Startseite Appling the computational fluid dynamics studies of the thermogravitational column for N2-CO2 and He-Ar gas mixtures separation
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Appling the computational fluid dynamics studies of the thermogravitational column for N2-CO2 and He-Ar gas mixtures separation

  • Hesam Salimi , Neda Hashemipour , Javad Karimi-Sabet EMAIL logo und Younes Amini
Veröffentlicht/Copyright: 11. Oktober 2021
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

In the present work, three-Dimensional stationary numerical simulations were accomplished for a deeper understanding of the gas mixtures separation by the thermogravitational column. To address the optimum condition and examine the limitation of the process, the thermogravitational column behavior has been thoroughly analyzed. First, the simulation model was validated by the experimental results of Youssef et al. then the model was developed for the pilot column. The mixture of helium-argon was chosen as feed composition. It was concluded that the variation of the separation factor in relation to pressure for both columns was almost the same. The optimum condition verified as p = 0.2  atm , θ = 0.4 , m ° = 4 SCCM .


Corresponding author: Javad Karimi-Sabet, Nuclear Fuel Cycle Research School, Nuclear Science and Technology Research Institute, Tehran, Iran; and Advanced Separation and Simulation Research Center, Tehran, Iran, E-mail:

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

1. Rahman, M, Saghir, M. Thermodiffusion or soret effect: historical review. Int J Heat Mass Tran 2014;73:693–705. https://doi.org/10.1016/j.ijheatmasstransfer.2014.02.057.Suche in Google Scholar

2. Clusius, K, Dickel, G. New process for separation of gas mixtures and isotopes. Naturwissenschaften 1938;26. https://doi.org/10.1007/bf01675498.Suche in Google Scholar

3. Khan, M, Salahuddin, T, Tanveer, A, Malik, M, Hussain, A. Change in internal energy of thermal diffusion stagnation point Maxwell nanofluid flow along with solar radiation and thermal conductivity. Chin J Chem Eng 2019;27:2352–8. https://doi.org/10.1016/j.cjche.2018.12.023.Suche in Google Scholar

4. Eslamian, M, Saghir, MZ. On thermophoresis modeling in inert nanofluids. Int J Therm Sci 2014;80:58–64. https://doi.org/10.1016/j.ijthermalsci.2014.01.016.Suche in Google Scholar

5. Abro, KA. A fractional and analytic investigation of thermo-diffusion process on free convection flow: an application to surface modification technology. Eur Phys J Plus 2020;135:31. https://doi.org/10.1140/epjp/s13360-019-00046-7.Suche in Google Scholar

6. Mousavi, SB, Heyhat, MM. Numerical study of heat transfer enhancement from a heated circular cylinder by using nanofluid and transverse oscillation. J Therm Anal Calorim 2019;135:935–45. https://doi.org/10.1007/s10973-018-7343-3.Suche in Google Scholar

7. Martin, A, Bou-Ali, MM, Barrutia, H, De Mezquia, DA. Microfluidic separation process by the soret effect in biological fluids. Compt Rendus Mec 2011;339:342–8. https://doi.org/10.1016/j.crme.2011.03.012.Suche in Google Scholar

8. Geelhoed, P, Lindken, R, Westerweel, J. Thermophoretic separation in microfluidics. Chem Eng Res Des 2006;84:370–3. https://doi.org/10.1205/cherd05012.Suche in Google Scholar

9. Dogonchi, A, Ismael, MA, Chamkha, AJ, Ganji, D. Numerical analysis of natural convection of Cu–water nanofluid filling triangular cavity with semicircular bottom wall. J Therm Anal Calorim 2019;135:3485–97. https://doi.org/10.1007/s10973-018-7520-4.Suche in Google Scholar

10. Sheikholeslami, M, Rezaeianjouybari, B, Darzi, M, Shafee, A, Li, Z, Nguyen, TK. Application of nano-refrigerant for boiling heat transfer enhancement employing an experimental study. Int J Heat Mass Tran 2019;141:974–80. https://doi.org/10.1016/j.ijheatmasstransfer.2019.07.043.Suche in Google Scholar

11. Yeh, H-M. Thermal diffusion in branch columns for improved separation. J Taiwan Inst Chem Eng 2013;44:560–5. https://doi.org/10.1016/j.jtice.2013.01.011.Suche in Google Scholar

12. Platten, J, Bou-Ali, M, Dutrieux, J. Enhanced molecular separation in inclined thermogravitational columns. J Phys Chem B 2003;107:11763–7. https://doi.org/10.1021/jp034780k.Suche in Google Scholar

13. Vela´ squez, JE, Chejne, F, Hill, AF. Mathematical model and simulation of a thermal diffusion column. J Heat Tran 2003;125:266–73.10.1115/1.1560150Suche in Google Scholar

14. Yamamoto, I, Makino, H, Kanagawa, A. Optimum feed point for isotope separating thermal diffusion column. J Nucl Sci Technol 1995;32:200–5. https://doi.org/10.1080/18811248.1995.9731696.Suche in Google Scholar

15. Yeh, HM. Improvement in recovery of deuterium from water–isotopes mixture in inclined thermal-diffusion columns. Int J Hydrogen Energy 2003;28:873–9. https://doi.org/10.1016/s0360-3199(02)00164-7.Suche in Google Scholar

16. Wiegand, S. Thermal diffusion in liquid mixtures and polymer solutions. J Phys Condens Matter 2004;16:R357. https://doi.org/10.1088/0953-8984/16/10/r02.Suche in Google Scholar

17. Yang, JC, Pitts, WM, Fernandez, M, Prasad, K. Measurements of effective diffusion coefficients of helium and hydrogen through gypsum. Int J Hydrogen Energy 2013;38:8125–31. https://doi.org/10.1016/j.ijhydene.2012.09.030.Suche in Google Scholar

18. Ning, H, Wiegand, S. Experimental investigation of the soret effect in acetone/water and dimethylsulfoxide/water mixtures. J Chem Phys 2006;125:221102. AIP.10.1063/1.2402159Suche in Google Scholar PubMed

19. Platten, JK. The Soret effect: a review of recent experimental results. J Appl Mech 2005;73:5–15.10.1115/1.1992517Suche in Google Scholar

20. Kumar, V, Murthy, SK, Kumar, BR. Influence of MHD forces on Bejan’s heatlines and masslines in a doubly stratified fluid saturated Darcy porous enclosure in the presence of Soret and Dufour effects–A numerical study. Int J Heat Mass Tran 2018;117:1041–62. https://doi.org/10.1016/j.ijheatmasstransfer.2017.10.054.Suche in Google Scholar

21. Mousavi, S, Yousefi, T, Saghir, M. Accurate measurement of temperature and concentration distribution of a mixture in a rectangular parallelepiped enclosure. Int Commun Heat Mass Tran 2016;76:225–36. https://doi.org/10.1016/j.icheatmasstransfer.2016.05.020.Suche in Google Scholar

22. Šeta, B, Lapeira, E, Dubert, D, Gavaldá, F, Bou-Ali, MM, Ruiz, X. Separation under thermogravitational effects in binary mixtures. Eur Phys J E 2019;42:58.10.1140/epje/i2019-11818-7Suche in Google Scholar PubMed

23. Hashemipour, N, Karimi-Sabet, J, Motahari, K, Monfared, SM, Amini, Y, Moosavian, MA. Experimental and simulation investigation on separation of binary hydrocarbon mixture by thermogravitational column. J Mol Liq 2018;268:791–806. https://doi.org/10.1016/j.molliq.2018.07.098.Suche in Google Scholar

24. Hashemipour, N, Karimi-Sabet, J, Motahari, K, Monfared, SM, Amini, Y, Moosavian, MA. Numerical study of n-heptane/benzene separation by thermal diffusion column. Chin J Chem Eng 2019;27:1745–55. https://doi.org/10.1016/j.cjche.2018.10.004.Suche in Google Scholar

25. Madariaga, JA, Santamaria, C, Barrutia, H, Bou-Ali, MM, Ecenarro, O, Valencia, JJ. Validity limits of the FJO thermogravitational column theory: experimental and numerical analysis. Compt Rendus Mec 2011;339:292–6. https://doi.org/10.1016/j.crme.2011.03.004.Suche in Google Scholar

26. Youssef, A, Hanna, M, Migahed, M. Performance of thermal diffusion columns for gas mixtures. Z Naturforsch 1965;20:655–62. https://doi.org/10.1515/zna-1965-0503.Suche in Google Scholar

27. Yeh, HM. Numerical model for separation of H–D gas mixture in batch-type concentric-tube thermal diffusion columns. Fusion Eng Des 2009;84:43–8. https://doi.org/10.1016/j.fusengdes.2008.09.001.Suche in Google Scholar

28. Dehkordi, JA, Hosseini, SS, Kundu, PK, Tan, NR. Mathematical modeling of natural gas separation using hollow fiber membrane modules by application of finite element method through statistical analysis. Chem Prod Process Model 2016;11:11–5. https://doi.org/10.1515/cppm-2015-0052.Suche in Google Scholar

29. Amini, Y, Nasr Esfahany, M. CFD simulation of the structured packings: a review. Separ Sci Technol 2019;54:2536–54. https://doi.org/10.1080/01496395.2018.1549078.Suche in Google Scholar

30. Amini, Y, Karimi-Sabet, J, Esfahany, MN. Experimental and numerical study of multiphase flow in new wire gauze with high capacity structured packing. Chem Eng Process: Process Intensif 2016;108:35–43. https://doi.org/10.1016/j.cep.2016.07.003.Suche in Google Scholar

31. Zhang, M, Müller-Plathe, F. Reverse nonequilibrium molecular-dynamics calculation of the Soret coefficient in liquid benzene/cyclohexane mixtures. J Chem Phys 2005;123:124502. https://doi.org/10.1063/1.2042427.Suche in Google Scholar PubMed

32. Adeniyi, AG, Ighalo, JO. Study of process factor effects and interactions in synthesis gas production via a simulated model for glycerol steam reforming. Chem Prod Process Model 2019;14:20180034. https://doi.org/10.1515/cppm-2018-0034.Suche in Google Scholar

33. Bird, RB. Transport phenomena. Appl Mech Rev 2002;55:R1–4. https://doi.org/10.1115/1.1424298.Suche in Google Scholar

34. Radhika, G, Burolia, AK, Raja, PKR, Ambati, SR, Patle, DS, Gara, UBB. Energy saving in batch distillation for separation of ternary zeotropic mixture integrated with vapor recompression scheme: dynamics and control. Chem Prod Process Model 2020;16:101–15.10.1515/cppm-2020-0045Suche in Google Scholar

35. Gakis, G, Koronaki, E, Boudouvis, A. Numerical investigation of multiple stationary and time-periodic flow regimes in vertical rotating disc CVD reactors. J Cryst Growth 2015;432:152–9. https://doi.org/10.1016/j.jcrysgro.2015.09.026.Suche in Google Scholar

36. Ighalo, JO, Adeniyi, AG. Statistical modelling and optimisation of the biosorption of Cd (II) and Pb (II) onto dead biomass of Pseudomonas aeruginosa. Chem Prod Process Model 2021;16:20190139. https://doi.org/10.1515/cppm-2019-0139.Suche in Google Scholar

37. Cox, N, Drapala, P, Finlayson, BF. Transport limitations in thermal diffusion. In: The 2007 Annual Meeting; 2007.Suche in Google Scholar

38. Wesselingh, J, Krishna, R. Mass transfer in multicomponent mixtures. Delft: University Press Delft; 2000.Suche in Google Scholar

39. Leahy-Dios, A, Bou-Ali, MM, Platten, JK, Firoozabadi, A. Measurements of molecular and thermal diffusion coefficients in ternary mixtures. J Chem Phys 2005;122:234502. https://doi.org/10.1063/1.1924503.Suche in Google Scholar PubMed

40. Jha, BK, Oni, MO. Theory of fully developed mixed convection including flow reversal: a nonlinear Boussinesq approximation approach. Heat Tran Asian Res 2019;48:3477–88. https://doi.org/10.1002/htj.21550.Suche in Google Scholar

41. Mojumder, S, Sourav, SA, Sumon, SA, Mamun, MA. Combined effect of Reynolds and Grashof numbers on mixed convection in a lid-driven T-shaped cavity filled with water-Al2O3 nanofluid. J Hydrodynam B 2015;27:782–94. https://doi.org/10.1016/s1001-6058(15)60540-6.Suche in Google Scholar

42. Boulemtafes-Boukadoum, A, Abid, C, Benzaoui, A. 3D Numerical study of the effect of aspect ratio on mixed convection air flow in upward solar air heater. Int J Heat Fluid Flow 2020;84:108570. https://doi.org/10.1016/j.ijheatfluidflow.2020.108570.Suche in Google Scholar

43. Mubashir, M, Leng, CT, Keong, LK, Jusoh, N. Study on the effect of process parameters on CO2/CH4 binary gas separation performance over NH2-MIL-53 (Al)/cellulose acetate hollow fiber mixed matrix membrane. Polym Test 2020;81:106223. https://doi.org/10.1016/j.polymertesting.2019.106223.Suche in Google Scholar

44. Wood, HG, Ying, C, Zeng, S, Nie, Y, Shang, X. Estimation of overall separation factor of a gas centrifuge for different multicomponent mixtures by separation theory for binary case. Separ Sci Technol 2002;37:417–30. https://doi.org/10.1081/ss-120000796.Suche in Google Scholar

45. Agarwal, P. Simulation of heat transfer phenomenon in furnace using fluent-gambit [Doctoral dissertation]. Rourkela: National Institute of Technology of Rourkela; 2009.Suche in Google Scholar

46. Srinivas, G, Potti, SR. Numerical simulation of axial flow fan using Gambit and Fluent. Int J Res Eng Technol 2014;3:586–90.10.15623/ijret.2014.0315109Suche in Google Scholar

47. Schulze, S, Nikrityuk, P, Abosteif, Z, Guhl, S, Richter, A, Meyer, B. Heat and mass transfer within thermogravimetric analyser: from simulation to improved estimation of kinetic data for char gasification. Fuel 2017;187:338–48. https://doi.org/10.1016/j.fuel.2016.09.048.Suche in Google Scholar

Received: 2021-05-29
Accepted: 2021-09-13
Published Online: 2021-10-11

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 16.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/cppm-2021-0036/pdf?lang=de
Button zum nach oben scrollen