Geomechanics and Engineering

  • 제22권1호
  • /
  • Pages.97-108
  • /
  • 2020
  • /
  • 2005-307X(pISSN)
  • /
  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

A parameter calibration method for PFC simulation: Development and a case study of limestone

  • Xu, Z.H. (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Wang, W.Y. (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Lin, P. (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Xiong, Y. (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • Liu, Z.Y. (Geotechnical and Structural Engineering Research Center, Shandong University) ;
  • He, S.J. (Geotechnical and Structural Engineering Research Center, Shandong University)
  • 투고 : 2020.04.08
  • 심사 : 2020.06.01
  • 발행 : 2020.07.10
⟨ 이전 논문 다음 논문 ⟩

초록

The time-consuming and less objectivity are the main problems of conventional micromechanical parameters calibration method of Particle Flow Code simulations. Thus this study aims to address these two limitation of the conventional "trial-and-error" method. A new calibration method for the linear parallel bond model (CM-LPBM) is proposed. First, numerical simulations are conducted based on the results of the uniaxial compression tests on limestone. The macroscopic response of the numerical model agrees well with the results of the uniaxial compression tests. To reduce the number of the independent micromechanical parameters, numerical simulations are then carried out. Based on the results of the orthogonal experiments and the multi-factor variance analysis, main micromechanical parameters affecting the macro parameters of rocks are proposed. The macro-micro parameter functions are ultimately established using multiple linear regression, and the iteration correction formulas of the micromechanical parameters are obtained. To further verify the validity of the proposed method, a case study is carried out. The error between the macro mechanical response and the numerical results is less than 5%. Hence the calibration method, i.e., the CM-LPBM, is reliable for obtaining the micromechanical parameters quickly and accurately, providing reference for the calibration of micromechanical parameters.

키워드

과제정보

The research described in this paper was financially supported by the National Natural Science Foundation of China (Grant No.: 51879153), the Natural Science Foundation of Shanodng Province (Grant No.: ZR201808080053) and the China Postdoctoral Science Foundation (Grant No.: 2019M662361).

참고문헌

  1. Ajamzadeh, M.R., Sarfarazi, V., Haeri, H. and Dehghani, H. (2018), "The effect of micro parameters of PFC software on the model calibration", Smart Struct. Syst., 22(6), 643-662. https://doi.org/10.12989/sss.2018.22.6.643.
  2. Bahaaddini, M., Hagan, P., Mitra, R. and Hebblewhite, B.K. (2016), "Numerical study of the mechanical behavior of nonpersistent jointed rock masses", Int. J. Geomech., 16(1), 1-10. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000510.
  3. Bahaaddini, M., Sharrock, G. and Hebblewhite, B.K. (2013), "Numerical direct shear tests to model the shear behaviour of rock joints", Comput. Geotech., 51, 101-115, https://doi.org/10.1016/j.compgeo.2013.02.003.
  4. Bahrani, N. and Kaiser, P.K. (2017), "Estimation of confined peak strength of crack-damaged rocks", Rock Mech. Rock Eng., 50(2), 309-326. https://doi.org/10.1007/s00603-016-1110-1.
  5. Bock, S. and Prusek, S. (2015), "Numerical study of pressure on dams in a backfilled mining shaft based on PFC3D code", Comput. Geotech., 66, 230-244. https://doi.org/10.1016/j.compgeo.2015.02.005.
  6. Chen, Q., Zhang, C., Yang, C., Ma, C. and Pan, Z. (2019), "Effect of fine-grained dipping interlayers on mechanical behavior of tailings using discrete element method", Eng. Anal. Boundary Elem., 104, 288-299. https://doi.org/10.1016/j.enganabound.2019.03.029.
  7. Cundall, P.A. and Strack, O.D.L. (1979), "Discrete numerical model for granular assemblies", Geotechnique, 29(1), 41-65. https://doi.org/10.1680/geot.1979.29.1.47.
  8. De Silva, V.R.S. and Ranjith, P.G. (2020), "A study of rock joint influence on rock fracturing using a static fracture stimulation method", J. Mech. Phys. Solids, 137, 21. https://doi.org/10.1016/j.jmps.2019.103817.
  9. Gracia, F., Villard, P. and Richefeu, V. (2019), "Comparison of two numerical approaches (DEM and MPM) applied to unsteady flow", Comput. Particle Mech., 6(4), 591-609. https://doi.org/10.1007/s40571-019-00236-1.
  10. Guo, W.B., Hu, B., Cheng, J.L. and Wang, B.F. (2020), "Modeling time-dependent behavior of hard sandstone using the DEM method", Geomech. Eng., 20(6), 517-525. https://doi.org/10.12989/gae.2020.20.6.517.
  11. Haeri, H., Sarfarazi, V., Zhu, Z.M. and Moosavi, E. (2019), "Effect of transversely bedding layer on the biaxial failure mechanism of brittle materials", Struct. Eng. Mech., 69(1), 11-20. https://doi.org/10.12989/sem.2019.69.1.011.
  12. Haeri, H., Sarfarazi, V., Zhu, Z.M. and Nejati, H.R. (2019), "Numerical simulations of fracture shear test in anisotropy rocks with bedding layers", Adv. Concrete Construct., 7(4), 241-247. https://doi.org/10.12989/acc.2019.7.4.241.
  13. Hasanpour, R., Ozcelik, Y., Yilmazkaya, E. and Sohrabian, B. (2016), "DEM modeling of a monowire cutting system", Arab. J. Geosci., 9(20), 11. https://doi.org/10.1007/s12517-016-2710-5.
  14. Hashemi, S.S., Momeni, A.A. and Melkoumian, N. (2014), "Investigation of borehole stability in poorly cemented granular formations by discrete element method", J. Petrol. Sci. Eng., 113, 23-35. https://doi.org/10.1016/j.petrol.2013.11.031.
  15. Hofmann, H., Babadagli, T., Yoon, J.S., Blocher, G. and Zimmermann, G. (2016), "A hybrid discrete/finite element modeling study of complex hydraulic fracture development for enhanced geothermal systems (EGS) in granitic basements", Geothermics, 64, 362-381. https://doi.org/10.1016/j.geothermics.2016.06.016.
  16. Jafri, T.H. and Yoo, H. (2018), "REV application in DEM analysis of non-vibrational rock splitting method to propose feasible borehole spacing", Appl. Sci., 8(3), 17, https://doi.org/10.3390/app8030335.
  17. Khazaei, C., Hazzard, J. and Chalaturnyk, R. (2015), "Damage quantification of intact rocks using acoustic emission energies recorded during uniaxial compression test and discrete element modeling", Comput. Geotech., 67, 94-102. https://doi.org/10.1016/j.compgeo.2015.02.012.
  18. Kwok, Y. and Bolton, M.D. (2010), "DEM simulations of thermally activated creep in soils", Geotechnique, 60(6), 425-433. https://doi.org/10.1680/geot.2010.60.6.425.
  19. Lin, P., Li, S.C., Xu, Z.H., Wang, J. and Huang, X. (2019), "Water inflow prediction during heavy rain while tunneling through Karst fissured zones", Int. J. Geomech., 19(8), 04019093. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001478.
  20. Lotidis, M.A., Nomikos, P.P. and Sofianos, A.I. (2019), "Numerical study of the fracturing process in marble and plaster hollow plate specimens subjected to uniaxial compression", Rock Mech. Rock Eng., 52(11), 4361-4386. https://doi.org/10.1007/s00603-019-01884-8.
  21. Manouchehrian, A., Sharifzadeh, M., Marji, M.F. and Gholamnejad, J. (2014), "A bonded particle model for analysis of the flaw orientation effect on crack propagation mechanism in brittle materials under compression", Arch. Civ. Mech. Eng., 14(1), 40-52. https://doi.org/10.1016/j.acme.2013.05.008.
  22. Mehranpour, M.H., Kulatilake, P., Ma, X.G. and He, M.C. (2018), "Development of new three-dimensional rock mass strength criteria", Rock Mech. Rock Eng., 51(11), 3537-3561. https://doi.org/10.1007/s00603-018-1538-6.
  23. Meidani, M., Meguid, M.A. and Chouinard, L.E. (2018), "Estimating earth loads on buried pipes under axial loading condition: Insights from 3D discrete element analysis", Int. J. Geo-Eng., 9(1), 5. https://doi.org/10.1186/s40703-018-0073-3.
  24. Potyondy, D. (2018), "Material-Modeling Support in PFC [fistPkg26]", Itasca Consulting Group, Inc., Minneapolis, Minnesota, U.S.A.
  25. Potyondy, D.O. and Cundall, P.A. (2004), "A bonded-particle model for rock", Int. J. Rock Mech. Min. Sci., 41(8), 1329-1364. https://doi.org/10.1016/j.ijrmms.2004.09.011.
  26. Poulsen, B.A., Adhikary, D. and Guo, H. (2018), "Simulating mining-induced strata permeability changes", Eng. Geol., 237, 208-216. https://doi.org/10.1016/j.enggeo.2018.03.001.
  27. Sarfarazi, V., Haeri, H., Shemirani, A.B., Zhu, Z.M. and Marji, M.F. (2018), "Experimental and numerical simulating of the crack separation on the tensile strength of concrete", Struct. Eng. Mech., 66(5), 569-582. https://doi.org/10.12989/sem.2018.66.5.569.
  28. Shemirani, A.B., Haeri, H., Sarfarazi, V., Akbarpour, A. and Babanouri, N. (2018), "The discrete element method simulation and experimental study of determining the mode I stress-intensity factor", Struct. Eng. Mech., 66(3), 379-386. https://doi.org/10.12989/sem.2018.66.3.379.
  29. Shi, C., Yang, W., Yang, J. and Chen, X. (2019), "Calibration of micro-scaled mechanical parameters of granite based on a bonded-particle model with 2D particle flow code", Granul. Matter, 21(2), 38. https://doi.org/10.1007/s10035-019-0889-3.
  30. Wu, X.J. (2017), "Study on mechanism of seepage and water-inrush from filled Karst conduit in tunnel", China University of Mining and Technology, Beijing, China.
  31. Xu, Z.H., Huang, X., Li, S.C., Lin, P., Shi, X.S. and Wu, J. (2020a), "A new slice-based method for calculating the minimum safe thickness for a filled-type karst cave", Bull. Eng. Geol. Environ., 79(2), 1097-1111. https://10.1007/s10064-019-01609-9.
  32. Xu, Z.H., Lin, P., Xing, H.L. and Wang, J. (2020b), "Mathematical modeling of cumulative erosion ratio for suffusion in soils", Proc. Inst. Civ. Eng. Geotech. Eng., 1-11. https://doi.org/10.1680/jgeen.19.00082.
  33. Xu, Z.H., Wang, W.Y., Lin, P., Wang, X.T. and Yu, T.F. (2020c), "Buffering effect of overlying sand layer technology for dealing with rockfall disaster in tunnels and a case study", Int. J. Geomech., 20(8), 04020127. https://10.1061/(ASCE)GM.1943-5622.0001751.
  34. Yang, B., Yue, J. and Lei, S. (2006), "A study on the effects of microparameters on macroproperties for specimens created by bonded particles", Eng. Comput., 23(6), 607-631. https://doi.org/10.1108/02644400610680333.
  35. Zhou, Y., Wu, S., Jiao, J. and Zhang, X. (2011), "Research on mesomechanical parameters of rock and soil mass based on BP neural network", Rock Soil Mech., 32(12), 3821-3826. https://doi.org/10.16285/j.rsm.2011.12.010.

피인용 문헌

  1. Failure characteristics and mechanical mechanism of study on red sandstone with combined defects vol.24, pp.2, 2021, https://doi.org/10.12989/gae.2021.24.2.179