Browsing by Autor "Victor Chavarria"

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Measurement of Convective Heat Transfer Coefficients During Food Freezing Processes
(Wiley, 1984) Victor Chavarria; Dennis R. Heldman
ABSTRACT Any prediction of freezing time for a food product depends on accurate heat transfer coefficients. The purpose of this investigation was to examine experimental procedures for accurate determination of convective transfer coefficients during freezing of food products. Measurements of heat transfer coefficients during cooling of any acrylic transducer and ground beef with similar size and shape were conducted at air temperatures below initial freezing point of the product. The results indicate that accurate measurements of the coefficients can be achieved through nonlinear regression analysis of temperature histories within an acrylic transducer.
Modeling the Influence of Temperature-dependent Thermal Properties on the Freezing Front
(Canadian Center of Science and Education, 2019) Victor Chavarria
Although numerical methods enable comprehensive analyses of food freezing, a thorough quantification is lacking the effects on the process introduced by uncertainties in variable thermal properties. Analytical models are, however, more suitable tools to perform such calculations. We aim to quantify these effects by developing a solution to the freezing front (FF) problem subject to temperature-dependent thermal properties and one-dimensional convective cooling. The heat integral balance method, Kirchhoff&#39;s transformation, and Plank&#39;s cooled-surface temperature equation (as a seed function) enabled us to obtain an approximate solution to the FF penetration time. To optimize model accuracy, two adjustable parameters were correlated with the inputs via nonlinear regression referenced to numerical simulation FF data. The mapped sensitivities, generated by perturbations in the temperature-dependent thermal conductivity and effective heat capacity, undergo rapid nonlinear changes for Biot numbers below 6. Above this level, these sensitivities stabilize depending on the cooling medium temperature and a thermal conductivity parameter. The median thermal conductivity-driven sensitivity is 0.348 and its interquartile range (IQR) is 0.220 to 0.425, whereas the median latent heat-driven sensitivity is 0.967 (IQR: 0.877 to 0.985). Statistical error measures and a ten-split K-fold validation support the model accuracy and reliability of the parameter estimates. Together, the model allows for gaining insights into the nonlinear behavior and magnitude of the influence of variable properties on the FF for a wide range of conditions. Nonlinear methods and prior information enable practical modeling of transport phenomena in foods.