Turbulence intensity and distribution in rough rice bin drying and storage system with new “cabling” technology

Abstract.

The new on-farm in-bin drying and storage system are equipped with network of sensors to monitor air conditions throughout the bin. However, the performance of sensors may be impaired by turbulent flow of the air through the grain mass. Computational fluid dynamic (CFD) simulation allows obtaining a more detailed view of fluid flow around the sensors. Hence, the objectives of this work are to investigate the potential of turbulence generation around the sensors and the potential of the intensity to impair sensor performance. A finite volume method with porous media formulation was employed to simulate the turbulent airflow. The turbulence intensities predicted from different turbulence models (k − ε model, k − model and the Reynolds stress model (RSM)) were investigated and the result of airflow rates of 1.1 m³ min⁻¹[air] t⁻¹ [rice] is presented. The results revealed that the turbulence models predicted a low to medium turbulence with intensities ranging between 1% and 2%. Sensors closer to the plenum experienced about 100% increase in turbulence intensities compared to the sensor closer to the outlet area. It can be concluded that sensors closer to the plenum be built to withstand medium scale turbulence flow.