Skip to main content
Log in

Advances in numerical methods for the solution of population balance equations for disperse phase systems

  • Published:
Science in China Series B: Chemistry Aims and scope Submit manuscript

Abstract

Accurate prediction of the evolution of particle size distribution is critical to determining the dynamic flow structure of a disperse phase system. A population balance equation (PBE), a non-linear hyperbolic equation of the number density function, is usually employed to describe the micro-behavior (aggregation, breakage, growth, etc.) of a disperse phase and its effect on particle size distribution. Numerical solution is the only choice in most cases. In this paper, three different numerical methods (direct discretization methods, Monte Carlo methods, and moment methods) for the solution of a PBE are evaluated with regard to their ease of implementation, computational load and numerical accuracy. Special attention is paid to the relatively new and superior moment methods including quadrature method of moments (QMOM), direct quadrature method of moments (DQMOM), modified quadrature method of moments (M-QMOM), adaptive direct quadrature method of moments (ADQMOM), fixed pivot quadrature method of moments (FPQMOM), moving particle ensemble method (MPEM) and local fixed pivot quadrature method of moments (LFPQMOM). The prospects of these methods are discussed in the final section, based on their individual merits and current state of development of the field.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Gu Z L, Su J W, Li Y, Feng S Y, Xu X Y. Behaviors of the disperse phase in the multiphase system and population balance model (in Chinese). Chem React Eng Technol, 2007, 23(2): 162–167

    CAS  Google Scholar 

  2. Hounslow M J, Ryall R L, Marshall V R. A discretized population balance for nucleation, growth, and aggregation. AIChE J, 1988, 34(11): 1821–1832

    Article  CAS  Google Scholar 

  3. Kumar S, Ramkrishna D. On the solution of population balance equations by discretization—i. A fixed pivot technique. Chem Eng Sci, 1996, 51(8): 1311–1332

    Article  CAS  Google Scholar 

  4. Kumar S, Ramkrishna D. On the solution of population balance equations by discretization—ii. A moving pivot technique. Chem Eng Sci, 1996, 51(8): 1333–1342

    Article  CAS  Google Scholar 

  5. Nicmanis M, Hounslow M J. Finite-element methods for steady-state population balance equations. AIChE J, 1998, 44(10): 2258–2272

    Article  CAS  Google Scholar 

  6. Rigopoulos S, Jones A G. Finite-element scheme for solution of dynamic population balance equation. AIChE J, 2003, 49(5): 1127–1139

    Article  CAS  Google Scholar 

  7. Qamar S, Warnecke G. Solving population balance equations for two-component aggregation by a finite volume scheme. Chem Eng Sci, 2007, 62(3): 679–693

    Article  CAS  Google Scholar 

  8. Smith M, Matsoukas T. Constant-number Monte Carlo simulation of population balances. Chem Eng Sci, 1998, 53(9): 1777–1786

    Article  CAS  Google Scholar 

  9. Tandon P, Rosner D E. Monte Carlo simulation of particle aggregation and simultaneous restructuring. J Colloid Interface Sci, 1999, 213(2): 273–286

    Article  CAS  Google Scholar 

  10. Irizarry R. Fast Monte Carlo methodology for multivariate particulate systems-I Point ensemble Monte Carlo. Chem Eng Sci, 2008, 63(1): 95–110

    Article  CAS  Google Scholar 

  11. McGraw R. Description of aerosol dynamics by the quadrature method of moments. Aerosol Sci Tech, 1997, 27(2): 255–265

    Article  CAS  Google Scholar 

  12. Rong F, Marchisio D, Fox R O. Application of the direct quadrature method of moments to polydisperse gas solid fluidized beds. Powder Technol, 2004, 139(1): 7–20

    Article  CAS  Google Scholar 

  13. Su J W, Gu Z L, Li Y, Feng S Y, Xu X Y. Solution of population balance equation using quadrature method of moments with an adjustable factor. Chem Eng Sci, 2007, 62(21): 5897–5911

    Article  CAS  Google Scholar 

  14. Su J W, Gu Z L, Li Y, Feng S Y, Xu X Y. An adaptive direct quadrature method of moment for population balance equation. AIChE J, 2008, 54(11): 2872–2887

    Article  CAS  Google Scholar 

  15. Alopaeus V, LaakkoneN M, Aittamaa J. Numerical solution of moment-transformed population balance equation with fixed quadrature points. Chem Eng Sci, 2006, 61(15): 4919–4929

    Article  CAS  Google Scholar 

  16. Gu Z L, Su J W, Jiao J Y, Xu X Y. Simulation of micro-behaviors including nucleation, growth, aggregation in particle system. Sci China Ser B-Chem, 2008, 52(2): 241–248

    Article  CAS  Google Scholar 

  17. Su J W, Gu Z L, Xu X Y. Solution of the population balance equation for growth using the moving particle ensemble method. AIChE J, 2008, submitted

  18. Su J W, Gu Z L, Jiao J Y, Xu X Y. Local fixed pivot quadrature method of moment for bubble population balance equation including coalescence and breakage. In: 6th International Symposium on Multiphase Flow, Heat Mass Transfer and Energy Conversion Xi’an, China, 11–15 July 2009. In press

  19. Vanni M. Approximate population balance equations for aggregation- breakage processes. J Colloid Interf Sci, 2000, 221(2): 143–160

    Article  CAS  Google Scholar 

  20. Batterham R J, Hall J S, Barton G. Pelletizing kinetics and simulation of full scale balling circuits. In: Proceedings of the Third International Symposium on Agglomeration, Nuremberg, 1981. 136

  21. Kumar J, Peglow M, Warnecke G, Heinrich S, Morl L. Improved accuracy and convergence of discretized population balance for aggregation: The cell average technique. Chem Eng Sci, 2006, 61(10): 3327–3342

    Article  CAS  Google Scholar 

  22. Litster J D, Smit D J, Hounslow M J. Adjustable discretized population balance for growth and aggregation. AIChE J, 1995, 41(3): 591–603

    Article  CAS  Google Scholar 

  23. Liu Y, Cameron I. A new wavelet-based method for the solution of the population balance equation. Chem Eng Sci, 2001, 56(18): 5283–5294

    Article  CAS  Google Scholar 

  24. Fichthom K A, Weinberg W H. Theoretical foundations of dynamical Monte Carlo simulations. J Chem Phys, 1991, 95(2): 1090–1096

    Article  Google Scholar 

  25. Liffman K. A direct simulation Monte-Carlo for cluster coagulation. J Comput Phys, 1992, 100(1): 116–127

    Article  Google Scholar 

  26. Garcia A L. A Monte Carlo simulation of coagulation. Physica, 1987, 143(3): 535–546

    Article  Google Scholar 

  27. Kruis F E, Maisels A, Fissan H. Direct simulation Monte Carlo method for particle coagulation and aggregation. AIChE J, 2000, 46(9): 1735–1742

    Article  CAS  Google Scholar 

  28. Smith M, Matsoukas T. Constant-number Monte Carlo simulation of population balances. Chem Eng Sci, 1998, 53(9): 1777–1786

    Article  CAS  Google Scholar 

  29. Lee K, Matsoukas T. Simultaneous coagulation and break-up using constant-N Monte Carlo. Powder Technol, 2000, 110(1–2): 82–89

    Article  CAS  Google Scholar 

  30. Lin Y, Lee K, Matsoukas T. Solution of the population balance equation using constant-number Monte Carlo. Chem Eng Sci, 2002, 57(12): 2241–2252

    Article  CAS  Google Scholar 

  31. Zhao H B, Zheng C G, Xu M H. Multi-Monte Carlo approach for general dynamic equation considering simultaneous particle coagulation and breakage. Powder Technol, 2005, 154(2–3): 164–178

    CAS  Google Scholar 

  32. Hulburt H M, Katz S. Some problems in particle technology-a statistical mechanical formulation. Chem Eng Sci, 1964, 19(8): 555–574

    Article  CAS  Google Scholar 

  33. Diemer R B, Olson J H. A moment methodology for coagulation and breakage problems: Part 2-moment models and distribution reconstruction. Chem Eng Sci, 2002, 57(12): 2211–2228

    Article  CAS  Google Scholar 

  34. Kruis F E, Kusters K A, Pratsinis S E, Scarlett B. A simple model for the evolution of aggregate particles undergoing coagulation and sintering. Aerosol Sci Technol, 1993, 19(4): 514–526

    Article  CAS  Google Scholar 

  35. Frenklach M, Harris S J. Aerosol dynamics modeling using the method of moments. J Colloid Interf Sci, 1987, 118(1): 252–261

    Article  CAS  Google Scholar 

  36. Lee K W. Change of particle size distribution during Brownian coagulation. J Colloid Interf Sci, 1983, 92(2): 315–325

    Article  CAS  Google Scholar 

  37. Marchisio D L, Vigil R D, Fox R O. Implementation of the quadrature method of moments in CFD codes for aggregation-breakage problems. Chem Eng Sci, 2003, 58(15): 3337–3351

    Article  CAS  Google Scholar 

  38. Prat O P, Ducoste J J. Modeling spatial distribution of floc size in turbulent processes using the quadrature method of moment and computational fluid dynamics. Chem Eng Sci, 2006, 61(1): 75–86

    Article  CAS  Google Scholar 

  39. Marchisio D L, Soos M, Sefcik J, Morbidelli M, Barresi A A, Baldi G. Effect of fluid dynamics on particle size distribution in particulate processes. Chem Eng Technol, 2006, 29(2): 191–199

    Article  CAS  Google Scholar 

  40. Marchisio D L, Soos M, Sefcik J, Morbidelli M. Role of turbulent shear rate distribution in aggregation and breakage processes. AIChE J, 2006, 52(1): 158–173

    Article  CAS  Google Scholar 

  41. Wright D L, McGraw R, Rosnery D E. Bivariate extension of the quadrature method of moments for modeling simultaneous coagulation and sintering of particle populations. J Colloid Interf Sci, 2001, 236(2): 242–251

    Article  CAS  Google Scholar 

  42. Su J W, Gu Z L, Li Y, Feng S Y. Study on quadrature method of moment of volume for population balance model for dispersed phase system (in Chinese). Chem React Eng Technol, 2007, 23(6): 518–524

    Google Scholar 

  43. Marchisio D L, Fox R O. Solution of population balance equations using the direct quadrature method of moments. J Aerosol Sci, 2005, 36(1): 43–73

    Article  CAS  Google Scholar 

  44. Su J W, Gu Z L, Li Y. Direct quadrature method of moment on characteristic volume for population balance equation. J Xi’an Jiaotong U, 2007, 41(5): 621–624

    Google Scholar 

  45. Marchisio D L, Pikturna J T, Fox R O, Vigil R D, Barresi A A. Quadrature method of moments for population-balance equations. AIChE J, 2003, 49(5): 1266–1276

    Article  CAS  Google Scholar 

  46. Gordon R G. Error bounds in equilibrium statistical mechanics. J Math Phys, 1968, 9(5): 655–663

    Article  Google Scholar 

  47. McGraw R, Wright D L. Chemically resolved aerosol dynamics for internal mixtures by the quadrature method of moments. J Aerosol Sci, 2003, 29(2): 189–209

    Article  Google Scholar 

  48. Su J W, Gu Z L, Li Y. Study on direct quadrature method of moment for population balance equation in isotropic particle system. Chem React Eng Technol, 2007, 22(4): 310–316

    Google Scholar 

  49. Golub G H, Vanloan C F. Matrix Computations. 3rd ed. Baltimore: The Johns Hopkins Univ Press, 1996. 183–188

    Google Scholar 

  50. Su J W, Gu Z L, Jiao J Y. Simulation of growth of aerosol particulates using particle travel method. Shanghai. Symposium on the Sixth Annual Meeting of the Chinese Society of Particuology and Seminar on Particle Technology across the Straits (in Chinese), 2008. 641–644

  51. Attarakih M M, Drumm C, Bart H. Solution of the population balance equation using the sectional quadrature method of moments (SQMOM). Chem Eng Sci, 2009, 64(4): 742–752

    Article  CAS  Google Scholar 

  52. McCoy B J, Madras G. Analytical solution for a population balance equation with aggregation and fragmentation. Chem Eng Sci, 2003, 58(13): 3049–3051

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to ZhaoLin Gu.

Additional information

Supported by the National Basic Research Program of China (Grant No. 2004CB720208), the National Natural Science Foundation of China (Grant Nos. 40675011 & 10872159), and the Key Laboratory of Mechanics on Disaster and Environment in Western China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Su, J., Gu, Z. & Xu, X.Y. Advances in numerical methods for the solution of population balance equations for disperse phase systems. Sci. China Ser. B-Chem. 52, 1063–1079 (2009). https://doi.org/10.1007/s11426-009-0164-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11426-009-0164-2

Keywords

Navigation