Improved computational models for particle transport in turbulent wall-bounded flows

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The proposed research program will improve our knowledge of gas-solid flows and enhance our ability to numerically predict their behavior. Many engineering applications involve the transport of particles within a gas or liquid. Agricultural equipment such as air-seeders use pneumatic transport to distribute seeds and granular fertilizer, and fluidized beds are used in processing granular potash. Environmental applications include sediment transport in rivers and coastal waters. These flows are typically turbulent, which means that the velocity field includes a fluctuating component that varies in time and space. The ability to accurately predict the particle behavior within a turbulent flow field is required to optimize the performance of such systems.     Computational fluid dynamics (CFD) uses numerical methods to solve the velocity field in a flow. For design purposes, CFD can be used to model particle transport in different ways. The simplest approach is to track the individual particle trajectories and use them to characterize the particle flow; however, for large numbers of particles - millions or billions - this approach becomes less efficient. An alternate strategy is to model the particles as a pseudo-fluid that co-exists with the carrier fluid. In both cases, the particle transport is strongly affected by the turbulence in the fluid, which is itself extremely difficult to predict.     The proposed research program uses both approaches to investigate three different applications of particle transport. The first application is pneumatic transport of seeds within an air-seeder. The research program will develop improved predictions for the distribution of particles within a complex duct system and the pressure required to transport them. One concern in pneumatic transport is the damage caused by the collision of seeds with the pipe walls. The second application looks at how solid particles are transported in a liquid, where the presence of the liquid modulates the particle collisions with each other. One application of liquid-particle flows is the pipelining of solids in the mining industry; safe pipeline design requires the ability to predict particle deposition and potential plugging of the line. The third application considers gas-particle flow within a fluidized bed. In fluidized beds, the particles are mixed by injecting a gas that flows upward through the particle bed as discrete bubbles. The proposed research will develop simpler models for predicting and controlling the large-scale mixing in such beds. Overall, the proposed research program will advance our understanding and predictive capability for particle transport in a fluid. The insight obtained will benefit various industries in Canada by improving their design capability. In addition to enhanced equipment performance, the design improvements will result in better utilization of scarce energy resources and a reduction in adverse environmental impacts.