NUMERICAL STUDY OF TURBULENCE ON DRAG COEFFICIENT DETERMINATION FOR PARTICLE AGGLOMERATES

Original scientific paper

Authors

  • Ricardo Arbach Fernandes de Oliveira Graduate Program in Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, km 235 - SP-310 São Carlos, São Paulo, Brazil https://orcid.org/0000-0002-4337-9351
  • Julio Henrique Zanata Department of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, km 235 - SP-310 São Carlos, São Paulo, Brazil https://orcid.org/0009-0004-1965-6701
  • Gabriela Cantarelli Lopes Department of Chemical Engineering and Graduate Program in Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, km 235 - SP-310 São Carlos, São Paulo, Brazil

DOI:

https://doi.org/10.2298/CICEQ221206021O

Keywords:

Particulate matter, particle agglomerates, turbulence, drag coefficient, computational fluid dynamics

Abstract

Numerical simulations of the flow surrounding particle agglomerates were carried out using computational fluid dynamics to assess the ability of five RANS turbulence models to estimate the drag coefficient in particle agglomerates. Simulations were carried out in steady conditions for Reynolds numbers between 1 and 1500. Streamlines showed that symmetrical agglomerates present a velocity profile similar to the single sphere profile. Results showed that both Spalart-Allmaras and SST k-ω turbulence models could represent the flow profile in the regions near and far from the walls of the agglomerates and the wake region in the rear of the agglomerates. The RNG k-ε model showed poor quality in predicting the velocity profile and the drag coefficient. The drag coefficient obtained by simulations presented a trend better represented by the Tran-Cong model, also showing that deviations from the predictions decreased as the packing density of the agglomerate increased. The use of steady RANS simulations showed to be a feasible and efficient method to predict, with low computational cost, the drag coefficient in particle agglomerates. For the transition and turbulent flows, results presented good agreement, with deviations between -15% and 13%, while for lower Reynolds numbers, deviations varied between -25% and 5%.

References

J. Wang, W. Ge, J. Li, Chem. Eng. Sci. 63 (2008) 1553—1571. https://doi.org/10.1016/j.ces.2007.11.023.

E.U. Hartge, L. Ratschow, R. Wischnewski, J. Werther, Particuology 7 (2009) 283—296.

https://doi.org/10.1016/j.partic.2009.04.005.

A. Nikolopoulos, D. Papafotiou, N. Nikolopoulos, P. Grammelis, E. Kakaras, Chem. Eng. Sci. 65 (2010) 4080—4088. https://doi.org/10.1016/j.ces.2010.03.054.

L. Wang, C. Wu, W. Ge, Powder Technol. 319 (2017) 221—227. https://doi.org/10.1016/j.powtec.2017.06.046.

D. Gidaspow, in Multiphase Flow and Fluidization: Continuum and Kinetic Theory Descriptions with Applications, Academic Press, Cambridge (1994). ISBN: 978-0-122-82470-8.

R.J. Hill, D.L. Koch, A.J.C. Ladd, J. Fluid Mech. 448 (2001) 213—241. https://doi.org/10.1017/S0022112001005948.

R.J. Hill, D.L. Koch, A.J.C. Ladd, J. Fluid Mech. 448 (2001) 243—278. https://doi.org/10.1017/S0022112001005936.

M.A. van der Hoef, R. Beetstra, J.A.M. Kuipers, J. Fluid Mech. 528 (2005) 233—254. https://doi.org/10.1017/S0022112004003295.

R.C. Senior, C. Brereton, Chem. Eng. Sci. 47 (1992) 281—296. https://doi.org/10.1016/0009-2509(92)80020-D.

K. Kuwagi, K. Takano, M. Horio, Powder Technol. 113 (2000) 287—298. https://doi.org/10.1016/S0032-5910(00)00311-9.

S. Tran-Cong, M. Gay, E.E. Michaelides, Powder Technol. 139 (2004) 21—32. https://doi.org/10.1016/j.powtec.2003.10.002.

D.A. Deglon, C.J. Meyer, Miner. Eng. 19 (2006) 1059—1068. https://doi.org/10.1016/j.mineng.2006.04.001.

G.L. Lane, Chem. Eng. Sci. 169 (2017) 188—211. https://doi.org/10.1016/j.ces.2017.03.061.

R. Clift, J.R. Grace, M.E. Weber, Bubbles, Drops and Particles, Academic Press, Cambridge (1978). ISBN: 978-0-121-76950-5.

D. Leith, Aerosol Sci. Technol. 6 (1987) 153—161. https://doi.org/10.1080/02786828708959128.

A. Haider, O. Levenspiel, Powder Technol. 58 (1989) 63—70. https://doi.org/10.1016/0032-5910(89)80008-7.

G.H. Ganser, Powder Technol. 77 (1993) 143—152. https://doi.org/10.1016/0032-5910(93)80051-B.

A. Hölzer, M. Sommerfeld, Powder Technol. 184 (2008) 361—365. https://doi.org/10.1016/j.powtec.2007.08.021.

G. Bagheri, C. Bonadonna, Powder Technol. 301 (2016) 526—544. https://doi.org/10.1016/j.powtec.2016.06.015.

R. Beetstra, M. van der Hoef, J. Kuipers, Comput. Fluids 35 (2006) 966—970. https://doi.org/10.1016/j.compfluid.2005.03.009.

N.G. Deen, S.H.L. Kriebitzsch, M.A. van der Hoef, J.A.M. Kuipers, Chem. Eng. Sci. 81 (2012) 329—344. https://doi.org/10.1016/j.ces.2012.06.055.

S.B. Pope, Turbulent Flows, Cambridge University Press, Cambridge, (2000). ISBN: 978-0-521-59886-6.

S. Heinz, Prog. Aerosp. Sci. 114 (2020) 100597. https://doi.org/10.1016/j.paerosci.2019.100597.

S.Y. Chen, G.D. Doolen, Annu. Rev. Fluid Mech. 30 (1998) 329—364. https://doi.org/10.1146/annurev.fluid.30.1.329.

M. Dietzel, M. Sommerfeld, Powder Technol. 250 (2013) 122—137. https://doi.org/10.1016/j.powtec.2013.09.023.

M. Mehrabadi, E. Murphy, S. Subramaniam, Chem. Eng. Sci. 152 (2016) 199—212. https://doi.org/10.1016/j.ces.2016.06.006.

S. Chen, P. Chen, J. Fu, Phys. Fluids 34 (2022) 023307. https://doi.org/10.1063/5.0082653.

ANSYS, Inc, ANSYS Fluent 14.5 Theory Guide (2012). http://www.pmt.usp.br/academic/martoran/notasmodelosgrad/ANSYS%20Fluent%20Theory%20Guide%2015.pdf [accessed 15 February 2023].

J. Ferziger, M. Perić, R.L. Street, Computational Methods for Fluid Dynamics, Springer, New York, (2002). ISBN: 978-3-319-99693-6.

P.R. Spalart, S.R. Allmaras, Technical Report AIAA-92-0439 1 (1992) 5—21. https://doi.org/10.2514/6.1992-439.

V. Yakhot, S.A. Orszag, S. Thangam, T.B. Gatski, C.G. Speziale, Phys. Fluids A 7 (1992) 1510—1520. https://doi.org/10.1063/1.858424.

F.R. Menter, AIAA J. 32 (1994) 1598—1605. https://doi.org/10.2514/3.12149.

R.B. Langtry, F.R. Menter, AIAA J. 47 (2009) 2894—2906. https://doi.org/10.2514/1.42362.

B.E. Launder, G.J. Reece, W. Rodi, J. Fluid Mech. 68 (1975) 537—566. https://doi.org/10.1017/S0022112075001814.

W.R.A. Goossens, Powder Technol. 352 (2019) 350—359. https://doi.org/10.1016/j.powtec.2019.04.075.

E. Loth, Powder Technol. 182 (2008) 342—353. https://doi.org/10.1016/j.powtec.2007.06.001.

J.P. van Doormaal, G.D. Raithby, Numer. Heat Transfer 7 (1984) 147—163. https://doi.org/10.1080/01495728408961817.

H.K. Versteeg, W. Malalasekera, An Introduction to Computational Fluid Dynamics: The Finite Volume Method, Pearson Education Limited, Harlow, (2007). ISBN: 978-0-131-27498-3.

Z. Tuković, M. Perić, H. Jasak, Comput. Fluids 166 (2018) 78—85. https://doi.org/10.1016/j.compfluid.2018.01.041.

D.C. Wilcox, Turbulence Modeling for CFD, DCW Industries, La Cañada, (2004). ISBN: 978-1-928729-08-2.

B.E. Launder, B.I. Sharma, Lett. Heat Mass Trans. 1 (1974) 131—138. https://doi.org/10.1016/0094-4548(74)90150-7.

J.L. Isaacs, G. Thodos, Can. J. Chem. Eng. 45 (1967) 150—155. https://doi.org/10.1002/cjce.5450450306.

R. Clift, W.H. Gauvin, Can. J. Chem. Eng. 49 (1971) 439—448. https://doi.org/10.1002/cjce.5450490403.

E.K. Marchildon, W.H. Gauvin, AIChE J. 25 (1979) 938—948. https://doi.org/10.1002/aic.690250604.

R.P. Chhabra, L. Agarwal, N.K. Sinha, Powder Technol. 101 (1999) 288—295. https://doi.org/10.1016/S0032-5910(98)00178-8.

J. Militzer, J. M. Kan, F. Hamdullahpur, P.R. Amyotte, A.M. Al Taweel, Powder Technol. 57 (1989) 193—195. https://doi.org/10.1016/0032-5910(89)80075-0.

R. Ouchene, Phys. Fluids 32 (2020) 073303. https://doi.org/10.1063/5.0011618.

B.R. Munson, D.F. Young, T.H. Okiishi, Fundamentals of Fluid Mechanics, John Wiley & Sons, Hoboken, (2016). ISBN: 978-1-119-54799-0.

B.E. Thompson, J.H. Whitelaw, J. Fluid Mech. 157 (1985) 305—326. https://doi.org/10.1017/S0022112085002397.

L. Davidson, J. Fluids Eng. 117 (1995) 50—57. https://doi.org/10.1115/1.2816818.

Published

17.08.2023 — Updated on 09.12.2023

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How to Cite

NUMERICAL STUDY OF TURBULENCE ON DRAG COEFFICIENT DETERMINATION FOR PARTICLE AGGLOMERATES: Original scientific paper. (2023). Chemical Industry & Chemical Engineering Quarterly, 30(2), 161-177. https://doi.org/10.2298/CICEQ221206021O

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