Multi-scale Predictive Simulation Methods for Turbulent Flow

湍流多尺度预测模拟方法

• 批准号: 0651754
• 负责人: Dale Pullin
• 金额: $ 24.97万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0651754&HistoricalAwards=false
• 关键词: Multi; scale; Predictive; Simulation; Methods

CBET- 0651754Dale I. Pullin This study will develop our capability for the predictive, numerical simulation of turbulent flows in several new directions. The goal is to both extend the present paradigm of conventional large-eddy simulation (LES) to span length/time scales from the energy-containing range to the Kolmogorov and Batchelor scales, for some turbulence statistics, and also to tackle the formidable near-wall problem in sub-grid-scale modeling. The work to be performed will extend the stretched-vortex (SV), subgrid-scale (SGS) model to multi-scale LES (MSLES) across almost the full-range of active length and time scales in turbulent flow, for some transport statistics. The aim is to move present LES-like methodology substantially closer to the ideal of DNS (direct numerical simulation). The study will develop algorithms that couple stretched-vortex solutions of the Navier-Stokes equations both as a basis for LES, and as a comprehensive model of turbulent fine scales, to produce an MSLES capability. This coupling should enable continuation of the statistics of several turbulent mixing flows from resolved to subgrid scales. Applications will comprise several canonical turbulent flows including decaying turbulence, passive-scalar mixing in the presence of a mean density gradient and variable-density turbulent mixing. For this last class of flows, direct-numerical simulation (DNS) runs will also be performed for validation of the MSLES. While not expecting true point- and time-wise DNS resolution, the MSLES methodology can provide a substantial improvement in the prediction of many turbulent statistics, particularly for turbulent mixing flows, over conventional LES techniques. The study will also further develop, test and apply a subgrid-scale approach designed specifically for the near-wall region of wall-bounded turbulent flows, a major roadblock to our capability for predictive simulation of turbulent flows. Two new concepts have been formulated. The first consists of a special near-wall, subgrid-scale element that is based on the idea of local inner scaling combined with wall-normal averaging and wall-parallel filtering. The second is an extension of the stretched-vortex, SGS-flux formalism, to model the principal dynamical behavior of near-wall, longitudinal vortices in their wall-normal transport of streamwise momentum. The method will implement boundary conditions at a virtual wall positioned at the lower limit of the log-law region. The viscous sublayer is not resolved. Intellectual merit: This study will provide a physically-based, analytical framework for the extension of conventional LES to both multiscale LES, and to the solution of the near-wall, subgrid-scale modeling problem. The paradigm of large-scale fluid-dynamical simulation has had an enormous impact on many diverse areas of science and engineering applications over a large range of Reynolds numbers.Broader impact: This research will extend capability to perform multi-dimensional, numerical simulations of complex fluid behavior. MSLES will provide some measure of DNS-like fidelity in numerical simulation but at a small fraction of the DNS cost in computational resources. With the continued explosion in the availability of desktop computing power, we expect this style of simulation to become readily available at the engineering application level within a decade.

CBET-0651754戴尔岛这项研究将发展我们在几个新方向上对湍流进行预测和数值模拟的能力。我们的目标是既要扩展现有的常规大涡模拟（LES）的范式，以跨越长度/时间尺度从含能范围的Kolmogorov和Batchelor尺度，为一些湍流统计，也要解决强大的近壁问题，在亚网格尺度建模。要执行的工作将扩展拉伸涡（SV），亚网格尺度（SGS）模型，多尺度LES（MSLES）在几乎整个范围内的活动长度和时间尺度的湍流，一些运输统计。我们的目标是移动本LES类方法大大接近理想的DNS（直接数值模拟）。这项研究将开发的算法，耦合拉伸涡解的Navier-Stokes方程作为LES的基础，并作为一个全面的湍流细尺度模型，产生MSLES的能力。这种耦合应使几个湍流混合流的统计数据，从解决亚网格尺度的延续。应用将包括几个典型的湍流，包括衰减湍流，被动标量混合的平均密度梯度和变密度湍流混合的存在。对于最后一类流动，还将进行直接数值模拟（DNS）运行，以验证MSLES。虽然不期望真正的点和时间明智的DNS分辨率，MSLES方法可以提供大量的改进，在许多湍流统计的预测，特别是湍流混合流，在传统的LES技术。这项研究还将进一步开发，测试和应用亚网格尺度的方法，专门为近壁区的壁边界湍流，一个主要的障碍，我们的能力预测模拟湍流。提出了两个新概念。第一个由一个特殊的近壁，subgrid-scale元素，这是基于局部内部缩放结合壁正常平均和壁平行滤波的想法。第二个是延伸涡，SGS通量形式主义，模拟近壁，纵向涡在其壁正常的流向动量传输的主要动力学行为。该方法将在位于对数律区域下限的虚拟壁处实现边界条件。粘性子层未被解析。智力优点：这项研究将提供一个物理为基础的，分析框架的扩展，传统LES的多尺度LES，并解决近壁，亚网格尺度建模问题。大规模流体动力学模拟的范例在大范围的Reynolds.Broader影响的科学和工程应用的许多不同的领域产生了巨大的影响：这项研究将扩展能力，执行多维，复杂的流体行为的数值模拟。MSLES将在数值模拟中提供一些类似DNS的保真度，但在计算资源中的DNS成本的一小部分。随着桌面计算能力的持续爆炸式增长，我们预计这种风格的模拟将在十年内在工程应用层面变得可用。