Modeling Turbulent Multiphase Flow in Nut Harvesters to Reduce the Dust Emission with Low Power Demand.

摘要

Particulate dust emission (e.g., PM10) has affected both the environment and agricultural practices in the San Joaquin Valley, California. Almond harvesting is cited as the highest dust-discharging field crop agricultural activity in this region. This work aimed to mitigate particulate dust emission, while maintaining the quality of nut products through the modification of the nut harvester using Computational Fluid Dynamics (CFD) modeling. In addition, modeling work also aimed to decrease excessive power demand of the nut harvester by reducing total pressure drop of the system.;Based on physical measurements, the Reynolds number of the gas-particle flow in the nut harvester was 105-106 at most locations and the particle volume fraction was 0.24%. The Realizable k-epsilon (RKE) and the Reynolds Stress Models (RSM) were applied to solve the turbulent gas flows, and the Stochastic Lagrangian Discrete Phase Model was used to solve the particle trajectories.;The predictions of the CFD models were validated by comparing with experimental results of the gas flows (i.e., velocity, static and dynamic pressure) as well as the particle collection characteristics. The velocity and pressure were measured using static and differential pressure probes, and a hot-film anemometer. In addition, the particle collection was measured with both gravimetric and opacity devices. Once validated, the CFD models were used to determine the critical design parameters and to guide the modification of the nut harvester.;Overall, the CFD models provided reasonable predictions for the gas flow fields, while additional validation experiments were still required for the particle flow model due to very high standard deviation of the experimental data. However, the statistical analysis of the particle effects implied that the Stochastic Lagrangian Discrete Phase Model was practical for predicting the particle flows in the nut harvester. Thus, some interesting results of the particle flows, which may be useful for field practices and for developing a retrofit technology to further reduce the fine particles, will also be presented.;Results suggested the importance of external geometry modification in reducing the total pressure drop by eliminating backflow and flow separation. Based on the results, this could reduce pressure drop as much as 61% depending on the gas flow rate. A slight change in the external geometry can significantly affect the gas flow fields in the nut harvester. In addition, the CFD model prediction showed that it improved the particle collection without excessive pressure drop and power demand. The application of the internal components (e.g., airfoil and reflector) was also shown to improve the particle collection. Moreover, the results also implied that the application and design of the separating chamber had a significant influence on the collection efficiency of large particles.;The CFD model prediction also indicated that the particle collection was improved with increasing gas flow rate. However, there was a threshold to this gas flow rate and it was shown to vary for each harvester design. It was also indicated that improving the particle collection by increasing the gas flow rate came at the cost of increased total pressure drop. In addition, the results indicated that the collection efficiency was increased with the particle sizes.;The CFD model prediction showed that the centrifugal force, around the semicircular section and in the transversal swirl tube, provided effective particle separation. However, this work has demonstrated that it is aerodynamically difficult or practically infeasible to collect substantial amounts of fine particles by applying solely this technique. Nevertheless, the technique is important in the pre-separation process of the particles in the nut harvester and may be useful for the application of a retrofit gas-solid separation technology to efficiently remove very fine particles from the harvester's discharge.