摘要
In this present work, the fluidynamic and drying process of skimmed milk in conical and conical-cylindrical spouted bed was analyzed as a function of different bed geometry and operating conditions. It used three internal cone angles (45°, 60° and 75°), different loads of inert particles (1.50, 3.00 and 4.50 kg) and a fixed static bed height (20.50 cm). Polyethylene particles of 4.38 mm of diameter and 930.50 ± 0.3 kg/m3 of specific mass were used as inert particles. An artificial neural network model was trained to predict the peak pressure drop and the minimum spout velocity from an experimental data bank. The experimental results showed a significant effect of geometric characteristics of the bed on fluidynamics parameters. It was also observed for the operating conditions that conical spouted bed and cone angle of 45° were more suitable for drying skimmed milk. The neural network provided predictions in good agreement with experimental data.
In this present work, the fluidynamic and drying process of skimmed milk in conical and conical-cylindrical spouted bed was analyzed as a function of different bed geometry and operating conditions. It used three internal cone angles (45°, 60° and 75°), different loads of inert particles (1.50, 3.00 and 4.50 kg) and a fixed static bed height (20.50 cm). Polyethylene particles of 4.38 mm of diameter and 930.50 ± 0.3 kg/m3 of specific mass were used as inert particles. An artificial neural network model was trained to predict the peak pressure drop and the minimum spout velocity from an experimental data bank. The experimental results showed a significant effect of geometric characteristics of the bed on fluidynamics parameters. It was also observed for the operating conditions that conical spouted bed and cone angle of 45° were more suitable for drying skimmed milk. The neural network provided predictions in good agreement with experimental data.
