Maria Aversa

An Experimental Analysis of Acoustic Drying of Carrots: Evaluation of Heat Transfer Coefficients in Different Drying Conditions

The aim of the present work was to ascertain the effect of ultrasonic waves on convective drying performance. In the tested range of process and operating conditions, it was proved that compared to a traditional convective process, ultrasounds enhanced the drying rate of cylindrical carrot samples. The obtained results suggested that ultrasound waves actually affected the external resistance to heat and mass transfer, thus improving the drying process mainly during the constant rate period. The heat transfer coefficient was estimated as a function of both air velocity and food diameter, thus allowing a quantitative comparison between traditional and acoustic-assisted convective drying.

Advanced Modeling of Food Convective Drying: A Comparison Between Artificial Neural Networks and Hybrid Approaches

In the present paper, three different approaches are proposed to model the convective drying of food. The performance of thin-layer, pure neural network and hybrid neural model is compared in a wide range of operating conditions, with two different vegetables, available either as cylinders or as slabs with different characteristic dimensions. It was found that the thin-layer model was adequate to describe food drying behavior, but it could be applied only as a fitting procedure. Pure neural models gave accurate predictions in some situations, but exhibited poor performance when tested outside the range of operating conditions exploited during their development. Finally, it was shown that hybrid neural models, formulated as a combination of both theoretical and neural network models, are capable of offering the most accurate predictions of system behavior with average relative errors never exceeding 10%, even in operating conditions unexploited during the definition of the neural part of the model. The results obtained proved that the hybrid neural paradigm is a novel and efficient modeling technique that could be used successfully in food processing, thus allowing drying process optimization to be achieved, and efficient and fast on-line controllers to be implemented.

Measurement of the Water-Diffusion Coefficient, Apparent Density Changes and Shrinkage During the Drying of Eggplant (Solanum Melongena)

The aim of this work was to estimate shrinkage, apparent density changes, and the effective diffusion coefficient of water, Deff , during eggplant drying. Drying experiments were performed using a halogen moisture analyzer. This technology has several advantages over the traditional methods reported in the literature, as it is quite inexpensive, requires less energy, and, in principle, can be used for many different types of foods. The experimental data were interpreted using a classical mathematical model that describes the transient mono-dimensional transport of water in food to estimate Deff . Under the experimental conditions examined, the Deff, was found to range from 1.13.10−10 to 5.65.10−10 m2/s. Shrinkage modelling revealed a non-linear dependence of food sample volume on the foods moisture content. In addition, while the apparent density of the food did not change appreciably during the first period of drying, a marked decrease was observed during the final drying period.

Transport Phenomena Modeling During Drying of Shrinking Materials

Different kind of materials are usually submitted to drying. In some cases the aim is to decrease their transportation costs in some others to preserve materials from deterioration. The latter is the case of foods drying. Foods usually exhibit changes in shape and dimensions (known as shrinkage) during drying caused by water loss. The aim of the present work is the modeling of the transport phenomena involved in drying process accounting for also the shrinkage effects. The simultaneous transfer of momentum, heat and mass occurring in a convective drier where hot dry air flows about the food sample have been modeled. The system of non-linear unsteady-state partial differential equations modeling the process has been solved by means of Finite Elements Method coupled to the ALE (Arbitrary Lagrangian Eulerian) procedure that, by a proper modification of integration domain, accounts for shrinkage effects. The model proposed is suitable for industrial equipment optimization.