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

拟议的研究计划将提高我们的知识，气固流动，提高我们的能力，数值预测其行为。许多工程应用涉及气体或液体中颗粒的输送。农业设备，如空气播种机使用气动输送来分配种子和颗粒肥料，流化床用于处理颗粒钾肥。环境应用包括河流和沿海沃茨的沉积物输送。这些流动通常是湍流，这意味着速度场包括随时间和空间变化的波动分量。为了优化这种系统的性能，需要精确预测湍流场中的颗粒行为的能力。 计算流体动力学（CFD）使用数值方法来求解流中的速度场。出于设计目的，CFD可用于以不同方式模拟颗粒传输。最简单的方法是跟踪单个粒子的轨迹并使用它们来表征粒子流;然而，对于大量粒子（数百万或数十亿），这种方法变得不那么有效。另一种策略是将颗粒建模为与载体流体共存的伪流体。在这两种情况下，颗粒的传输都受到流体中湍流的强烈影响，而湍流本身是极难预测的。 拟议的研究计划使用这两种方法来研究粒子传输的三种不同应用。第一个应用是在气播机内气动输送种子。该研究计划将改进对复杂管道系统内颗粒分布的预测，以及运输它们所需的压力。气力输送中的一个问题是种子与管壁碰撞造成的损坏。第二个应用程序着眼于固体颗粒如何在液体中传输，其中液体的存在调节颗粒相互碰撞。液体-颗粒流的一个应用是采矿业中固体的管道输送;安全的管道设计需要能够预测颗粒沉积和管道的潜在堵塞。第三种应用考虑流化床内的气体-颗粒流动。在流化床中，颗粒通过注入气体而混合，该气体作为离散气泡向上流过颗粒床。拟议的研究将开发更简单的模型来预测和控制这种床中的大规模混合。总的来说，拟议的研究计划将提高我们对流体中颗粒输运的理解和预测能力。所获得的见解将有利于加拿大的各个行业，提高他们的设计能力。除了提高设备性能外，设计改进还将导致更好地利用稀缺的能源，减少对环境的不利影响。

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.