Nonlinear Fluctuating Hydrodynamics as Model for Turbulent Super-structures

非线性脉动流体动力学作为湍流上层建筑的模型

• 批准号: 316141967
• 负责人: Professor Dr.-Ing. Nikolaus Andreas Adams
• 金额: --
• 依托单位: Lehrstuhl für Aerodynamik und Strömungsmechanik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/316141967?language=en
• 关键词: Nonlinear; Fluctuating; Hydrodynamics; Model; Turbulent

Structures arising from self-organization in turbulence with length and time scales significantly larger than those characteristic for the turbulent fluctuation field can be classified as superstructures. Such structures may have far-reaching effects in promoting or preventing mixing in engineering applications involving, or in atmospheric physics. One may differentiate between large-scale structures enforced on a turbulent flow by boundary conditions or body forces, and large-scale structures that arise from nonlinear interactions across scales. It is an interesting question whether a lower-dimensional description is possible that reproduces the essential interactions. It has been observed in the past that thermal fluctuations in fluctuating hydrodynamics give rise to so-called giant fluctuations in a scalar-concentration field near a layer with a strong concen-tration gradient. With uniform concentration, i.e. a single fluid material, the mechanism for the occurrence of large-scale structures cannot be the same. Nevertheless, the question arises, whether a simple non-equilibrium stochastic mechanism can explain large-scale correlations in the momentum field, and how the presence of mean gradients, body forces, or boundary conditions affects their generation. The current project addresses this question and contributes to modeling the origin and dynamics of turbu-lent superstructures. We employ simple stochastic models for turbulent fluctuations and compare two model families with different ways of satisfying a fluctuation-dissipation balance. One is nLLNS (nonlinear Landau-Lifshitz Navier-Stokes equations). Although this model originally has been proposed for equilibrium configurations its applicability to non-equilibrium has been demonstrated. The other model is GLMEF (generalized Langevin model in Eulerian reference frame) which is a variant of nonlinear fluctuating hydrodynamics derived from the underdamped Langevin equation. GLMEF allows for more complex non-equilibrium effects than nLLNS. The plan for the 1st funding period has two main parts: (A) Qualification of GLMEF as model for a complex, wave-number dependent dissipation mechanism. Three-dimensional implementations and performance optimization of GLMEF and nLLNS codes for large-scale parallel computing. (B) Explorative simulations with imposed momentum and / or density gradient with an isothermal equation of state. Investigation of scale-effects in terms of gradient scales and domain scales. Comparison of the different stochastic models nLLNS and GLMEF. For the latter, investigation of different kernel esti-mators and thus different memory effects. For the former exploration of non-isothermal equation of state. In a 2nd funding period the predictive capability of the stochastic models in terms of long-range correlations in a non-equilibrium turbulence field will be compared with actual direct numerical simulations of turbulent shear flows.

长度和时间尺度在湍流中自组织产生的结构明显大于湍流波动场的特征。这种结构可能在促进或防止涉及或大气物理学的工程应用中混合的混合中具有深远的影响。一个人可能会区分边界条件或身体力量在湍流上​​强制执行的大规模结构，以及由跨尺度的非线性相互作用引起的大规模结构。这是一个有趣的问题，是否可能有可能重现基本相互作用的较低维度描述。过去曾观察到，在波动流体动力学中的热波动会导致在具有强浓度梯度的层附近的标量浓缩场中所谓的巨型波动。浓度均匀的浓度，即单个流体材料，发生大规模结构的机制不能相同。然而，出现的问题是，简单的非平衡随机机制是否可以解释动量领域中的大规模相关性，以及平均梯度，身体力或边界条件的存在如何影响其产生。当前的项目解决了这个问题，并有助于建模Turbu-Lent上层建筑的起源和动态。我们采用简单的随机模型来进行湍流波动，并比较了两个模型家族，这些模型家族具有不同的方式来满足波动隔离平衡。一个是NLLN（非线性Landau-Lifshitz Navier-Stokes方程）。尽管该模型最初是针对平衡构型提出的，但已证明其适用于非平衡性。另一个模型是Glmef（Eulerian参考框架中的广义Langevin模型），它是源自阻尼不足的Langevin方程的非线性波动流体动力学的变体。 GLMEF允许比NLLN更复杂的非平衡效应。第一个资金期间的计划有两个主要部分：（a）GLMEF作为复杂的，依赖波浪依赖的耗散机制的模型。 GLMEF和NLLNS代码的三维实现和性能优化，用于大规模并行计算。 （b）具有施加动量和 /或密度梯度的探索性模拟，具有等温状态方程。根据梯度尺度和域尺度研究量表效应的研究。不同随机模型NLLN和GLMEF的比较。对于后者，研究不同的内核埃斯蒂甲壳虫，从而研究了不同的记忆效应。对于以前对非等温州方程的探索。在第二个资金期间，将随机模型在非平衡湍流场中的远程相关性方面的预测能力与湍流的实际直接数值模拟进行比较。