Monte Carlo simulation of the collective behavior of food particles in pneumatic drying operation

Although most of the time drying operation aims at controlling the mean batch behavior, the quality of the final product is often related to the individual behavior of the supplied materials in a batch. The mean batch models provide limited information for quality evaluation studies. Since the initial physical and thermal properties of rice powder in a batch influence the final condition of product dried with a pneumatic dryer, a Monte Carlo simulation with initial random parameters is useful to investigate the individual behavior of rice particle during pneumatic drying. In this study, we analyzed the influence of initial moisture content and particle diameter of rice powder on the conditions of the final product in pneumatic drying process. Samples of initial moisture content and particle diameter distributions were generated by means of the covariance decomposition algorithm and Monte Carlo simulations with 5000 runs based on momentum, energy and mass balances between drying air and rice particles were performed to obtain the profiles of the response variables, rice powder temperature, moisture content and particle diameter, in a pneumatic dryer. The developed pneumatic conveying drying (PCD) model could describe the complex behavior of rice particles in a batch.