Modeling immersion frying as a moving boundary proble

A quantitative description of the heat and mass transfer which occurs during the frying of foods is needed to aid in product and process development. The goal of this research was to develop a predictive mathematical model of the heat and mass transfer in the product during immersion frying. The model, developed using macroscopic balances, was comprised of four non-linear, coupled, partial differential equations and associated initial and boundary conditions. The method of Crank-Nicholson was used to reduce the problem to a set of nonlinear, algebraic equations; Gauss-Seidel iteration was used to solve these equations.;It was found that the model was able to predict temperature profiles, moisture content, and crust thickness in close agreement with experimentally determined data. Heat transfer in the crust and core regions was primarily by conduction. The conversion of liquid water to vapor at the crust/core interface served to fix the interface temperature at the boiling point. Mass transfer in the core was modeled using diffusion theory. Magnetic resonance images of un-fried and fried potato samples showed that oil resides solely in the outer crust layer of the fried material.;The validated model was used for a sensitivity analysis. The effect of changing the physical and thermal properties required by the model on temperature profiles, moisture content, and crust thickness was studied. Temperature profiles in the crust region were primarily a function of oil temperature. Core region temperature profiles were not affected by oil temperature due to the presence of a 100$spcirc$C boundary temperature at the crust/core interface. Heating rates of the core region were affected by thermal conductivity and specific heat of the core. Values chosen for diffusivity of the water/starch system had a strong effect on the final moisture content of the fried sample. It was found that crust thickness was affected by thermal conductivity of the crust region, oil temperature, moisture content, and thermal conductivity of the core region. As oil temperature and thermal conductivity of the crust increased so did crust thickness. As moisture content and core thermal conductivity decreased crust thickness increased.