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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=657616
• 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. ******************

本研究系关于发展数学模式以预测气体紊流中微粒之运动。这个问题与许多工程应用有关，包括液体燃料液滴的燃烧、大气中的污染物扩散以及药物气雾剂药物输送系统的设计。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。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雷诺平均Navier-Stokes（RANS）建模，因为与大涡模拟（LES）或直接数值模拟（DNS）相关的高计算工作量排除了大多数工程应用中使用这些方法。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，优先浓度，湍流各向异性和不均匀性必须考虑在数学模型。 **** 拟议的研究将侧重于使用载有颗粒的DNS进行RANS模型开发。 这些模拟将提供相关的时间和长度尺度（拉格朗日跟踪模型的改进至关重要）的信息，也将提供洞察粒子与湍流的相干结构的相互作用的物理。 LES也将用于考虑更高雷诺数的流动。将注意评估粒子运动亚网格尺度模型的影响。 还将研究颗粒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。******************