Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials

A model to predict the effective thermal conductivity of heterogeneous materials is proposed based on unit cell approach. The model is combined with four fundamental effective thermal conductivity models (Parallel, Series, Maxwell-Eucken-I, and Maxwell-Eucken-II) to evolve a unifying equation for the estimation of effective thermal conductivity of porous and nonporous food materials. The effect of volume fraction (ν) on the structure composition factor (ψ) of the food materials is studied. The models are compared with the experimental data of various foods at the initial freezing temperature. The effective thermal conductivity estimated by the Maxwell-Eucken-I + Present model shows good agreement with the experimental data with a minimum average deviation of ±8.66% and maximum deviation of ±42.76% of Series + Present Model. The combined models have advantages over other empirical and semiempirical models