A stochastic technique for multidimensional granulation modeling

AIChE Journal

Volumn 52, Issue 9, 2006, Pages 3067-3077

  Gantt, Justin A ^a   Gatzke, Edward P ^a  

^a The Department of Mechanical Engineering   (United States)

Author keywords

Coalescence kernel; Discrete element method; Kinetic Monte Carlo; Population balance

Indexed keywords

COALESCENCE KERNEL; GRANULATION MODELING; POPULATION BALANCE EQUATION (PBE);

COALESCENCE; COMPUTER SIMULATION; FINITE DIFFERENCE METHOD; MIXING; MONTE CARLO METHODS; REACTION KINETICS;

GRANULATION;

COALESCENCE; COMPUTER SIMULATION; FINITE DIFFERENCE METHOD; GRANULATION; MIXING; MONTE CARLO METHODS; REACTION KINETICS;

EID: 33748534200     PISSN: 00011541     EISSN: 15475905     Source Type: Journal    
DOI: 10.1002/aic.10911     Document Type: Article

References (33)

1. Iveson, SM. Limitations of one-dimensional population balance models of wet granulation processes. Powder Technol. 2002;124:219-229.
2. Kapur PC, Fuerstenau DW. Coalescence model for granulation. Ind and Eng Chem Proc Design Devices. 1969;8:56-62.
3. Sastry KVS. Similarity size distribution of agglomerates during their growth by coalescence in granulation or green pelletization. Intl J of Mineral Processing. 1975;2:187-203.
4. Adetayo AA, Ennis BJ. A unifying approach to modeling coalescence mechanisms. AlChE. 1997;43(1):927-934.
5. Iveson SM. Beathe JA, Page NW. The dynamic strength of partially saturated powder compacts: the effect of liquid properties. Powder Technol. 2002;127:149-161.
6. Liu LX. Litster JD. Coalescence of deformable granules in wet granulation processes. AICHE J. 2000;46(3):529-539.
7. Liu LX, Litster JD, Iveson SM. Ennis BJ. Coalescence of deformable granules in wet granulation processes. AIChE J. 2000;46(3):529-539.
8. Liu LX, Litster JD. Population balance modeling of granulation with a physically based coalescence kernel. Chem Eng Sci. 2002;57:2183-2191.
9. Tsuji T, Kawaguchi T, Tanaka T. Discrete particle simulation of two-dimensional fluidized bed. Powder Technol. 1993;77:79-87.
10. Muguruma Y, Tanaka T, Tsuji Y. Numerical simulation of particulate flow with liquid bridge between particles (simulation of centrifugal tumbling granulator). Powder Technol. 2000;109:49-57.
11. Cundall PA. Strack ODL. A discrete numerical model for granular assemblies. Ceotechnique. 1979;29:47-65.
12. Gantt JA. Cameron IT, Litster JD, Gatzke EP. Determination of coalescence kernels for high shear granulation using dem simulations; 2005.
13. Goldshmidt M. Hydrodynamic Modelling of Fluidized Bed Granulation. Twente University, 2001. PhD thesis.
14. Tan H, Goldschmidt M, Boerefijn R, Hounslow M, Salman A, Kuipers J. Building population balances for fluidized bed granulation: lessons from kinetic theory of granular flow. Powder Technol. 2004;142(30): 103-109.
15. Verkoeijen D, Pouw GA, Meesters GMH, Scarlett B. Population balances for paniculate processes-a volume approach. Chem Eng Sci. 2002;57:2287-2303.
16. Wauters P, Modeling and mechanisms of granulation. Delft University of Technology, Delft, The Netherlands; 2001, PhD thesis.
17. Ingram GD. Multiscale Modeling and Analysis of Process Systems. University of Queensland, St. Lucia, Queensland, AU; 2006. PhD thesis.
18. Diemer R, Olson J. A moment methodology for coagulation and breakage problems: Part 1 - analytical solution of the steady state population balance. Chem Eng Sci. 2002;57:1735-1742.
19. Hounslow MJ, Ryall RL, Marshall VR. A discretized population balance for nucleation, growth and aggregation. AIChE J. 1988;34(11):1821-1832.
20. Daralius A, Brage H, Rasmusson A, Bjorn I, Folestad S. A volume-based multidimensional population balance approach for modelling high shear granulation. Chem Eng Sci. 2006;61:2482-2493.
21. Das P. Monte carlo simulation of drop breakage on the basis of drop volume. Comp and Chem Eng. 1995;20(3):307-313.
22. Goodson M, Kraft M, Forrest S, Bridgewater J. A multi-dimensional population balance model for agglomeration. In PARTEC; 2004.
23. Smith M, Matsoukas T. Constant-number monte carlo simulation population balances. Chem Eng Sci. 1998;53(9):1777-1786.
24. Lee K, Matsoukas T. Simultaneous coagulation and break-up using constant-n monte carlo. Powder Technol. 2000;110:82-89.
25. Kostoglou M, Konstandolopoulos A. Evolution of aggregate size and fractal dimension during brownian coagulation. J of Aerosol Sci. 2001;32:1399-1420.
26. Lin Y, Lee K, Matsoukas T. Solution of the population balance equation using constant-number monte carlo. Chem Eng Sci. 2002;57: 2241-2252.
27. Iveson S, Litster J, Ennis B. Fundamental studies of granule consolidation, part 1: effects of binder content and binder viscosity. Powder Technol. 1996;88:15-20.
28. Iveson SM, Litster JD, Hapgood K, Ennis BJ. Nucleation, growth and breakage phenomena in agitated wet granulation process: a review. Powder Technol. 2001;117:3-39.
29. Nilpawar A, Reynolds G, Salman A, Hounslow M. Kinematics in high shear granulation. In Proceedings: The 8th International Symposium on Agglomeration, 447 Sri Ayudhaya rd. Bangkok, Thailand, 2005. The Industrial Pharmacists Group.
30. Rubinstein RY. Optimization of computer simulation models with rare events. Euro J of Operational Res. 1997;99:89-112.
31. Sanders C, Willemse A, Salman A, Hounslow M. Development of a predictive high shear granulation model. Powder Technol. 2003;138: 18-24.
32. Mangwandi C, Fu J, Reynolds G, Adams M, Hounslow M, Salman A. Impact behavior of different types of granules. In 8th International Symposium on Agglomeration, Sri Ayudhaya rd, Bangkok, Thailand, The Industrial Pharmacists Group. 2005; p 11-21: 447.
33. Adetayo AA, Ennis BJ. A new approach to modeling granulation processes for simulation and control purposes. Powder Technol. 2000; 108:202-209.