Volume 20, Issue 5 (May 2020)
Modares Mechanical Engineering 2020, 20(5): 1309-1320 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Aghaei M, Dehghan R. Effect of Turbulence Models on Numerical Simulation of a Two-Stage Centrifugal Separator. Modares Mechanical Engineering 2020; 20 (5) :1309-1320
URL: http://mme.modares.ac.ir/article-15-32293-en.html
URL: http://mme.modares.ac.ir/article-15-32293-en.html
1- Mining & Metallurgical Engineering Department, Yazd University, Yazd, Iran
2- Mining & Metallurgical Engineering Department, Yazd University, Yazd, Iran , rdehghans@yazd.ac.ir
2- Mining & Metallurgical Engineering Department, Yazd University, Yazd, Iran , rdehghans@yazd.ac.ir
Abstract: (1605 Views)
Two-stage centrifugal separators are the last generation of gravity separators for the separation and upgrading of minerals. Gravity upgrading techniques are methods by which a mixture of particles with different dimensions, shapes, and masses can be separated by gravity, centrifugal force, and other forces by the flow of fluid, especially water (or air). The fluid flow inside such separators is always turbulent. The selection of a suitable turbulence model is an important stage for the prediction of the fluid flow pattern in numerical simulation. The purpose of this research was to find the suitable turbulence model for the prediction of hydrodynamic parameters in a two-stage centrifugal separator using computational fluid dynamics (CFD) modeling. For this purpose, multiphase simulation of the separator has been performed using five turbulence model including k-e, renormalization group (RNG k-e) and Reynolds stress model (RSM). Air core pattern, velocity distribution and partition curve of discrete phase were used for evaluation of the effect of turbulence model on the flow field. The results of the CFD simulation were validated using experimental data. The difference between the results of RSM simulation with the experimental results for fluid recovery, air-core size in the first and second stage of separator were 4.73%, 4.3% and 5.2%, respectively. The results of turbulence models of k-e and RNG k-e were not in accordance with the experimental results.
Keywords: Two-Stage Centrifugal Separator, Turbulence Model, Air Core, Computational Fluid Dynamics (CFD)
Article Type: Original Research |
Subject:
Computational Fluid Dynamic (CFD)
Received: 2019/04/24 | Accepted: 2019/10/14 | Published: 2020/05/9
Received: 2019/04/24 | Accepted: 2019/10/14 | Published: 2020/05/9
References
1. Piller M, Mencinger J, Schena G, Belardi G. Two-phase flow field in a cylindrical hydrocyclone with tangential discharge. International Journal of Fluid Mechanics Research. 2017;44(1):41-64. [Link] [DOI:10.1615/InterJFluidMechRes.2017016140]
2. Piller M, Schena G, Belardi G. Sensitivity of DynaWhirlpool hydrocyclone operation to applied back-pressure. International Journal of Mineral Processing. 2016;154:81-93. [Link] [DOI:10.1016/j.minpro.2016.07.006]
3. Ferrara G, Bozzato P, Chinè B. Performance of conical and cylindrical separatory vessels in dynamic dense-medium separation processes. Mining, Metallurgy & Exploration. 1999;16(2):8-15. [Link] [DOI:10.1007/BF03402801]
4. Ferrara G, Machiavelli G, Bevilacqua P, Meloy TP. Tri-Flo: A multistage high- sharpness DMS process with new applications. Mining, Metallurgy & Exploration. 1994;11(2):63-73. [Link] [DOI:10.1007/BF03403043]
5. Ruff HJ. Operating experience with the Tri-Flo dense medium separator. Trans Inst Min Metall Sect C. 1986;95:225-228. [Link]
6. Dhakal TP, Walters DK, Strasser W. Numerical study of gas-cyclone airflow: an investigation of turbulence modelling approaches. International Journal of Computational Fluid Dynamics. 2014;28(1-2):1-15. [Link] [DOI:10.1080/10618562.2013.878800]
7. Suasnabar DJ. Dense medium cyclone performance enhancement via computational modelling of the physical processes [Dissertaion]. Sydney, Australia: The University of New South Wales; 2000. [Link]
8. Dyakowski T, Williams RA. Modelling turbulent flow within a small-diameter hydrocyclone. Chemical Engineering Science. 1993;48(6):1143-1152. [Link] [DOI:10.1016/0009-2509(93)81042-T]
9. Delgadillo JA, Rajamani RK. A comparative study of three turbulence-closure models for the hydrocyclone problem. International Journal of Mineral Processing. 2005;77(4):217-230. [Link] [DOI:10.1016/j.minpro.2005.06.007]
10. Brennan M. CFD simulations of hydrocyclones with an air core: Comparison between large eddy simulations and a second moment closure. Chemical Engineering Research and Design. 2006;84(6):495-505. [Link] [DOI:10.1205/cherd.05111]
11. Slack MD, Prasad RO, Bakker A, Boysan F. Advances in cyclone modelling using unstructured grids. Chemical Engineering Research and Design. 2000;78(8):1098-1104. [Link] [DOI:10.1205/026387600528373]
12. Narasimha M, Brennan M, Holtham PN. Large eddy simulation of hydrocyclone-prediction of air-core diameter and shape. International Journal of Mineral Processing. 2006;80(1):1-14. [Link] [DOI:10.1016/j.minpro.2006.01.003]
13. Narasimha M, Brennan MS, Holtham PN, Napier-Munn TJ. A comprehensive CFD model of dense medium cyclone performance. Minerals Engineering. 2007;20(4):414-426. [Link] [DOI:10.1016/j.mineng.2006.10.004]
14. Cortés C, Gil A. Modeling the gas and particle flow inside cyclone separators. Progress in Energy and Combustion Science. 2007;33(5):409-452. [Link] [DOI:10.1016/j.pecs.2007.02.001]
15. Elghobashi S. On predicting particle-laden turbulent flows. Applied Scientific Research. 1994;52(4):309-329. [Link] [DOI:10.1007/BF00936835]
16. Elsayed K, Lacor C. Optimization of the cyclone separator geometry for minimum pressure drop using mathematical models and CFD simulations. Chemical Engineering Science. 2010;65(22):6048-6058. [Link] [DOI:10.1016/j.ces.2010.08.042]
17. Elsayed K, Lacor C. The effect of cyclone vortex finder dimensions on the flow pattern and performance using LES. Computers & Fluids. 2013;71:224-239. [Link] [DOI:10.1016/j.compfluid.2012.09.027]
18. Wang B, Xu DL, Chu KW, Yu AB. Numerical study of gas-solid flow in a cyclone separator. Applied Mathematical Modelling. 2006;30(11):1326-1342. [Link] [DOI:10.1016/j.apm.2006.03.011]
19. de Souza FJ, de Vasconcelos Salvo R, de Moro Martins DA. Large Eddy Simulation of the gas-particle flow in cyclone separators. Separation and Purification Technology. 2012;94:61-70. [Link] [DOI:10.1016/j.seppur.2012.04.006]
20. Derksen JJ. Separation performance predictions of a Stairmand high-efficiency cyclone. AIChE Journal. 2003;49(6):1359-1371. [Link] [DOI:10.1002/aic.690490603]
21. Derksen JJ, van den Akker HEA, Sundaresan S. Two-way coupled large-eddy simulations of the gas-solid flow in cyclone separators. AIChE Journal. 2008;54(4):872-885. [Link] [DOI:10.1002/aic.11418]
22. Ghadirian M, Hayes RE, Mmbaga J, Afacan A, Xu Z. On the simulation of hydrocyclones using CFD. The Canadian Journal of Chemical Engineering. 2013;91(5):950-958. [Link] [DOI:10.1002/cjce.21705]
23. Mousavian SM, Najafi AF. Numerical simulations of gas-liquid-solid flows in a hydrocyclone separator. Archive of Applied Mechanics. 2009;79(5):395-409. [Link] [DOI:10.1007/s00419-008-0237-2]
24. Aketi VAK, Vakamalla TR, Narasimha M, Sreedhar GE, Shivakumar R, RajanKumar A. Computational Fluid Dynamic study on the effect of near gravity material on dense medium cyclone treating coal using Discrete Phase Model and Algebraic Slip mixture multiphase model. The Journal of Computational Multiphase Flows. 2016;9(2):58-70. [Link] [DOI:10.1177/1757482X16677755]
25. Brar LS, Elsayed K. Analysis and optimization of cyclone separators with eccentric vortex finders using large eddy simulation and artificial neural network. Separation and Purification Technology. 2018;207:269-283. [Link] [DOI:10.1016/j.seppur.2018.06.013]
26. Li G, Hall P, Miles N, Wu T, Dong J. Numerical Investigation of the Performance of a Vorsyl Separator Using a Euler-Lagrange Approach. International Journal of Mechanical and Mechatronics Engineering. 2016;10(9):1643-1650. [Link]
27. Mikheev N, Saushin I, Paereliy A, Kratirov D, Levin K. Cyclone separator for gas-liquid mixture with high flux density. Powder Technology. 2018;339:326-333. [Link] [DOI:10.1016/j.powtec.2018.08.040]
28. Zhang T, Guo K, Liu C, Li Y, Tao M, Shen C. Experimental and Numerical Investigations of a Dual-Stage Cyclone Separator. Chemical Engineering & Technology. 2018;41(3):606-617. [Link] [DOI:10.1002/ceat.201700052]
29. Elsayed K, Lacor C. CFD modeling and multi-objective optimization of cyclone geometry using desirability function, artificial neural networks and genetic algorithms. Applied Mathematical Modelling. 2013;37(8):5680-5704. [Link] [DOI:10.1016/j.apm.2012.11.010]
30. Elsayed K. Optimization of the cyclone separator geometry for minimum pressure drop using Co-Kriging. Powder Technology. 2015;269:409-424. [Link] [DOI:10.1016/j.powtec.2014.09.038]
31. Elsayed K, Lacor C. Numerical modeling of the flow field and performance in cyclones of different cone-tip diameters. Computers & Fluids. 2011;51(1):48-59. [Link] [DOI:10.1016/j.compfluid.2011.07.010]
32. Elsayed K. Design of a novel gas cyclone vortex finder using the adjoint method. Separation and Purification Technology. 2015;142:274-286. [Link] [DOI:10.1016/j.seppur.2015.01.010]
33. Fathizadeh N, Mohebbi A, Soltaninejad S, Iranmanesh M. Design and simulation of high pressure cyclones for a gas city gate station using semi-empirical models, genetic algorithm and computational fluid dynamics. Journal of Natural Gas Science and Engineering. 2015;26:313-329. [Link] [DOI:10.1016/j.jngse.2015.06.022]
34. Karimi M, Akdogan G, Dellimore KH, Bradshaw SM. Quantification of numerical uncertainty in computational fluid dynamics modelling of hydrocyclones. Computers & Chemical Engineering. 2012;43:45-54. [Link] [DOI:10.1016/j.compchemeng.2012.04.009]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |