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: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=523369
• 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

这项研究致力于发展数学模型来预测颗粒在气体湍流中的运动。这一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雾剂给药系统的设计。计算流体动力学(CFD)越来越多地被用来帮助分析这些流动，并有助于改进工程设计的发展。在这种流动中遇到的复杂几何形状和通常较高的雷诺数需要使用雷诺平均N-S(RANS)模型，因为与大涡模拟(LES)或直接数值模拟(DNS)相关的高计算量排除了这些方法在大多数工程应用中的使用。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，但又足够简单，可以合并到标准的CFD代码中，