Modeling Turbulent Flow for Design of Almond Harvesters with Low Power Demand and Reduced Emission of Particulate Material

摘要

Particulate air pollution is a serious problem in the San Joaquin Valley of California. Almond harvesting has been cited as the highest dust-discharging field crop agricultural activity in the San Joaquin Valley, the largest almond producer in the United States. Almonds and other nuts are harvested by collecting them from the orchard floor and pneumatically separating them from other orchard debris. In current industrial gas-particle separating devices, significant power is required due to the high pressure drop necessary to sufficiently separate fine particles from the flow. For mobile equipment, the power and size demands prohibit most conventional designs. In this project Computational Fluid Dynamic (CFD) modeling was applied to improve a nut harvester design to reduce the emission of particulate matter while maintaining the quality of the nut product. CFD modeling provided a convenient way to optimize the essential parameters with significantly lower cost than physical prototyping. This paper presents a numerical study of gas-particle flow using Realizable k-e Model to simulate the gas flow and Stochastic Lagrangian Discrete Phase Model to track the particles using a commercial CFD product. The simulated results were validated with the experimental measurements on a harvester. The results show a good agreement between the simulated and the measured values of pressure and velocity.