Turbulent Transport in Wall Turbulence

PI将对壁面湍流中的标量输运（如污染物或热能）以及普朗特（或施密特）数对近壁和色散行为的影响进行计算研究。本研究的核心将是直接数值模拟（DNS）的发展，与朗日标量跟踪（LST）相结合，用于生成数值数据和开发描述性模型。该项目将结合高性能计算的先进技术，对各种流体系统湍流中的传热和传质进行详细研究。中心问题是预测湍流输运性质的空间变化，分子普朗特数对湍流输运的影响以及边界条件对标量输运的影响。本工作的创新之处在于：(a)利用直接数值模拟（DNS）产生的流体力学来生成湍流色散的拉格朗日数据；(b)发展了用于研究恒应力区输运的平面Couette流模拟；(c)在拉格朗日框架下研究湍流中的化学反应。研究结果如果成功，将对各种实际的传热传质问题（热交换、混合、反应堆流动、涡轮叶片冷却、污染物在大气中的扩散）产生影响。这项工作还将促进高性能计算技术的应用，使DNS更具可评估性和成本效益，并可能导致在其他重要物理问题中研究标量传输的能力，例如非常小规模流的传输。已经制定了具体计划，将HPC引入俄克拉何马大学化学工程课程，并将HPC引入将在工作的不同阶段参与研究的本科生。

The PI will undertake a computational study of scalar transport (e.g., contaminants or thermal energy) in wall turbulence and the influence of Prandtl (or Schmidt) number on near-wall and dispersion behavior. Central to this study will be the development of Direct Numerical Simulation (DNS) in conjunction with Langrangian Scalar Tracking (LST) for the generation of numerical data and the development of descriptive models. The program will incorporate advances in High Performance Computing to allow the detailed investigation of heat and mass transfer in turbulent flow for a variety of fluid systems. Central concerns are the prediction of the spatial variation of turbulent transport properties, the effect of molecular Prandtl number on turbulent transport and the effect of boundary conditions on the scalar property transport. The innovations of the present work are (a) the use of hydrodynamics generated by a Direct Numerical Simulation (DNS) to generate Lagrangian data for turbulent dispersion; (b) the development of plane Couette flow simulations for the study of transport in the constant stress region; and (c) the study of chemical reaction in turbulence in the Lagrangian framework. The results, if successful, will have impact on a variety of practical heat and mass transfer problems (heat exchange, mixing, reactor flows, turbine blade cooling, pollutant dispersion in the atmosphere). The work will also foster the application of HPC technology in ways that will make DNS more assessable and cost effective, and potentially will lead to the ability to study scalar transport in other important physical problems, such as transport in very small-scale flows. Specific plans have been laid out to introduce HPC to undergraduate students who will participate in the research at different stages of the work and through the introduction of HPC into the curriculum of Chemical Engineering at the University of Oklahoma.