Prediction of Residence Time Distribution of Solid Wastes in a Rotary Dryer

Abstract

The residence time distribution (RTD) of heterogeneous citrus waste particles was determined in a semi-pilot-scale rotary dryer with concurrent flow under several operational conditions. The experimental methodology was based on the stimulus-response technique, which consisted of injecting pulse-like tracers in the dryer feed stream. Measurements of RTD were performed to build up experimental curves that were numerically integrated to provide the mean residence time. A perfectly-stirred-tank in series model and a neural network model were derived. In addition, empirical and semi-empirical correlations from the literature were used to estimate residence time and the influence of operating conditions on this variable was investigated.

Keywords:

• Dryer performance
• Drying
• Neural networks
• RTD
• Transport properties