187–194

    Article  Google Scholar 

  41. Liu T, Xie Y, Feng Z H, Luo Y B, Wang K, Xu W. Better understanding the failure modes of tunnels excavated in the boulder-cobble mixed strata by distinct element method. Engineering Failure Analysis, 2020, 116: 104712

    Article  Google Scholar 

  42. Lu Y W, Zheng Y, Zuo Y Z. Experimental study on the strength and deformation characteristics of sandy pebble soil foundation based on the equivalent density method. IOP Conference Series. Earth and Environmental Science, 2021, 861(2): 022047

    Google Scholar 

  43. Lu J F, Zhang C W, Jian P. Meso-structure parameters of discrete element method of sand pebble surrounding rock particles in different dense degrees. In: Proceedings of the 7th International Conference on Discrete Element Methods. Singapore: Springer, 2017, 188: 871–879

    Chapter  Google Scholar 

  44. Liang X, Ye F, Ouyang A, Han X, Qin X Z. Theoretical analyses of the stability of excavation face of shield tunnel in Lanzhou metro crossing beneath the Yellow River. International Journal of Geomechanics, 2020, 20(11): 04020200

    Article  Google Scholar 

  45. Lu J F, Li D, Xue X Q, Ling S L. Macro-micromechanical properties of sandy pebble soil of different coarse-grained content. Earth Sciences Research Journal, 2018, 22(1): 65–71

    Article  Google Scholar 

  46. Kroese D P, Chan J C. Statistical Modeling and Computation. New York: Springer, 2014, 306–308

    Book  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China (Grant No. 51978019) and the Beijing Natural Science Foundation (No. 8222004).

Author information

Authors and Affiliations

  1. Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing, 100124, China

    Pengfei Li, Xiaopu Cui & Yingjie Wei

  2. China Railway 14th Bureau Group Co., Ltd., Jinan, 250014, China

    Yingjie Wei

  3. China Railway 19 Bureau Group Rail Traffic Engineering Co., Ltd., Beijing, 101399, China

    Junwei Xia

  4. School of Civil Engineering, Henan Polytechnic University, Jiaozuo, 454000, China

    Xinyu Wang

Authors
  1. Pengfei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaopu Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yingjie Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Junwei Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xinyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xinyu Wang.

Ethics declarations

Conflict of Interests The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, P., Cui, X., Wei, Y. et al. Calibration method of mesoscopic parameter in sandy cobble soil triaxial test based on PFC3D. Front. Struct. Civ. Eng. 17, 1924–1933 (2023). https://doi.org/10.1007/s11709-023-0028-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11709-023-0028-4

Keywords

Search

Navigation