Mathematical modelling of particle-laden turbulent flows

这项研究是关于数学模型的发展，以预测气体湍流中颗粒的运动。这个问题与许多工程应用有关，包括液体燃料液滴的燃烧，大气中的污染分散以及药物气溶胶给药系统的设计。计算流体动力学（CFD）越来越多地用于帮助分析这些流动，并有助于改进工程设计。由于大涡模拟（LES）或直接数值模拟（DNS）的高计算量使得这些方法无法在大多数工程应用中使用，因此在这种流动中遇到的复杂几何形状和典型的高雷诺数需要使用Reynolds平均Navier-Stokes （RANS）模型。因此，有必要开发数学模型来捕捉颗粒/湍流相互作用的基本物理特性，并且足够简单，可以纳入使用RANS方法的标准CFD代码中。这个问题是具有挑战性的，因为许多物理现象，如湍流调制，优先集中，湍流各向异性和非均匀性必须在数学模型中考虑。****建议的研究将侧重于使用粒子负载DNS进行RANS模型开发。这些模拟将提供相关时间和长度尺度的信息（对改进拉格朗日跟踪模型至关重要），并且还将提供对颗粒与湍流相干结构相互作用的物理见解。LES还将用于考虑更高雷诺数的流动。要注意评估子网格尺度建模对粒子运动的影响。还将研究粒子通过衰减和增强湍流动能对流体湍流的影响，并进行仔细的验证。******************

This research is concerned with the development of mathematical models to predict the motion of particulates in a gaseous turbulent flow. This problem is relevant to many engineering applications including the combustion of liquid fuel droplets, pollution dispersion in the atmosphere, and the design of pharmaceutical aerosol drug delivery systems. Computational fluid dynamics (CFD) is used increasingly to aid in the analysis of these flows and is useful for development of improved engineering designs. The complex geometries and typically high Reynolds numbers encountered in such flows necessitate the use of Reynolds Averaged Navier-Stokes (RANS) modelling since the high computational effort associated with large eddy simulation (LES) or direct numerical simulation (DNS) precludes the use of those methods for most engineering applications. It is thus necessary to develop mathematical models that capture the essential physics of the particulate/turbulence interactions, and yet are simple enough to be incorporated into standard CFD codes that**use RANS methodologies. The problem is challenging since numerous physical phenomena such as**turbulence modulation, preferential concentration, turbulence anisotropy and inhomogeneity must be accounted for in the mathematical models. ****The proposed research will focus on using particle-laden DNS for RANS model development. These simulations will provide information on correlation time and length scales (critical for improvement of Lagrangian tracking models) and will also provide insight into the physics of the interaction of the particulates with the coherent structures of the turbulence. LES will also be used to allow for higher Reynolds number flows to be considered. Care will be taken to assess the effect of the subgrid scale modelling on the particle motion. The effects of the particles on the fluid turbulence, through both attenuation and enhancement of turbulent kinetic energy, will also be studied and careful validations performed. ******************