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Numerical investigation of the effects of dry gas model and wet steam model in solar-driven refrigeration ejector system

  • Honglun Cong and Jiao Zhang EMAIL logo
Published/Copyright: October 16, 2023
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Abstract

Nowadays, the use of equipment with little pollution is essential due to the increase in the planet’s temperature. Ejectors are considered one of the equipment with no pollution, and their failure rate is low due to the lack of moving parts. Also, scholars have recently focused on improving the efficiency of industrial equipment. The use of accurate modeling is required to improve steam ejector performance. In a steam ejector, non-equilibrium condensation creates a two-phase flow situation. The wet steam model, used in this study, characterizes this two-phase flow. The study’s objective was to compare this wet steam model with the dry gas model. In the wet steam model, the liquid mass fraction is 0.25, and its calculated entrainment ratio is lower than the dry gas model, closely matching experimental observations. The dry gas model reaches a maximum Mach number of about 5, while the wet steam model approximates 4. A significant temperature difference exists between the two models, with the dry gas model indicating lower temperatures compared to the wet steam model. Diagonal shocks and expansion waves are evident in the mixing chamber, fixed cross-section, and diffuser. These phenomena occur with greater intensity and a slight delay in the wet steam model compared to the dry gas model.


Corresponding author: Jiao Zhang, Working in YiWu JiangNa New Material co., Ltd, Hami Xinjiang, 839303, China, E-mail:

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: Not applicable.

References

1. Gagan, J, Śmierciew, K, Łukaszuk, M, Butrymowicz, D. Investigations of thermal performance of ejection refrigeration system driven by low grade heat. Appl Therm Eng 2018;130:1121–38. https://doi.org/10.1016/j.applthermaleng.2017.11.093.Search in Google Scholar

2. Sarbu, I, Sebarchievici, C. Review of solar refrigeration and cooling systems. Energy Build 2013;67:286–97. https://doi.org/10.1016/j.enbuild.2013.08.022.Search in Google Scholar

3. Liu, J, Wang, L, Jia, L, Wang, X. Thermodynamic modeling and sensitivity analysis of ejector in refrigeration system. Int J Heat Mass Tran 2018;126:485–92. https://doi.org/10.1016/j.ijheatmasstransfer.2018.06.035.Search in Google Scholar

4. Baek, S, Ko, S, Song, S, Ryu, S. Numerical study of high-speed two-phase ejector performance with R134a refrigerant. Int J Heat Mass Tran 2018;126:1071–82. https://doi.org/10.1016/j.ijheatmasstransfer.2018.05.053.Search in Google Scholar

5. Chen, Z, Dang, C, Hihara, E. Investigations on driving flow expansion characteristics inside ejectors. Int J Heat Mass Tran 2017;108:490–500. Sustainable Energy Reviews 2009;13(8):1760–1780. https://doi.org/10.1016/j.ijheatmasstransfer.2016.12.040.Search in Google Scholar

6. Wang, JX, Li, YZ, Li, JX, Li, C, Zhang, Y, Ning, XW. A gas-atomized spray cooling system integrated with an ejector loop: ejector modeling and thermal performance analysis. Energy Convers Manag 2019;180:106–18. https://doi.org/10.1016/j.enconman.2018.10.095.Search in Google Scholar

7. Wang, XD, Lei, HJ, Dong, JL, Tu, JY. The spontaneously condensing phenomena in a steam-jet pump and its influence on the numerical simulation accuracy. Int J Heat Mass Tran 2012;55:4682–7. https://doi.org/10.1016/j.ijheatmasstransfer.2012.04.028.Search in Google Scholar

8. Hakkaki-Fard, A, Aidoun, Z, Ouzzane, M. A computational methodology for ejector design and performance maximisation. Energy Convers Manag 2015;105:1291–302. https://doi.org/10.1016/j.enconman.2015.08.070.Search in Google Scholar

9. Fu, W, Li, Y, Liu, Z, Wu, H, Wu, T. Numerical study for the influences of primary nozzle on steam ejector performance. Appl Therm Eng 2016;106:1148–56. https://doi.org/10.1016/j.applthermaleng.2016.06.111.Search in Google Scholar

10. Ruangtrakoon, N, Thongtip, T, Aphornratana, S, Sriveerakul, T. CFD simulation on the effect of primary nozzle geometries for a steam ejector in refrigeration cycle. Int J Therm Sci 2013;63:133–45. https://doi.org/10.1016/j.ijthermalsci.2012.07.009.Search in Google Scholar

11. Wang, L, Yan, J, Wang, C, Li, X. Numerical study on optimization of ejector primary nozzle geometries. Int J Refrig 2017;76:219–29. https://doi.org/10.1016/j.ijrefrig.2017.02.010.Search in Google Scholar

12. Lee, MS, Lee, H, Hwang, Y, Radermacher, R, Jeong, HM. Optimization of two-phase R600a ejector geometries using a non-equilibrium CFD model. Appl Therm Eng 2016;109:272–82. https://doi.org/10.1016/j.applthermaleng.2016.08.078.Search in Google Scholar

13. Palacz, M, Smolka, J, Kus, W, Fic, A, Bulinski, Z, Nowak, AJ, et al.. CFD-based shape optimisation of a CO2 two-phase ejector mixing section. Appl Therm Eng 2016;95:62–9. https://doi.org/10.1016/j.applthermaleng.2015.11.012.Search in Google Scholar

14. Chen, J, Havtun, H, Palm, B. Screening of working fluids for the ejector refrigeration system. Int J Refrig 2014;47:1–4. https://doi.org/10.1016/j.ijrefrig.2014.07.016.Search in Google Scholar

15. Saleh, B. Performance analysis and working fluid selection for ejector refrigeration cycle. Appl Therm Eng 2016;107:114–24. https://doi.org/10.1016/j.applthermaleng.2016.06.147.Search in Google Scholar

16. Keisari, SJ, Shams, M. Shape optimization of nucleating wet-steam flow nozzle. Appl Therm Eng 2016;103:812–20. https://doi.org/10.1016/j.applthermaleng.2016.04.134.Search in Google Scholar

17. Dolatabadi, AM, Masoumi, S, Lakzian, E. Optimization variables of the injection of hot-steam into the non-equilibrium condensing flow using TOPSIS method. Int Commun Heat Mass Tran 2021;129:105674. https://doi.org/10.1016/j.icheatmasstransfer.2021.105674.Search in Google Scholar

18. Rad, EA, Mahpeykar, MR, Teymourtash, AR. Evaluation of simultaneous effects of inlet stagnation pressure and heat transfer on condensing water-vapor flow in a supersonic Laval nozzle. Sci Iran 2013;20:141–51. https://doi.org/10.1016/j.scient.2012.12.009.Search in Google Scholar

19. Li, A, Yuen, AC, Chen, TB, Wang, C, Liu, H, Cao, R, et al.. Computational study of wet steam flow to optimize steam ejector efficiency for potential fire suppression application. Appl Sci 2019;9:1486. https://doi.org/10.3390/app9071486.Search in Google Scholar

20. Li, H, Wang, X, Huang, H, Ning, J, Li, A, Tu, J. Numerical study on the effect of superheat on the steam ejector internal flow and entropy generation for MED-TVC desalination system. Desalination 2022;537:115874. https://doi.org/10.1016/j.desal.2022.115874.Search in Google Scholar

21. Wen, C, Ding, H, Yang, Y. Performance of steam ejector with nonequilibrium condensation for multi-effect distillation with thermal vapour compression (MED-TVC) seawater desalination system. Desalination 2020;489:114531. https://doi.org/10.1016/j.desal.2020.114531.Search in Google Scholar

22. Ding, H, Sun, C, Wen, C, Liang, Z. The droplets and film behaviors in supersonic separator by using three-field two-fluid model with heterogenous condensation. Int J Heat Mass Tran 2022;184:122315. https://doi.org/10.1016/j.ijheatmasstransfer.2021.122315.Search in Google Scholar

23. Wen, C, Li, B, Ding, H, Akrami, M, Zhang, H, Yang, Y. Thermodynamics analysis of CO2 condensation in supersonic flows for the potential of clean offshore natural gas processing. Appl Energy 2022;310:118523. https://doi.org/10.1016/j.apenergy.2022.118523.Search in Google Scholar

24. Hosseinizadeh, SE, Ghamati, E, Jahangiri, A, Majidi, S, Khazaee, I, Aliabadi, MA. Reduction of water droplets effects in steam turbine blade using Multi-objective optimization of hot steam injection. Int J Therm Sci 2023;187:108155. https://doi.org/10.1016/j.ijthermalsci.2023.108155.Search in Google Scholar

25. Hosseini, SA, Lakzian, E, Nakisa, M. Multi-objective optimization of supercooled vapor suction for decreasing the nano-water droplets in the steam turbine blade. Int Commun Heat Mass Tran 2023;142:106613. https://doi.org/10.1016/j.icheatmasstransfer.2023.106613.Search in Google Scholar

26. Chunnanond, K, Aphornratana, S. An experimental investigation of a steam ejector refrigerator: the analysis of the pressure profile along the ejector. Appl Therm Eng 2004;24:311–22. https://doi.org/10.1016/j.applthermaleng.2003.07.003.Search in Google Scholar

27. Giacomelli, F, Biferi, G, Mazzelli, F, Milazzo, A. CFD modeling of the supersonic condensation inside a steam ejector. Energy Proc 2016;101:1224–31. https://doi.org/10.1016/j.egypro.2016.11.137.Search in Google Scholar

28. Mahpeykar, MR, Amirirad, E. Suppression of condensation shock in wet steam flow by injection of water droplets in different regions of a Laval nozzle. Sci Iran 2010;17.Search in Google Scholar

29. Wiśniewski, P, Dykas, S, Yamamoto, S, Pritz, B. Numerical approaches for moist air condensing flows modelling in the transonic regime. Int J Heat Mass Tran 2020;162:120392. https://doi.org/10.1016/j.ijheatmasstransfer.2020.120392.Search in Google Scholar

30. Dolatabadi, AM, Lakzian, E, Heydari, M, Khan, A. A modified model of the suction technique of wetness reducing in wet steam flow considering power-saving. Energy 2022;238:121685. https://doi.org/10.1016/j.energy.2021.121685.Search in Google Scholar

31. Sharifi, N, Boroomand, M, Kouhikamali, R. Wet steam flow energy analysis within thermo-compressors. Energy 2012;47:609–19. https://doi.org/10.1016/j.energy.2012.09.003.Search in Google Scholar

32. Sharifi, N, Boroomand, M, Sharifi, M. Numerical assessment of steam nucleation on thermodynamic performance of steam ejectors. Appl Therm Eng 2013;52:449–59. https://doi.org/10.1016/j.applthermaleng.2012.12.003.Search in Google Scholar

33. Mazzelli, F, Giacomelli, F, Milazzo, A. CFD modeling of condensing steam ejectors: comparison with an experimental test-case. Int J Therm Sci 2018;127:7–18. https://doi.org/10.1016/j.ijthermalsci.2018.01.012.Search in Google Scholar

34. Ariafar, K, Buttsworth, D, Sharifi, N, Malpress, R. Ejector primary nozzle steam condensation: area ratio effects and mixing layer development. Appl Therm Eng 2014;71:519–27. https://doi.org/10.1016/j.applthermaleng.2014.06.038.Search in Google Scholar

35. Ariafar, K, Buttsworth, D, Al-Doori, G, Malpress, R. Effect of mixing on the performance of wet steam ejectors. Energy 2015;93:2030–41. https://doi.org/10.1016/j.energy.2015.10.082.Search in Google Scholar

36. Aliabadi, MA, Lakzian, E, Jahangiri, A, Khazaei, I. Numerical investigation of effects polydispersed droplets on the erosion rate and condensation loss in the wet steam flow in the turbine blade cascade. Appl Therm Eng 2020;164:114478. https://doi.org/10.1016/j.applthermaleng.2019.114478.Search in Google Scholar

37. Aliabadi, MA, Lakzian, E, Khazaei, I, Jahangiri, A. A comprehensive investigation of finding the best location for hot steam injection into the wet steam turbine blade cascade. Energy 2020;190:116397. https://doi.org/10.1016/j.energy.2019.116397.Search in Google Scholar

38. Aliabadi, MA, Jahangiri, A, Khazaee, I, Lakzian, E. Investigating the effect of water nano-droplets injection into the convergent-divergent nozzle inlet on the wet steam flow using entropy generation analysis. Int J Therm Sci 2020;149:106181. https://doi.org/10.1016/j.ijthermalsci.2019.106181.Search in Google Scholar

39. Aliabadi, MA, Bahiraei, M. Effect of water nano-droplet injection on steam ejector performance based on non-equilibrium spontaneous condensation: a droplet number study. Appl Therm Eng 2021;184:116236. https://doi.org/10.1016/j.applthermaleng.2020.116236.Search in Google Scholar

40. Zhang, G, Wang, X, Dykas, S, Aliabadi, MA. Reduction entropy generation and condensation by NaCl particle injection in wet steam supersonic nozzle. Int J Therm Sci 2022;171:107207. https://doi.org/10.1016/j.ijthermalsci.2021.107207.Search in Google Scholar

41. Dykas, S, Wróblewski, W. Single-and two-fluid models for steam condensing flow modeling. Int J Multiphas Flow 2011;37:1245–53. https://doi.org/10.1016/j.ijmultiphaseflow.2011.05.008.Search in Google Scholar

42. Wróblewski, W, Dykas, S, Gepert, A. Steam condensing flow modeling in turbine channels. Int J Multiphas Flow 2009;35:498–506. https://doi.org/10.1016/j.ijmultiphaseflow.2009.02.020.Search in Google Scholar

43. Aliabadi, MA, Zhang, G, Dykas, S, Li, H. Control of two-phase heat transfer and condensation loss in turbine blade cascade by injection water droplets. Appl Therm Eng 2021;186:116541. https://doi.org/10.1016/j.applthermaleng.2020.116541.Search in Google Scholar

44. Somesaraee, MT, Rad, EA, Mahpeykar, MR. Analytical investigation of simultaneous effects of convergent section heating of Laval nozzle, steam inlet condition, and nozzle geometry on condensation shock. J Therm Anal Calorim 2018;133:1023–39. https://doi.org/10.1007/s10973-018-7126-x.Search in Google Scholar

45. Tashtoush, BM, Al-Nimr, MA, Khasawneh, MA. A comprehensive review of ejector design, performance, and applications. Appl Energy 2019;240:138–72. https://doi.org/10.1016/j.apenergy.2019.01.185.Search in Google Scholar

46. Roe, PL. Characteristic-based schemes for the Euler equations. Annu Rev Fluid Mech 1986;18:337–65. https://doi.org/10.1146/annurev.fl.18.010186.002005.Search in Google Scholar

47. Al-Doori, GF. Investigation of refrigeration system steam ejector performance through experiments and computational simulations. (Doctoral dissertation, University of Southern Queensland).Search in Google Scholar

Received: 2023-04-29
Accepted: 2023-09-15
Published Online: 2023-10-16

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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