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[1] Jounela, A.J., Pentikainen, P.J. & Sothmann, A., Effect of particle size on the bioavailability of digoxin. European Journal of Clinical Pharmacology, 8, pp. 365–370, 1975. doi: [Crossref]
[2] Clearly, P.W., Predicting charge motion, power draw, segregation, wear and particle breakage in ball mills using discrete element method. Minerals Engineering, 11, pp. 1061–1080, 1998. doi: [Crossref]
[3] Watanbe, H., Critical rotation speed for ball-milling. Powder Technology, 104, pp. 95–99, 1999. doi: [Crossref]
[4] Misra, B.K. & Rajamani, R.K., Simulation of charge motion in ball mills, Part 2: numerical simulations. International Journal of Mineral Processing, 40, pp. 187–197, 1994. doi: [Crossref]
[5] Hlungwani, O., Rikhotso, J., Dong, H. & Moys, H., Further validation of DEM modeling of milling: effects of linear profi le and mill speed. Minerals Engineering, 16, pp. 993–998, 2003. doi: [Crossref]
[6] Austin, L.G. & Lucker, P.T., A simulation model for air-swept ball mill grinding coal. Powder Technology, 38, pp. 255–266, 1984. doi: [Crossref]
[7] Kwan, C.C., Mio, H., Chen, Y.C., Ding, Y.L., Saito, F., Papadopoulos, D.G., Benthem, A.C. & Ghadiri, M., Analysis of the milling rate of pharmaceutical powders usingdistinct element method. Chemical Engineering Science, 60, pp. 1441–1448, 2005. doi: [Crossref]
[8] Campbell, G.M., Bunn, P.J., Webb, C. & Hook, S.C.W., On predicting roller mill performance, Part II: the breakage function. Powder Technology, 115, pp. 243–255, 2001. doi: [Crossref]
[9] Austin, L., A preliminary simulation model for fi ne grinding in high speed hammer mills. Powder Technology, 143–144, pp. 240–252, 2004. doi: [Crossref]
[10] Gotsis, C. & Austin, L.G., Batch grinding kinetics in the presence of a dead space as in a hammer mill. Powder Technology, 41, pp. 91–98, 1985. doi: [Crossref]
[11] Vogel, L. & Peukert, W., From single particle impact behavior to modeling of impact mills. Chemical Engineering Science, 60, pp. 5164–5176, 2005. doi: [Crossref]
[12] Djordjevic, N., Shi, F.N. & Morrison, R.D., Applying discrete element modeling to vertical and horizontal shaft impact crushers. Minerals Engineering, 16, pp. 983–991, 2003. doi: [Crossref]
[13] Cundall, P.A., A computer model for simulating progressive large-scale movements in blocky rock systems. Proceedings of Symposium International Society of Rock Mechanics, 2, pp. 129, 1971.
[14] Cundall, P.A. & Strack, O., A discrete numerical model for granular assemblies. Geotechnique, 29, pp. 47–65, 1979. doi: [Crossref]
[15] Dippel, S., Batrouni, G. & Wolf, D., Collision-induced friction in the motion of a single particle on a bumpy inclined line. Physical Review E, 54, pp. 6845, 1995. doi: [Crossref]
[16] Chaudhuri, B., Mehrota, A., Muzzio, F. & Tomassone, M., Cohesive effects in powder mixing in a tumbling blender. Powder Technology, 165, pp. 105–114, 2006. doi: [Crossref]
[17] Faqih, A., Chaudhuri, B., Mehrotra, A., Tomassone, M. & Muzzio, F., Constitutive model to predict fl ow of cohesive powders in bench scale hoppers. Chemical Engineering Science, 65(10), pp. 3341–3351, 2010. doi: [Crossref]
[18] Walton, O.R., Numerical simulation of inclined chute fl ows of mono disperse, inelastic, frictional spheres. Mechanics of Materials, 16, pp. 239–247, 1993. doi: [Crossref]
[19] Chaudhuri, B., Alexander, A.W.A., Faqih, A, Muzzio, F.J., Davies, C. & Tomassone, M.S., Avalanching fl ow of cohesive powders. Powder Technology, 164, pp. 13–21, 2006. doi: [Crossref]
[20] Chaudhuri, B., Muzzio, F. & Tomassone, M., Modeling of heat transfer in granular flow in rotary vessels. Chemical Engineering Science, 61, pp. 6348–6360, 2006. doi: [Crossref]
[21] Morrison, R.D., Shi, F. & Whyte, R., Modeling of incremental rock breakage by impact – for use in DEM models. Mineral Engineering, 20, pp. 303–309, 2007. doi: [Crossref]
[22] Grady, D.E., Fragmentation under impulsive stress loading. Fragmentation by Blasting, ed. W.L. Fourney et al., Society for Experimental Mechanics: Connecticut, USA, pp. 63–72, 1985.
[23] Poschel, T. & Schwager, T., Computational Granular Dynamics: Model and Algorithms, Springer Verlag: Berlin, Germany, pp. 110, 2005. doi: [Crossref]
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Open Access
Research article

Experiment and Model-Based Investigation of Comminution in a Hammer Mill

s. naik1,
y. feng2,
b. chaudhuri1,3
1
Department of Pharmaceutical Sciences, University of Connecticut, USA
2
Eli Lilly and Company, USA
3
Institute of Material Sciences, University of Connecticut, USA
International Journal of Computational Methods and Experimental Measurements
|
Volume 2, Issue 4, 2014
|
Pages 362-373
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
View Full Article|Download PDF

Abstract:

Particle size reduction of dry granular material by mechanical means, also known as milling or comminution, is undoubtedly a very important unit operation in pharmaceutical, agricultural, food, mineral and paper industries. As comminution is a stochastic and a nonlinear process, an attempt was made to understand this complicated process by conducting parametric studies experimentally and computationally using discrete element method (DEM). Greater size reduction was observed at higher rotational speed of the hammer owing to the greater centrifugal force experienced by the particles. Increase in impeller wall tolerance resulted in rolling mode regime of powder bed, which was found to be significant at low impeller speeds. A numerical model based on DEM was used to simulate a hammer mill and study the breakage and kinematics of the particle motion within the hammer mill. In the simulations, increase in hammer tip speed causes higher frequency of impact of particles per unit time and higher specific energy of impact resulting in generation of much finer end product. A limit can be conceived during the breakage event. This is because as size reduction occurs, the breakage rates can fall for very fine particles as crack propagation ceases. This is because as size decreases the probability of finding a flaw also decreases. Simulations also showed a higher milling rate for big hammers as larger hammers decrease the tolerance between the milling chamber and rotating impeller. To study the effect of material properties, the energy of fragmentation was estimated and it was found to increase as the material became more cohesive.

Keywords: DEM, Fragmentation, Mill, Pharmaceutical

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References
[1] Jounela, A.J., Pentikainen, P.J. & Sothmann, A., Effect of particle size on the bioavailability of digoxin. European Journal of Clinical Pharmacology, 8, pp. 365–370, 1975. doi: [Crossref]
[2] Clearly, P.W., Predicting charge motion, power draw, segregation, wear and particle breakage in ball mills using discrete element method. Minerals Engineering, 11, pp. 1061–1080, 1998. doi: [Crossref]
[3] Watanbe, H., Critical rotation speed for ball-milling. Powder Technology, 104, pp. 95–99, 1999. doi: [Crossref]
[4] Misra, B.K. & Rajamani, R.K., Simulation of charge motion in ball mills, Part 2: numerical simulations. International Journal of Mineral Processing, 40, pp. 187–197, 1994. doi: [Crossref]
[5] Hlungwani, O., Rikhotso, J., Dong, H. & Moys, H., Further validation of DEM modeling of milling: effects of linear profi le and mill speed. Minerals Engineering, 16, pp. 993–998, 2003. doi: [Crossref]
[6] Austin, L.G. & Lucker, P.T., A simulation model for air-swept ball mill grinding coal. Powder Technology, 38, pp. 255–266, 1984. doi: [Crossref]
[7] Kwan, C.C., Mio, H., Chen, Y.C., Ding, Y.L., Saito, F., Papadopoulos, D.G., Benthem, A.C. & Ghadiri, M., Analysis of the milling rate of pharmaceutical powders usingdistinct element method. Chemical Engineering Science, 60, pp. 1441–1448, 2005. doi: [Crossref]
[8] Campbell, G.M., Bunn, P.J., Webb, C. & Hook, S.C.W., On predicting roller mill performance, Part II: the breakage function. Powder Technology, 115, pp. 243–255, 2001. doi: [Crossref]
[9] Austin, L., A preliminary simulation model for fi ne grinding in high speed hammer mills. Powder Technology, 143–144, pp. 240–252, 2004. doi: [Crossref]
[10] Gotsis, C. & Austin, L.G., Batch grinding kinetics in the presence of a dead space as in a hammer mill. Powder Technology, 41, pp. 91–98, 1985. doi: [Crossref]
[11] Vogel, L. & Peukert, W., From single particle impact behavior to modeling of impact mills. Chemical Engineering Science, 60, pp. 5164–5176, 2005. doi: [Crossref]
[12] Djordjevic, N., Shi, F.N. & Morrison, R.D., Applying discrete element modeling to vertical and horizontal shaft impact crushers. Minerals Engineering, 16, pp. 983–991, 2003. doi: [Crossref]
[13] Cundall, P.A., A computer model for simulating progressive large-scale movements in blocky rock systems. Proceedings of Symposium International Society of Rock Mechanics, 2, pp. 129, 1971.
[14] Cundall, P.A. & Strack, O., A discrete numerical model for granular assemblies. Geotechnique, 29, pp. 47–65, 1979. doi: [Crossref]
[15] Dippel, S., Batrouni, G. & Wolf, D., Collision-induced friction in the motion of a single particle on a bumpy inclined line. Physical Review E, 54, pp. 6845, 1995. doi: [Crossref]
[16] Chaudhuri, B., Mehrota, A., Muzzio, F. & Tomassone, M., Cohesive effects in powder mixing in a tumbling blender. Powder Technology, 165, pp. 105–114, 2006. doi: [Crossref]
[17] Faqih, A., Chaudhuri, B., Mehrotra, A., Tomassone, M. & Muzzio, F., Constitutive model to predict fl ow of cohesive powders in bench scale hoppers. Chemical Engineering Science, 65(10), pp. 3341–3351, 2010. doi: [Crossref]
[18] Walton, O.R., Numerical simulation of inclined chute fl ows of mono disperse, inelastic, frictional spheres. Mechanics of Materials, 16, pp. 239–247, 1993. doi: [Crossref]
[19] Chaudhuri, B., Alexander, A.W.A., Faqih, A, Muzzio, F.J., Davies, C. & Tomassone, M.S., Avalanching fl ow of cohesive powders. Powder Technology, 164, pp. 13–21, 2006. doi: [Crossref]
[20] Chaudhuri, B., Muzzio, F. & Tomassone, M., Modeling of heat transfer in granular flow in rotary vessels. Chemical Engineering Science, 61, pp. 6348–6360, 2006. doi: [Crossref]
[21] Morrison, R.D., Shi, F. & Whyte, R., Modeling of incremental rock breakage by impact – for use in DEM models. Mineral Engineering, 20, pp. 303–309, 2007. doi: [Crossref]
[22] Grady, D.E., Fragmentation under impulsive stress loading. Fragmentation by Blasting, ed. W.L. Fourney et al., Society for Experimental Mechanics: Connecticut, USA, pp. 63–72, 1985.
[23] Poschel, T. & Schwager, T., Computational Granular Dynamics: Model and Algorithms, Springer Verlag: Berlin, Germany, pp. 110, 2005. doi: [Crossref]

Cite this:
APA Style
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BibTex Style
MLA Style
Chicago Style
GB-T-7714-2015
Naik, S., Feng, Y., & Chaudhuri, B. (2014). Experiment and Model-Based Investigation of Comminution in a Hammer Mill. Int. J. Comput. Methods Exp. Meas., 2(4), 362-373. https://doi.org/10.2495/CMEM-V2-N4-362-373
S. Naik, Y. Feng, and B. Chaudhuri, "Experiment and Model-Based Investigation of Comminution in a Hammer Mill," Int. J. Comput. Methods Exp. Meas., vol. 2, no. 4, pp. 362-373, 2014. https://doi.org/10.2495/CMEM-V2-N4-362-373
@research-article{Naik2014ExperimentAM,
title={Experiment and Model-Based Investigation of Comminution in a Hammer Mill},
author={S. Naik and Y. Feng and B. Chaudhuri},
journal={International Journal of Computational Methods and Experimental Measurements},
year={2014},
page={362-373},
doi={https://doi.org/10.2495/CMEM-V2-N4-362-373}
}
S. Naik, et al. "Experiment and Model-Based Investigation of Comminution in a Hammer Mill." International Journal of Computational Methods and Experimental Measurements, v 2, pp 362-373. doi: https://doi.org/10.2495/CMEM-V2-N4-362-373
S. Naik, Y. Feng and B. Chaudhuri. "Experiment and Model-Based Investigation of Comminution in a Hammer Mill." International Journal of Computational Methods and Experimental Measurements, 2, (2014): 362-373. doi: https://doi.org/10.2495/CMEM-V2-N4-362-373
NAIK S, FENG Y, CHAUDHURI B. Experiment and Model-Based Investigation of Comminution in a Hammer Mill[J]. International Journal of Computational Methods and Experimental Measurements, 2014, 2(4): 362-373. https://doi.org/10.2495/CMEM-V2-N4-362-373