A Semi-Empirical Model for Predicting Frost Properties

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate numerical model in predicting properties like density, thickness, and thermal conductivity. This can recognize crystal shape via linear programming of existing map morphology. By using method, conditions be taken into account obtain corresponding conductivity, density specific crystal. It found that developed predict more accurately than correlations. Specifically, identify by dimensionless temperature surface temperature. Moreover, adopting identification model, thickness also predicted satisfactorily. The calculation not only shows better predictive ability with conductivities, but gives good predictions especially accurate when lower 125 kg/m3. Yet, improved 24% compared most correlation available.