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Another frequently used approach for thermal conductivity prediction involves the use of thermal conductivities of components constituting the material. Sweat [26] has proposed the following correlation for solid and liquid foods. 58m w (63) The following equation has been suggested by Choi and Okos [27] for liquid foods. 61m w (64) Riedel [35] has proposed the following equation for fruit juices, sugar solutions and milk over a temperature range from 0°C to180°C. 73x10 −3 ) (65) A more general model for thermal conductivity prediction can be written as follows [27]: λ = ∑ λi εi (66) i where εi is the volume fraction of component i and λi is the corresponding thermal conductivity.
By using the perfect gas law, it can be expressed as the ratio of the actual vapor pressure Pv (Pa) to the vapor pressure of the saturated air at the same temperature Pv,sat (Pa). ϕ = Pv / Pv,sat (T) (1) Humidity Ratio The humidity ratio of moist air is defined as the ratio of the mass of water vapor Mv (kg) to the mass of dry air contained in the moist air Ma (kg). ω = Mv / Ma (2) Saturation Humidity Ratio The saturation humidity ratio ωsat is the humidity ratio of moist air saturated with respect to water at the same temperature and pressure.
5037 x10 −5 T 2 Inverse Approaches for the Prediction of Thermophysical Properties Inverse modeling is a general mathematical method to determine unknown causes on the basis of observation of their effects, as opposed to modeling of direct problems whose solution involves finding effects on the basis of a description of their causes [36]. Inverse approaches for the prediction of the thermophysical properties become widely used in the last few decades. Inverse approaches can also be used to obtain other physical properties such as heat and mass transfer coefficients.