Numerical Simulation of Corn Drying in a Hybrid Fluidized Bed‐Infrared Dryer

Abstract

AbstractThis study deals with numerical modeling and experimental validation of hybrid fluidized bed‐infrared drying of bulk grain. A mathematical model of simultaneous heat and mass transfer for the aforementioned dryer was developed: first single phase model was used to establish heat and mass transfer equations over the fluidized bed, then the effect of infrared heating was incorporated into the single phase model as a source term to develop the model for a hybrid fluidized bed‐infrared dryer. The model is capable of predicting the moisture content of bulk corn as well as the drying air parameters (i.e., out let air temperature and out let air absolute humidity) during drying. The model was validated by comparison with experimentally obtained drying kinetics for different combinations of inlet air temperature, infrared power density and bed height. The results of verification test for all drying conditions indicated that the mean relative deviation for prediction of grain moisture content, out let air temperature and absolute humidity were less than 8, 11 and 7%, respectively, which reflects an acceptable accuracy (<15%). Other results showed that the application of infrared power in conjunction with fluidized bed drying to reduce corn moisture content from 0.23 to 0.12 kg H2O/kg dry solid led to a 45–87% saving in drying time and 36–68% saving in specific energy consumption compared to conventional fluidized bed configurations. The model indicated acceptable performance and hence the model could be suggested as a mathematical tool providing precise prognostications dealing with fluidized bed drying equipped with infrared heat source.Practical ApplicationsThe suggested model is an efficient method to simulate drying process of bulk grain in infrared‐fluidized bed dryers. This model provides precise prognostications regarding the variations in grain moisture content, gas temperature and gas absolute humidity. Additionally the features of the model introduced in the present study might qualify it for use in automatic control of fluidized bed dryers and online prediction of drying time to reach a desired value of moisture content.