Mathematical modelling of particle-laden turbulent flows

含颗粒湍流的数学建模

• 批准号: 203162-2012
• 负责人: Lightstone, Marilyn
• 金额: $ 1.89万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=569883
• 关键词: Mathematical; modelling; particle; laden; turbulent

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.

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，以捕捉颗粒/湍流相互作用的基本物理特性，但又足够简单，可以纳入标准的CFD代码