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Quantitative Simulation on Powder Shear Flow Using Discrete Element Method

  • Yijie Gao
Original Article

Abstract

Purpose

In the pharmaceutical industry, a deep understanding on the physical properties of drug substance (DS) and excipients, such as the powder flowability and compressibility, is critical for the quality control of solid dose drug product (DP). The purpose of this work is to develop a quantitative simulation method to model powder flow by applying the discrete element method (DEM) simulation on the ring shear testing process.

Methods

A commercially available software Star CCM+ v10.2 by Siemens (New York, NY, USA) was applied as the DEM simulation software. A workstation with Dual CPUs Intel® Xeon® E5-2640 @ 2.50 GHz (24 processors) was applied as the simulation hardware. The Hertz-Mindlin non-slip contact model was applied for particle-particle and particle-wall interactions. The Johnson-Kendall-Roberts (JKR) model was applied to model the cohesion between particles. Original data of powder flowability was measured using the Ring Shear Tester RST-XS by Jenike & Johanson, Inc. (Tyngsborough, MA, USA).

Results

The sliding friction coefficient and the work of cohesion were determined as influential parameters on the flowability of DEM particles in the scope of this study. Correlation was established between DEM parameter setting and shear flow behavior of bulk DEM particles by applying multiple linear regression and was verified by comparing simulation with shear flow data of common pharmaceutical excipients.

Conclusions

This method is recommended for general formulation and manufacture development of solid dose DP.

Keywords

Discrete element method Shear flow Particle technology 

Notes

Acknowledgements

This work is supported by the Formulation Development group of Takeda-Boston. The author would like to thank Willow DiLuzio, Frederick Hicks, Hirohisa Takeuchi, Yoshinobu Sato, and Marianne Langston for their assistance, and Siemens PLM for providing the simulation software.

References

  1. 1.
    Kruggel-Emden H, Simsek E, Rickelt S, Wirtz S, Scherer V. Review and extension of normal force models for the discrete element method. Powder Technol. 2007;171(3):157–73.CrossRefGoogle Scholar
  2. 2.
    Luding S. Cohesive, frictional powders: contact models for tension. Granul Matter. 2008;10(4):235–46.CrossRefGoogle Scholar
  3. 3.
    Luding S. Contact Models for very loose granular materials. In: Eberhard P, editor. IUTAM Symposium on Multiscale Problems in Multibody System Contacts: Proceedings of the IUTAM Symposium held in Stuttgart, Germany, February 20–23, 2006. Netherlands: Dordrecht: Springer; 2007. p. 135–50.CrossRefGoogle Scholar
  4. 4.
    Ketterhagen WR, am Ende MT, Hancock BC. Process modeling in the pharmaceutical industry using the discrete element method. J Pharm Sci. 2009;98(2):442–70.CrossRefPubMedGoogle Scholar
  5. 5.
    Schwedes J. Review on testers for measuring flow properties of bulk solids. Granul Matter. 2003;5(1):1–43.CrossRefGoogle Scholar
  6. 6.
    JenikeAW. Storage and flow of solids, bulletin no. 123. Bulletin of the University of Utah. 1964;53(26).Google Scholar
  7. 7.
    Schulze D. Shear testing of powders for process optimization. Ann Trans Nordic Rheology Soc. 2013;21:99–106.Google Scholar
  8. 8.
    Schulze D. Flow properties of powders and bulk solids. Braunschweig/Wolfenbu ttel: University of Applied Sciences; 2006.Google Scholar
  9. 9.
    Freeman R. Measuring the flow properties of consolidated, conditioned and aerated powders—a comparative study using a powder rheometer and a rotational shear cell. Powder Technol. 2007;174(1–2):25–33.CrossRefGoogle Scholar
  10. 10.
    Asadzadeh M, Soroush A. Fundamental investigation of constant stress simple shear test using DEM. Powder Technol. 2016;292:129–39.CrossRefGoogle Scholar
  11. 11.
    Lätzel M, Luding S, Herrmann HJ, Howell DW, Behringer RP. Comparing simulation and experiment of a 2D granular couette shear device. Eur Phys J E. 2003;11(4):325–33.CrossRefPubMedGoogle Scholar
  12. 12.
    Luding S. Shear flow modeling of cohesive and frictional fine powder. Powder Technol. 2005;158(1–3):45–50.CrossRefGoogle Scholar
  13. 13.
    Bharadwaj R, Ketterhagen WR, Hancock BC. Discrete element simulation study of a Freeman powder rheometer. Chem Eng Sci. 2010;65(21):5747–56.CrossRefGoogle Scholar
  14. 14.
    Jerier JF, Molinari JF. Normal contact between rough surfaces by the discrete element method. Tribol Int. 2012;47:1–8.CrossRefGoogle Scholar
  15. 15.
    AignerA, SchneiderbauerS, KlossC, PirkerS. Determining the coefficient of friction by shear tester simulation. 3rd International Conference on Particle-Based Methods; 2013; 2013. p. 335–42.Google Scholar
  16. 16.
    Rozbroj J, Zegzulka J, Nečas J. Use of DEM in the determination of friction parameters on a physical comparative model of a vertical screw conveyor. Chem Biochem Eng Q. 2015;29(1):25–34.CrossRefGoogle Scholar
  17. 17.
    Ai J, Chen J-F, Rotter JM, Ooi JY. Assessment of rolling resistance models in discrete element simulations. Powder Technol. 2011;206(3):269–82.CrossRefGoogle Scholar
  18. 18.
    Persson A-S, Frenning G. The influence of rolling friction on the shear behaviour of non-cohesive pharmaceutical granules—an experimental and numerical investigation. Eur J Pharm Sci. 2013;49(2):241–50.CrossRefPubMedGoogle Scholar
  19. 19.
    Iwashita K, Oda M. Rolling resistance at contacts in simulation of shear band development by DEM. J Eng Mech. 1998;124(3):285–92.CrossRefGoogle Scholar
  20. 20.
    Bartels G, Unger T, Kadau D, Wolf ED, Kertész J. The effect of contact torques on porosity of cohesive powders. Granul Matter. 2005;7(2):139–43.CrossRefGoogle Scholar
  21. 21.
    Ketterhagen WR, Bharadwaj R, Hancock BC. The coefficient of rolling resistance (CoRR) of some pharmaceutical tablets. International Journal of Pharmaceutics. 2010;392(1–2):107–10.CrossRefPubMedGoogle Scholar
  22. 22.
    Zhao C, Li C. Influence of rolling resistance on the shear curve of granular particles. Phys A: Stat Mech Appl. 2016;460:44–53.CrossRefGoogle Scholar
  23. 23.
    Wang X, Li J. Simulation of triaxial response of granular materials by modified DEM. Sci China Phys, Mech Astron. 2014;57(12):2297–308.CrossRefGoogle Scholar
  24. 24.
    Ma G, Zhou W, Chang X-L, Ng T-T, Yang L-F. Formation of shear bands in crushable and irregularly shaped granular materials and the associated microstructural evolution. Powder Technol. 2016;301:118–30.CrossRefGoogle Scholar
  25. 25.
    Yang Y, Wang JF, Cheng YM. Quantified evaluation of particle shape effects from micro-to-macro scales for non-convex grains. Particuology. 2016;25:23–35.CrossRefGoogle Scholar
  26. 26.
    Simons TAH, Weiler R, Strege S, Bensmann S, Schilling M, Kwade A. A ring shear tester as calibration experiment for DEM simulations in agitated mixers—a sensitivity study. Procedia Engineering. 2015;102:741–8.CrossRefGoogle Scholar
  27. 27.
    Alizadeh E, Bertrand F, Chaouki J. Comparison of DEM results and Lagrangian experimental data for the flow and mixing of granules in a rotating drum. AICHE J. 2014;60:60–75.CrossRefGoogle Scholar
  28. 28.
    Mindlin R. Compliance of elastic bodies in contact. J Appl Mech. 1949;16Google Scholar
  29. 29.
    Zhou YC, Wright BD, Yang RY, Xu BH, Yu AB. Rolling friction in the dynamic simulation of sandpile formation. Phys A: Stat Mech Appl. 1999;269(2–4):536–53.CrossRefGoogle Scholar
  30. 30.
    GrafK, Kappl M. Physics and chemistry of interfaces: John Wiley & Sons2006.Google Scholar
  31. 31.
    JohnsonKL, JohnsonKL. Contact mechanics: Cambridge university press 1987.Google Scholar
  32. 32.
    Mishra BK, Rajamani RK. The discrete element method for the simulation of ball mills. Applied Mathematical Modelling. 1992;16(11):598–604.CrossRefGoogle Scholar
  33. 33.
    Li Y, Xu Y, Thornton C. A comparison of discrete element simulations and experiments for ‘sandpiles’ composed of spherical particles. Powder Technol. 2005;160(3):219–28.CrossRefGoogle Scholar
  34. 34.
    Derekshani S, Schott D, Lodewijks G. Reducing computation time of DEM simulations of fine granular materials. Bulk Solids Handling. 2013;6:52–6.Google Scholar
  35. 35.
    Remy B, Khinast JG, Glasser BJ. Discrete element simulation of free flowing grains in a four-bladed mixer. AICHE J. 2009;55(8):2035–48.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Takeda Pharmaceuticals International Co.CambridgeUSA

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