Large-eddy simulation of smooth and rough-wall turbulent boundary-layer flows at arbitrary Reynolds numbers

湍流流体动力学现象的大规模计算模拟将继续对科学和工程的许多不同领域产生巨大影响 范围从行星地球的气候建模，到环境流体动力学以及大雷诺数下的工业和工程应用。 理想的是直接数值模拟（DNS），其中所有相关的物理过程都得到适当的表示，所有的长度尺度都在数值模拟中得到解决。 然而，在许多工程应用所需的极端雷诺数下， 在可预见的未来不大可能切实可行。标准的工程预测工具是雷诺平均模型（RANS）。虽然RANS将仍然适用于许多应用，但在工程开发工作中，越来越需要更详细但计算上易于处理的数值模拟能力。例子包括内部管道流和外部流线型和钝体流，其中湍流边界层动力学的物理真实建模，包括过渡，曲率，分离和雷诺数效应，需要准确的预测。大涡 仿真 (LES)其中大尺度湍流运动在计算网格上被解析，而小的、未解析的涡流的影响被建模，是介于RANS和DNS之间的。LES已经非常成功地在各种设置的自由剪切和混合湍流。在无界流中，大涡携带大部分湍流动能，主导动量传输，并设定了影响小尺度湍流动力学的长度和时间尺度。这幅图在光滑或粗糙的墙壁附近发生了逆转，其中能量最丰富的漩涡必然是小规模运动的一部分。 因此，尽管经过几十年的努力，壁面湍流的精确数值预测仍然是计算流体力学的一个具有挑战性的领域。 本研究的主要目标是建立一个强大的LES能力，为壁面有界流动， 该项目的目标是发展一种用于壁面湍流大涡模拟的亚网格尺度方法，重点是在存在有利和不利压力梯度、壁面曲率、层流-湍流转捩和基本上任意大雷诺数的流动分离的情况下，应用于空间演变的光滑或粗糙壁面湍流边界层流动。新的元素是一个亚网格尺度的壁模型，基于壁法线积分的流向动量方程，使动态计算的壁面剪应力，而不需要近壁尺度分辨率，但它结合了局部表面粗糙度，壁法线动量输运和压力梯度效应。 从这项工作中产生的LES建模将可用于纳入一般的计算流体动力学代码。预计这将提供一个显着的进步，我们的能力，在非常大的雷诺数的复杂湍流的数值模拟。这项研究将成为研究生个人教育和培养的重要组成部分。此外，这项工作将通过参与K-12外展计划来支持现代计算工程技术的概念和应用的传播。

The large-scale, computational simulation of turbulent fluid-dynamical phenomena will continue to have an enormous impact on many diverse areas of science and engineering ranging from climate modeling of planet earth, to environmental fluid dynamics and to industrial and engineering applications at large Reynolds numbers. The ideal is direct-numerical simulation (DNS) in which all relevant physical processes are properly represented and all length scales are resolved within numerical simulation. At the extreme Reynolds numbers required for many engineering applications, however, full DNS is unlikely to be practicable within the foreseeable future. The standard engineering prediction tool has been Reynolds-averaged modeling (RANS). Whilst RANS will remain useful for many applications, there exists a growing need for a more detailed but computationally tractable numerical simulation capability in engineering development work. Examples include internal pipe flows and external streamlined and bluff-body flows where physically realistic modeling of turbulent boundary-layer dynamics including transition, curvature, separation and Reynolds-number effects is required for accurate prediction. Large-eddy simulation (LES), where the large scales of turbulent motion are resolved on the computational grid while the effects of small, unresolved eddies are modeled, is intermediate between RANS and DNS. LES has been very successful for free-shear and mixing turbulence in a wide variety of settings. In unbounded flows, the large eddies carry most of the turbulent kinetic energy, dominate momentum transport and set the length and time scales that condition the small-scale turbulence dynamics. This picture is reversed near a smooth or rough wall, where the most energetically productive eddies are necessarily part of the small-scale motion. Hence despite decades of effort, the accurate numerical prediction of wall-bounded turbulent flows remains a challenging area for computational fluid dynamics. The broad objective of the present research is to construct a robust LES capability for wall-bounded flows at Reynolds-numbers typical of practical engineering interest.The project will aim to develop a subgrid-scale methodology for LES of wall-bounded turbulence with emphasis on application to spatially evolving smooth or rough-wall turbulent boundary-layer flows in the presence of favorable and adverse pressure gradients, wall curvature, laminar-turbulent transition and flow separation at essentially arbitrarily large Reynolds numbers. The novel element is a subgrid-scale wall model, based on a wall-normal integration of the stream-wise momentum equation, which enables dynamical calculation of the wall shear stress without requiring near-wall scale resolution, but which incorporates local surface roughness, wall-normal momentum transport and pressure-gradient effects. The LES modeling resulting from this work will be available for incorporation into general computational fluid-dynamics codes. It is expected that this will provide a significant advance in our capability for the numerical simulation of complex turbulent flows at very large Reynolds numbers. The research will form an important part of the education and training of individual graduate students. Additionally the work will support dissemination of the concepts and applications of modern computational engineering technology through participation in K-12 outreach programs.