Graduate Thesis Or Dissertation

 

Thermophysical properties and temperature response of surimi-- measurement and modeling Pubblico Deposited

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/6q182n92v

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  • Freezing is one of the important technologies for preservation of foods. In this project, using surimi as a food model, thermophysical properties of frozen foods were evaluated and the freezing process was simulated using a finite element package. To measure temperature-dependent thermal conductivity, a line-source probe system was used. Effects of test conditions and sample history were investigated. Thermal conductivity of Alaska pollock (Theragra chalcogramma) surimi having 0, 4, 6, 8, and 12% cryoprotectant levels was measured in the range of -40 to 30 ° C. Other thermal properties were analyzed using differential scanning calorimetry (DSC) at the same cryoprotectant concentrations and in the same temperature range. Each dynamically corrected DSC thermogram was used to determine initial freezing point, unfreezable water (bound water), apparent specific heat, enthalpy and unfrozen water weight fraction. When water content of the sample is controlled, thermophysical properties of surimi have a relatively weak dependence upon cryoprotectant level in the unfrozen and fully frozen (-40° C) ranges. However, the initial freezing point and the properties just below this point were significantly affected. From measured data, the Schwartzberg thermal property models for frozen foods were investigated. The models agreed well with experimental data. However, possibility for further improvement is demonstrated by using DSC analysis. This research additionally demonstrated the great potential of DSC for measuring and modeling frozen food thermal properties. Using the derived property models, a commercial PC-based finite element package was used to simulate the process of freezing a food block in a plate freezer. The capability of the program to handle temperature-dependent thermal properties and time-dependent boundary conditions enabled a simulation which accounted for measured changes in thermal properties, ambient temperatures and overall heat transfer coefficient. Predicted temperature history agreed well with measured data. Sensitivities of important model parameters, which were varied within their experimental error range, were also investigated using a factorial experimental design method. The result showed that in decreasing order of influencing freezing time prediction, attention should be given to apparent specific heat, block thickness, overall heat transfer coefficient, ambient temperature, thermal conductivity, and density.
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