Location: Healthy Processed Foods ResearchTitle: Mathematical and computational modeling simulation of solar drying Systems Author
Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 1/5/2017
Publication Date: 8/30/2017
Citation: Milczarek R.R., Alleyne F.S. (2017) Mathematical and Computational Modeling Simulation of Solar Drying Systems. In: Prakash O., Kumar A. (eds) Solar Drying Technology. Green Energy and Technology. p. 357-379 Springer, Singapore
Interpretive Summary: This chapter summarizes recent work on the application of mathematical and computer simulation models to sun drying of fruits, vegetables, nuts, herbs, and meat products. Mathematical models are developed to help predict how long a given material will take to dry in a given dryer under given environmental conditions. Computational models (2D or 3D computer simulations) also help predict drying times but also afford insights into the effects of the geometry of the dryer. The types, uses, and performance of several models are discussed in this chapter.
Technical Abstract: Mathematical modeling of solar drying systems has the primary aim of predicting the required drying time for a given commodity, dryer type, and environment. Both fundamental (Fickian diffusion) and semi-empirical drying models have been applied to the solar drying of a variety of agricultural commodities in several different dryer types (direct, indirect, and mixed-mode with both forced and natural convection). Computational modeling (i.e. computational fluid dynamics or CFD), both in 2-dimensional and 3-dimensional modes, affords insights on geometry-specific solar drying issues, such as airflow patterns within the drying cabinet. Both mathematical and computational modeling have recently been brought to bear on solar drying innovations such as thermal storage, use of dessicants during drying, and dynamic feedback control of the drying process. Robust models are also necessary for the performance evaluation and comparison of different dryer designs and configurations. The outputs of mathematical and computational models are compared with measured drying data (whether performed outdoors or with a solar simulator) to ensure the accuracy and efficacy of the model.