New Development in Computational Physics of Turbulence

湍流计算物理新进展

基本信息

批准号：
17340117
负责人：
KANEDA Yukio
金额：
$ 9.63万
依托单位：
Nagoya University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2005
资助国家：
日本
起止时间：
2005 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17340117/
关键词：
Turbulence Direct Numerical Simulation Universality in Statistics Intermittency Reduction of Information Wavelet Analysis Wall Bounded Turbulence Numerical Scheme エネルギー散逸率秩序渦成分乱流境界層数値計算法 Wavelet Coherent成分 Sinc法乱流の統計的法則 /

项目摘要

The achievements of this project include the following.1.Universality in the Statistics of Turbulence :(1) We studied the small scale statistics of turbulence by using the data of DNS with the world's highest resolution. The analysis showed that the DNS does not support assumptions commonly used in phenomenological theories of intermittency of turbulence.(2) An evidence supporting the Loitsyansky hypothesis on universality of large scale statistics in freely decaying turbulence was presented by DNS in a computation domain which is the largest in the DNSs so far made.2.Reduction of Information to be treated :(1) The analysis of the statistics of the energy transfer from large to small scales by using the data of 1-(1)clarified the dependence of the statistics on the method and scale of the coarse graining.-(2) The wavelet-analysis of the statistics of the coherent and incoherent modes of turbulence by using the data of 1-(1)showed that the ratio of the numbers of the coherent modes to that of the total modes decreases with the Reynolds number.3.Wall bounded turbulence :New numerical schemes for DNS of wall bounded turbulence were proposed, and compared with conventional ones. A scheme was shown to be promising in view of the accuracy and cost performance for DNS of boundary layer turbulence. The feasibility of -DNS of the inertial subrange in a turbulent channel flow was examined on the basis of our understanding of the physics.The achievements of 1 and 2 were possible only by DNS at the level of our study, and provide us with sound basis for developing turbulence theory and modeling. The finding in 3 should be useful for very large scale DNS of wall bounded turbulence. They contribute to the understanding of turbulence by computational approaches.

本课题取得的成果如下： 1.湍流统计的普适性：(1)利用世界上最高分辨率的DNS数据，研究了小尺度湍流的统计。分析表明，DNS 不支持湍流间歇性现象学理论中常用的假设。(2) DNS 在计算域中提出了支持自由衰减湍流中大规模统计数据普遍性的 Loitsyansky 假设的证据，该假设是2.减少需要处理的信息：(1)利用以下数据对从大尺度到小尺度的能量转移进行统计分析1-(1)阐明了统计量对粗粒化方法和尺度的依赖性。-(2)利用1-(1)的数据对湍流的相干和非相干模态的统计量进行小波分析结果表明，相干模数与总模数之比随着雷诺数的增加而减小。 3.壁界湍流：提出了壁界湍流DNS的新数值格式，并且与传统的相比。考虑到边界层湍流 DNS 的准确性和性价比，该方案被证明是有前途的。基于我们对物理学的理解，检验了湍流通道流中惯性子范围的-DNS的可行性。1和2的成就只有在我们研究水平上的DNS才有可能实现，并为我们提供了良好的基础用于发展湍流理论和建模。 3 中的发现对于壁边界湍流的超大规模 DNS 应该有用。它们有助于通过计算方法理解湍流。