Experimental Energy Studies and Artificial Neural Network Modeling For Continuous Wall Heated Fluidized Bed Dryer

Now a days, scope of research has increased on energy studies due to shortage for fuel inputs. Fluidized bed dryers are prominent among efficient moisture removal equipments in food, pharmaceutical and particle based industries. Various food, pharmaceutical, cement and solid handling industries have adopted continuous fluidized bed drying technique due to its advantages like efficient heat transfer, good moisture removal rate and good solid-gas mixing due to continuous inputs. To optimize the energy consumption it is important to consider energy utilization ratio of any process equipment. From the literature review, it has been observed that only few studies were done on energy analysis of dryers. In the present study, experiments were carried out to determine the drying characteristics and energy utilization ratio of continuous wall heated fluidized bed dryer varying operating conditions like wall temperature from 40 to 60 degrees C, air velocity from 1.01 to 1.7 m/s and solids flow rate from 5 to 10 kg/h. For predicting the energy utilization ratio, artificial neural network (ANN) model was developed using experimental data. (C) 2019 Elsevier Ltd. All rights reserved.