با همکاری انجمن علوم و صنایع غذایی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و صنایع غذایی، دانشکده کشاورزی و منابع طبیعی، دانشگاه آزاد اسلامی واحد اصفهان (خوراسگان)، اصفهان، ایران

2 گروه علوم و صنایع غذایی، واحد شهرکرد، دانشگاه آزاد اسلامی، شهرکرد، ایران

چکیده

در این پژوهش مدل عددی انتقال حرارت در کنسرو عصاره مالت با بریکس 60 در بسته‌بندی آلومینیومی نیمه‌سخت با نرم‌افزار فلوئنت توسعه داده شد. شکل هندسی کنسرو حاوی نمونه، توسط نرم­افزار گمبیت رسم و شبکه­بندی مناسب با فاصله گره­هایcm 1/0 و cm2/0 اعمال شد. سپس انتقال حرارت درون کنسرو در طول فرآیند حرارتی با استفاده از نرم­افزار فلوئنت شبیه­سازی شد. پروفیل­های دمایی فرآیند حرارتی، شکل و محل ناحیه کند حرارتی در کنسرو نمونه بررسی شد. همچنین تأثیر وجود سرفضا (فضای خالی بالای ظرف) بر انتقال حرارت مورد بررسی قرار گرفت. شبکه­بندی مناسب برای شبیه­سازی، شبکه با فاصله گره­های cm2/0 بود. نتایج شبیه­سازی نشان داد که محل ناحیه کند حرارتی در کنسرو عصاره مالت دارای سرفضا در پایان مرحله حرارت­دهی در محدوده cm27/3->Z>37/3-، cm3/0>Y>1-، cm8/0>X>02/0-  و در مدل فاقد سرفضا در پایان مرحله حرارت­دهی در محدوده cm05/3->Z>46/3- ، cm48/0>  Y>44/3-، cm76/3>X>58/3- است. بین دماهای پیش­بینی شده و دماهای حاصل از تکرارهای آزمایشگاهی در سطح احتمال 1% تفاوت معنی­دار مشاهده نشد. پروفیل­های دمایی حاصل از شبیه­سازی در حالت­های دارا و فاقد سرفضا در مراحل مختلف فرآیند حرارتی دارای مشابهت قابل قبولی بودند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Heat Transfer Modeling of Malt Syrup in Semi-rigid Aluminum Based Packaging

نویسندگان [English]

  • Saeede Hamidi 1
  • Nafiseh Zamindar 1
  • Nayyere Gholipour Shahraki 2

1 Department of Food Science and Technology, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

2 Department of Food Science and Technology, Shahrekord Branch, Islamic Azad ‎University, Shahrekord, Iran

چکیده [English]

Introduction
Thermal processing is an important method of canned food production (Farid & Abdul Ghani, 2004). Estimation of the heat transfer rates is essential to obtain optimum processing conditions and to improve product quality. In addition, a better understanding of the mechanism of the heating process will lead to an improved performance in the process and to some energy savings (Abdul Ghani et al., 1999). Computational fluid dynamics (CFD) is an efficient way to study flow behavior and temperature distribution of thermal processing in the food technology (Ghani et al., 2003). As the semi-rigid aluminum packaging market recently has been introduced, there is limited information about the temperature distribution during the heating process of such containers. In this paper the temperature distribution was predicted and location of cold zone was determined. The effect of headspace (air and water vapor) in heat transfer mechanism was investigated.
 
Materials and Methods
Physical properties
Malt extract properties such as density, specific heat, thermal conductivity and viscosity values are necessary for the equations solution. Viscosity and density of the sample was measured as a function of temperature (Vatankhah et al., 2015). Specific heat and thermal conductivity of sample were estimated using the mass fraction of its constituents. For simulation, the experimental results were applied by piecewise-linear method in the material part of the software to describe viscosity, thermal conductivity and specific heat.
 
Experimental methodology
For the experimental, a thermocouple probe was located at point (0, 0, -2.76) in a semi rigid aluminum based packaging to measure the temperature distribution inside the container. Then the package was filled with malt extract (°Brix ~ 60) and then the package was sealed at 280 °C using Alcan machine. Another thermocouple was placed near the containers, in the water cascading Barriquand steriflow retort. The thermocouples were attached to Ellab data logger by PT100 cables. The data logger was connected to a personal computer and E-val 2.1 software was used to export time temperature profile of each thermocouple in 1 min intervals.
 
 
Geometry and meshing
Gambit 2.3.30 was used to develop geometry and set of grid (0.2 cm, and 0.1 cm mesh size) was performed. Then software of fluent 6.3.26 with 3-D, double precision, pressure-based solver, implicit formulation, unsteady time, laminar flow was applied to solve the system of the governing equations (Vatankhah et al., 2015).
 
Boundary conditions and initial values
Unsteady temperature function was imposed to all faces of the geometry in 1 min time intervals. No-slip boundary condition was supposed for velocity components relative to boundaries. The boundary conditions used at top surface, bottom surface and side walls included: T = Tw, Vx = 0, Vy = 0 and Vz = 0. The initial temperature was assumed as the first temperature which was measured by the thermocouple at the starting time of processing.
 
Solution methodology
Fluent software was used to solve the Navier-Stokes and energy equations simultaneously. A preset convergence limit of 10−3 for continuity and momentum equations and 10−8 for the energy equation were used, in order to achieve an appropriate convergence. The under-relaxation factors were adjusted smaller than 1 to obtain a good convergence of the numerical solution. SIMPLEC algorithm was used for pressure-velocity coupling.
 
Results and Discussion
There was no significant difference between predicted and experimental temperatures for point (0, 0, -2.76) in models with and without head space using t-test (p<0.01).  Temperature contours of predicted models (with headspace) were similar to model without headspace at the different stages of the process. Simulation result showed slowest heating zone located in (0.02 <X< 0.8, -1 <Y< 0.3 and -3.27<Z< 3.27) for model of malt extract with headspace and in (-3.58 < X< 3.76, -3.44 <Y< 0.48 and -3.46 <Z< -3.05) for model of malt extract without headspace.
 
Conclusion
The heating process of malt extract in semi rigid aluminum container during thermal processing was simulated successfully using CFD. The CFD based model showed that the position of SHZ was located in the third end of the container.

کلیدواژه‌ها [English]

  • Computational Fluid Dynamics
  • Malt extract
  • Semi rigid aluminum container
  • Slowest heating zone

©2023 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.

  1. Abdul Ghani, A.G., Farid, M.M., & Chen, X.D. (2002). Numerical simulation of transient temperature and velocity profiles in a horizontal can during sterilization using computational fluid dynamics. Journal of Food Engineering, 51(1), 77-83. https://doi.org/10.1016/S0260-8774(01)00039-5
  2. Abdul Ghani, A.G., Farid, M.M., & Chen, X.D. (2002). Theoretical and experimental investigation of the thermal inactivation of Bacillus stearothermophilus in food pouches. Journal of Food Engineering, 51(3), 221-228. https://doi.org/10.1016/S0260-8774(01)00060-7
  3. Abdul Ghani, G., Farid, M.M., Chen, X.D., & Richards, P. (1999). An investigation of deactivation of bacteria in a canned liquid food during sterilization using computational fluid dynamics (CFD). Journal of Food Engineering, 42, 207-214. https://doi.org/10.1016/S0260-8774(99)00123-5
  4. Abdul Ghani, A.G., Farid, M.M., Chen, X.D., & Richards, P. (1999). Numerical simulation of natural convection heating of canned food by computational fluid dynamics. Journal of Food Engineering, 41, 55-64. https://doi.org/10.1016/S0260-8774(99)00073-4
  5. Alonso, A.A., Arias-Mendes, A., Balsa-canto, E., Garsia, M.R., Molinia, J.I., Vilas, C., & Villafin, M. (2013). Real time optimization for quality control of batch thermal Sterilization prepackaged Food Control, 32(2), 392-403. https://doi.org/10.1016/j.foodcont.2013.01.002
  6. Brennan, A. (1979). Food engineering operations. Applied Science. London.
  7. Cevik, M., & Icier, F. (2021). Numerical simulation of temperature histories of frozen minced meat having different fat contents during ohmic thawing. International Journal of Thermal Sciences, 165, 106958. https://doi.org/10.1016/j.ijthermalsci.2021.106958
  8. Dash, K., Sharma, M., & Tiwari, A. (2022). Heat and mass transfer modeling and quality changes during deep fat frying: A comprehensive review. Journal of Food Process Engineering, 45(4). https://doi.org/10.1111/jfpe.13999
  9. Erdogdu, F., & Tutar, M. (2012). A computational study for axial rotation effects on heat transfer in rotating cans containing liquid water, semi-fluid food system and headspace. International Journal of Heat and Mass Transfer, 55, 3774–3788. https://doi.org/10.1016/j.ijheatmasstransfer.2012.03.031
  10. Fadavi, A., Yousefi, S., Darvishi, H., & Mirsaeedghazi, H. (2018). Comparative study of ohmic vacuum, ohmic, and conventional-vacuum heating methods on the quality of tomato concentrate. Innovative Food Science & Emerging Technologies, 47, 225-230. https://doi.org/10.1016/j.ifset.2018.03.004
  11. Farid, M.M., & Abdul Ghani, A.G. (2004). A new computational technique for the estimation of sterilization time in canned food. Chemical Engineering and Processing, 43, 523–53. https://doi.org/10.1016/j.cep.2003.08.007
  12. Islamic Republic of Iran ISIRI NUMBER 3897. Barley malt extract specifications and test methods. Institute of Standards and Industrial Research of Iran. ISLAMIC REPUBLIC OF IRAN.
  13. Loews, F.A. (1952). Improvement in anthrone method for determination of carbohydrates. Analytical Chemistry, 24(1), 219. https://doi.org/10.1021/ac60061a050
  14. Mohamed, I.O. (2007). Determination of an effective heat transfer coefficients for can headspace during thermal sterilization process. Journal of Food Engineering, 79, 1166-1171. https://doi.org/10.1016/j.jfoodeng.2006.04.015
  15. Narsaiah, K., Bedi, V., Ghodki, B., & Goswami, T. (2021). Heat transfer modeling of shrimp in tunnel type individual quick freezing system. Journal of Food Process Engineering, 44(11). https://doi.org/10.1111/jfpe.13838
  16. Nicolai, B.M., Verboven, P., & Scheerlinck, N. (2001). Food process modeling. PP 60-81 in: L. M. M. Tijskens and M. L. A. T. M. Hertog. The Modeling of Heat and Mass Transfer. CRC Press., Boca Rayton.
  17. Norton, & Sun, D.W. (2006). Computational fluid dynamics (CFD) – an effective and efficient design and analysis tool for the food industry: A review. Trends in Food Science & Technology, 17(11), 600-620. https://doi.org/10.1016/j.tifs.2006.05.004
  18. Razavi, M. A., & Akbari, R. (2012). Biophysical properties of agricultural & food materials. Mashhad Ferdowsi University, Mashhad.
  19. Sahin, S., & Sumnu, S.G. (2006). Physical Properties of Foods. Middle East Technical University. Ankara.
  20. Simpson, R., Almonasid, S., & Mitchel, M. (2004). Matyhematical model development, Experimemtal validation and processing optimization: retortable pouches packed with seafood in cone frusum shape. Journal of Food Engineering, 63, 153-162. https://doi.org/10.1016/S0260-8774(03)00294-2
  21. Vatankhah, H., Zamindar, N., & Shahedi Baghekhandan, M. (2015). Heat transfer simulation and retort program adjustment for thermal processing of wheat based Haleem in semi-rigid aluminum containers.

 

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