Startseite Numerical simulation of conductive heat transfer in canned celery stew and retort program adjustment by computational fluid dynamics (CFD)
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Numerical simulation of conductive heat transfer in canned celery stew and retort program adjustment by computational fluid dynamics (CFD)

  • Arezoo Berenjforoush Azar , Yousef Ramezan EMAIL logo und Morteza Khashehchi
Veröffentlicht/Copyright: 11. Juni 2020
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

In this study, conductive heat transfer was investigated during sterilization in the canned celery stew. A computational fluid dynamics CFD model was developed and validated to predict the temperature profiles and determine the slowest heating zone (SHZ) during the thermal processing. The temperature profile was obtained and recorded experimentally at a point where the coldest thermal point was expected. CFD models were validated against experimental data. The results of the study showed that the SHZ was located at the geometric center of the containers (x = 5.00, y = 1.42, z = 6.75 cm), and the temperature reached 119.5 °C. Root mean square error (RMSE) was calculated and showed a good fit between both methods (RMSE = 1.03). The container geometrical center F0 was estimated to be 13.19 min. For optimization of the process, according to the stew ingredients, especially meat, F0 was about 8 min. Thus, the required holding time was decreased by 5.19 min, and the retort setting was readjusted.


Corresponding author: Yousef Ramezan, Department of Food Science and Technology, Faculty of Pharmacy, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran, E-mail:

Acknowledgments

The authors are grateful to the Hani food company in Tehran for providing experimental facilities for this study.

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

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

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

Nomenclature

time (s)

t

experimental temperature (°C)

Texp

simulated temperature (°C)

Tsim

wall temperature (°C)

Tw

mass component

X

volumetric component

Y

thermal resistance coefficient (°C)

Z

density (kg/m3)

ρ

computational fluids dynamics

CFD

special heat (kJ/kg °C)

Cp

sterilization value (s)

F0

special total enthalpy (J/kg)

htotal

thermal conductivity (W/m °C)

λ, k

root mean square error

RMSE

internal energy source(J)

SE

temperature (°K)

T

References

1. Padmavati R, Anandharamakrishnan C. Computational fluid dynamics modeling of the thermal processing of canned pineapple slices and titbits. Food Bioprocess Technol 2013;6:882–95. https://doi.org/10.1007/s11947-012-0892-8.Suche in Google Scholar

2. Vatankhah H, Zamindar N, Baghekhandan MS. Heat transfer simulation and retort program adjustment for thermal processing of wheat based Haleem in semi-rigid aluminum containers. J Food Sci Technol 2015;52:6798–803. https://doi.org/10.1007/s13197-015-1764-9.Suche in Google Scholar

3. Ghani AA, Farid M, Chen X, Richards P. An investigation of deactivation of bacteria in a canned liquid food during sterilization using computational fluid dynamics (CFD). J Food Eng 1999;42:207–14. https://doi.org/10.1016/s0260-8774(99)00123-5.Suche in Google Scholar

4. Singh RP, Heldman DR. Introduction to food engineering, 4th ed. Burlington, MA: Academic Press/Elsevier; 2009.Suche in Google Scholar

5. Ghani, A, Farid, M, Chen, X. Theoretical and experimental investigation of the thermal inactivation of Bacillus stearothermophilus in food pouches. J Food Eng 2002; 51: 221–8. https://doi.org/10.1016/s0260-8774(01)00060-7.Suche in Google Scholar

6. Vatankhah H, Zamindar N, Shahedi M. Geometry simplification of wrinkled wall semi-rigid aluminum containers in heat transfer simulation. J Agr Sci Tech 2016;18:123–33. https://doi.org/10.1007/s13197-015-1764-9.Suche in Google Scholar

7. Erdogdu F, Tutar M. Velocity and temperature field characteristics of water and air during natural convection heating in cans. J Food Sci 2011;76:E119–29. https://doi.org/10.1111/j.1750-3841.2010.01913.x.Suche in Google Scholar

8. Cordioli M, Rinaldi M, Copelli G, Casoli P, Barbanti D. Computational fluid dynamics (CFD) modelling and experimental validation of thermal processing of canned fruit salad in glass jar. J Food Eng 2015;150:62–9. https://doi.org/10.1016/j.jfoodeng.2014.11.003.Suche in Google Scholar

9. Pletcher, R., Tannehill, J., Anderson, D., 2012. Computational fluid mechanics and heat transfer. CRC Press, New York, USA.Suche in Google Scholar

10. Xia B, Sun DW. Applications of computational fluid dynamics (CFD) in the food industry: a review. Comput Electron Agric 2002;34:5–24. https://doi.org/10.1016/s0168-1699(01)00177-6.Suche in Google Scholar

11. Park H, Yoon W. Computational fluid dynamics (CFD) modelling and application for sterilization of foods: a review. Processes 2018;6:62. https://doi.org/10.3390/pr6060062.Suche in Google Scholar

12. Boz Z, Erdogdu F, Tutar M. Effects of mesh refinement, time step size and numerical scheme on the computational modeling of temperature evolution during natural-convection heating. J Food Eng 2014;123:8–16. https://doi.org/10.1016/j.jfoodeng.2013.09.008.Suche in Google Scholar

13. Ghani AA, Farid M, Chen X, Richards P. Thermal sterilization of canned food in a 3-D pouch using computational fluid dynamics. J Food Eng 2001;48:147–56. https://doi.org/10.1016/s0260-8774(00)00150-3.Suche in Google Scholar

14. Cordioli M, Rinaldi M, Barbanti D. Investigation and modelling of natural convection and conduction heat exchange: study on food systems with modified starch by means of computational fluid dynamics. Int J Food Sci Technol 2016;51:854–64. https://doi.org/10.1111/ijfs.13039.Suche in Google Scholar

15. Rinaldi M, Malavasi M, Cordioli M, Barbanti D. Investigation of influence of container geometry and starch concentration on thermal treated in-package food models by means of computational fluid dynamics (CFD). Food Bioprod Process 2018;108:1–11. https://doi.org/10.1016/j.fbp.2017.12.003.Suche in Google Scholar

16. Mc Donald K, Sun DW, Lyng JG. Effect of vacuum cooling on the thermophysical properties of a cooked beef product. J Food Eng 2002;52:167–76. https://doi.org/10.1016/s0260-8774(01)00100-5.Suche in Google Scholar

17. Sahin S, Sumnu S. Electromagnetic properties. Physical properties of foods. Springer, New York, USA; 2006, pp. 157–92.10.1007/0-387-30808-3_4Suche in Google Scholar

18. Mohsenin NN. Thermal properties of foods and agricultural materials. New York, USA: Gordon & Breach Science Publisher; 1980.Suche in Google Scholar

19. Baghe‐Khandan M, Choi Y, Okos MR. Improved line heat source thermal conductivity probe. J Food Sci 1981;46:1430–2. https://doi.org/10.1111/j.1365-2621.1981.tb04191.x.Suche in Google Scholar

20. Hamdami N, Monteau JY, Le Bail A. Effective thermal conductivity of a high porosity model food at above and sub-freezing temperatures. Int J Refrig 2003;26:809–16. https://doi.org/10.1016/s0140-7007(03)00051-3.Suche in Google Scholar

21. Latimer, G, 2019. Official methods of analysis of AOAC International, 21st ed. AOAC International, Gaithersburg, Maryland.10.1093/9780197610138.001.0001Suche in Google Scholar

22. Varma MN, Kannan A. CFD studies on natural convective heating of canned food in conical and cylindrical containers. J Food Eng 2006;77:1024–36. https://doi.org/10.1016/j.jfoodeng.2005.07.035.Suche in Google Scholar

23. Sun, D-W. Thermal sterilization of food using CFD. Computational fluid dynamics in food processing. CRC Press, New York, USA; 2007, pp. 331–46.10.1201/9781420009217-17Suche in Google Scholar

24. Simpson R, Almonacid S, Mitchell M. Mathematical model development, experimental validation and process optimization: retortable pouches packed with seafood in cone frustum shape. J Food Eng 2004;63:153–62. https://doi.org/10.1016/s0260-8774(03)00294-2.Suche in Google Scholar

25. Sun, D-W. Thermal food processing: new technologies and quality issues. CRC Press, New York, USA; 2012.10.1201/b12112Suche in Google Scholar

26. Noronha J, Van Loey A, Hendrickx M, Tobback P. Simultaneous optimisation of surface quality during the sterilisation of packed foods using constant and variable retort temperature profiles. J Food Eng 1996;30:283–97. https://doi.org/10.1016/s0260-8774(96)00035-0.Suche in Google Scholar

27. Landry, W, Schwab, A, Lancette, G. Examination of canned foods. AOAC International, Gaithersburg, Maryland; 1998.Suche in Google Scholar

28. Rabiey L, Flick D, Duquenoy A. 3D simulations of heat transfer and liquid flow during sterilisation of large particles in a cylindrical vertical can. J Food Eng 2007;82:409–17. https://doi.org/10.1016/j.jfoodeng.2007.02.011.Suche in Google Scholar

29. Siripon K, Tansakul A, Mittal GS. Heat transfer modeling of chicken cooking in hot water. Food Res Int 2007;40:923–30. https://doi.org/10.1016/j.foodres.2007.03.005.Suche in Google Scholar

30. Ghani AA, Farid M, Chen X, Richards P. Numerical simulation of natural convection heating of canned food by computational fluid dynamics. J Food Eng 1999;41:55–64. https://doi.org/10.1016/s0260-8774(99)00073-4.Suche in Google Scholar

Received: 2019-10-01
Accepted: 2020-04-02
Published Online: 2020-06-11

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 11.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijfe-2019-0303/html
Button zum nach oben scrollen