Skip to main content
SpringerLink
Log in

Effect of DEM inter-particle parameters on uniaxial loading modeling results

  • Published:
Computational Particle Mechanics Aims and scope Submit manuscript

Abstract

We present a 2D DEM-based model with bonded particles to simulate the uniaxial loading of a porous material. In this paper, we focus on the numerical study of the model parameters at the microscale (normal and tangential stiffnesses of the bonds, bond length, and friction coefficient) influence on the Young modulus and compressive strength of the modeled material. Young’s modulus exhibits linear dependence on the normal stiffness, whereas its dependence on the other parameters is more complex and hard to characterize. We illustrate that compressive strength depends linearly on the normal and tangential stiffness as well as on the bond length but it relates quadratically to the friction coefficient. Additionally, we illustrate that the model is scalable and that Young’s modulus and compressive strength do not depend on the particle size. The provided study allows the construction DEM-based model of porous material with prescribed properties to perform a simulation of uniaxial and triaxial loading of complex heterogeneous materials.

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

Similar content being viewed by others

References

  1. Abdelhamid Y, Shamy UE (2016) Pore-scale modeling of fine-particle migration in granular filters. Int J Geomech 16(3):04015086

    Article  Google Scholar 

  2. Alassi HT, Holt R (2012) Relating discrete element method parameters to rock properties using classical and micropolar elasticity theories. Int J Numer Anal Methods Geomech 36(10):1350–1367

    Article  Google Scholar 

  3. Alkhimenkov Y, Caspari E, Gurevich B, Barbosa ND, Glubokovskikh S, Hunziker J, Quintal B (2020) Frequency-dependent attenuation and dispersion caused by squirt flow: three-dimensional numerical study. Geophysics 85(3):MR129–MR145

    Article  Google Scholar 

  4. Banerjee A, Pasupuleti S, Mondal K, Nezhad MM (2021) Application of data driven machine learning approach for modelling of non-linear filtration through granular porous media. Int J Heat Mass Transf 179:121650

    Article  Google Scholar 

  5. Bao J, Zhang Y, Wu H, Zhou Y, Yue Z (2022) Sintering characteristics, crystal structure and dielectric properties of cobalt-tungsten doped molybdate-based ceramics at microwave frequency. J Materiomics 8(5):949–957

    Article  Google Scholar 

  6. Bazaikin YV, Malkovich EG, Derevschikov VS, Lysikov AI, Okunev AG (2016) Evolution of sorptive and textural properties of CaO-based sorbents during repetitive sorption/regeneration cycles. Chem Eng Sci 152:709–716

    Article  Google Scholar 

  7. Caspari E, Novikov M, Lisitsa V, Barbosa ND, Quintal B, Rubino JG, Holliger K (2019) Attenuation mechanisms in fractured fluid-saturated porous rocks: a numerical modelling study. Geophys Prospect 67(4):935–955

    Article  Google Scholar 

  8. Cundall PA, Strack ODL (1979) A discrete numerical model for granular assemblies. Géotechnique 29(1):47–65

    Article  Google Scholar 

  9. Derevschikov VS, Kazakova ED, Yatsenko DA, Veselovskaya JV (2021) Multiscale study of carbon dioxide chemisorption in the plug flow adsorber of the anesthesia machine. Sep Sci Technol 56(3):485–497

    Article  Google Scholar 

  10. Derevshchikov VS, Kazakova ED (2020) Comparative analysis of the chemical composition and sorption, textural, and strength properties of commercial medical co2 sorbents. Catal Ind 12(1):1–6

    Article  Google Scholar 

  11. Feng GS, Wu SI, Han HI, Ma LW, Jiang WZ, Liu XQ (2011) Sintering characteristics of fluxes and their structure optimization. Int J Miner Metall Mater 18(3):270

    Article  Google Scholar 

  12. Gibou F, Fedkiw R, Osher S (2018) A review of level-set methods and some recent applications. J Comput Phys 353:82–109

    Article  MathSciNet  MATH  Google Scholar 

  13. Hardy S, Finch E (2005) Discrete-element modelling of detachment folding. Basin Res 17(4):507–520

    Article  Google Scholar 

  14. Hardy S, McClayc K, Munozb JA (2009) Deformation and fault activity in space and time in high-resolution numerical models of doubly vergent thrust wedges. Mar Pet Geol 26:232–248

    Article  Google Scholar 

  15. Hazzard JF, Young RP (2000) Simulating acoustic emissions in bonded-particle models of rock. Int J Rock Mech Min Sci 37(5):867–872

    Article  Google Scholar 

  16. Khachkova T, Lisitsa V, Kolyukhin D, Reshetova G (2021) Influence of interfaces roughness on elastic properties of layered media. Probab Eng Mech 66:103170

    Article  Google Scholar 

  17. Lisitsa V, Kolyukhin D, Tcheverda V, Volianskaia V, Priimenko V (2019) GPU-based discrete element modeling of geological faults. In: Voevodin V, Sobolev S (eds) Supercomputing. Springer, Berlin, pp 225–236

    Chapter  Google Scholar 

  18. Mavko G, Mukerji T, Dvorkin J (2009) The rock physics handbook. Cmabridge University Press, New York

    Book  Google Scholar 

  19. Osher S, Fedkiw RP (2001) Level set methods: an overview and some recent results. J Comput Phys 169(2):463–502

    Article  MathSciNet  MATH  Google Scholar 

  20. Peirce A, Detournay E (2008) An implicit level set method for modeling hydraulically driven fractures. Comput Methods Appl Mech Eng 197(33):2858–2885

    Article  MATH  Google Scholar 

  21. Potyondy DO, Cundall PA (2004) A bonded-particle model for rock. Int J Rock Mech Min Sci 41(8):1329–1364

    Article  Google Scholar 

  22. Prokhorov D, Lisitsa V, Khachkova T, Bazaikin Y, Yang Y (2022) Topology-based characterization of chemically-induced pore space changes using reduction of 3d digital images. J Comput Sci 58:101550

    Article  Google Scholar 

  23. Quintal B, Steeb H, Frehner M, Schmalholz SM (2011) Quasi-static finite-element modeling of seismic attenuation and dispersion due to wave-induced fluid flow in poroelastic media. J Geophys Res 116:B01201

    Google Scholar 

  24. Rahimpour MR, Jafari M, Iranshahi D (2013) Progress in catalytic naphtha reforming process: a review. Appl Energy 109:79–93

    Article  Google Scholar 

  25. Shulakova V, Pervukhina M, Muller TM, Lebedev M, Mayo S, Schmid S, Golodoniuc P, Paula OBD, Clennell MB, Gurevich B (2013) Computational elastic up-scaling of sandstone on the basis of x-ray micro-tomographic images. Geophys Prospect 61(2):287–301

    Article  Google Scholar 

  26. Solovyev S, Novikov M, Lisitsa V (2023) A numerical investigation of wave-induced fluid flows in anisotropic fractured porous media. Comput Math Appl 140:78–88. https://doi.org/10.1016/j.camwa.2023.03.013

    Article  MathSciNet  MATH  Google Scholar 

  27. Tavelli M, Chiocchetti S, Romenski E, Gabriel AA, Dumbser M (2020) Space-time adaptive ADER discontinuous Galerkin schemes for nonlinear hyperelasticity with material failure. J Comput Phys 422:109758

    Article  MathSciNet  MATH  Google Scholar 

  28. Vesga LF, Vallejo LE, Lobo-Guerrero S (2008) Dem analysis of the crack propagation in brittle clays under uniaxial compression tests. Int J Numer Anal Methods Geomech 32(11):1405–1415

    Article  MATH  Google Scholar 

  29. Wessling A, Larsson S, Jonsen P, Kajberg J (2022) A statistical dem approach for modelling heterogeneous brittle materials. Comput Particle Mech 9(4):615–631

    Article  Google Scholar 

  30. Yan Z, Wilkinson SK, Stitt EH, Marigo M (2015) Discrete element modelling (dem) input parameters: understanding their impact on model predictions using statistical analysis. Comput Particle Mech 2(3):283–299

    Article  Google Scholar 

  31. Yazykov NA, Dubinin YV, Simonov AD, Reshetnikov SI, Yakovlev VA (2016) Features of sulfur oils catalytic combustion in fluidized bed. Chem Eng J 283:649–655

    Article  Google Scholar 

  32. Zhang W, Dai G, Wang F, Sun S, Bassir H (2007) Using strain energy-based prediction of effective elastic properties in topology optimization of material microstructures. Acta Mech Sin 23(1):77–89

    Article  MathSciNet  MATH  Google Scholar 

  33. Zhao H, Liu C, Zhang J, Ge L (2021) Breakage behavior of gravel rock particles under impact force. Comput Particle Mech 8(5):1075–1087

    Article  Google Scholar 

  34. Zhou YC, Xu BH, Yu AB, Zulli P (2002) An experimental and numerical study of the angle of repose of coarse spheres. Powder Technol 125(1):45–54

    Article  Google Scholar 

Download references

Acknowledgements

The research was supported by the Mathematical Center in Akademgorodok, the agreement with the Ministry of Science and High Education of the Russian Federation number 075-15-2022-281 dated 05.04.2022.

Author information

Authors and Affiliations

  1. Novosibirsk State University, 2 Pirogova St., Novosibirsk, Russia, 630090

    Veronica Chepelenkova

  2. Institute of Mathematics SB RAS, 4 Kptug Ave., Novosibirsk, Russia, 630090

    Vadim Lisitsa

Authors
  1. Veronica Chepelenkova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vadim Lisitsa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vadim Lisitsa.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is 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

Chepelenkova, V., Lisitsa, V. Effect of DEM inter-particle parameters on uniaxial loading modeling results. Comp. Part. Mech. 10, 2021–2030 (2023). https://doi.org/10.1007/s40571-023-00604-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40571-023-00604-y

Keywords

Mathematics Subject Classification

Search

Navigation