Estudo da secagem de grãos em leito fixo, com e sem escoamento reverso do ar de secagem

Abstract

Attempting to contribute to the development of the drying process in fixed bed, this work has the objective of the experimental study on the drying of barley grains in fixed bed, without and with drying airflow reversal. The drying experiments consist of obtaining moisture content and temperature data as a function of time, evaluating the influence of the main process operating variables, such as initial moisture content of grain and drying air temperature. The bed's shrinkage of barley grain, exposed to different drying conditions, was evaluated and quantified to be incorporated in the mathematical modeling of the drying process. The drying experiments were performed in a fixed bed dryer, which operates with upward and downward airflow, allowing the drying process with airflow reversal. The experiments to determine the temperature and moisture content distribution, without and with airflow reversal, were performed and the results showed the presence of temperature and moisture content gradients inside the grain bed. It has also been observed that shrinkage of the grain bed during the drying process is strongly influenced by the initial moisture content of barley grains. It was found that the drying rate decreased with drying airflow reversal, but increased the homogeneity of the drying process, reducing the temperature and moisture content gradients in the bed. For the simulation of the temperature and moisture content profiles, a physical-mathematical analysis of the process was carried out, based on the two-phases model proposed by Massarani and Silva Telles (1992) for fixed bed, with incorporation of shrinkage phenomenon and temperature of mixture (fluid-solid). The equations of the model were solved by the method of lines in MatLab software R2015a. The predicted data compared to the experimental values showed good agreement, with relative average errors ranging from 1,0 to 13,6%, showing that the model is promising to predict the drying variables , but should be improved.