湍流中相干结构的扩展聚类网络建模

IF 2.2 3区 工程技术 Q2 MECHANICS Theoretical and Computational Fluid Dynamics Pub Date : 2024-10-25 DOI:10.1007/s00162-024-00723-z
Antonio Colanera, Johann Moritz Reumschüssel, Jan Paul Beuth, Matteo Chiatto, Luigi de Luca, Kilian Oberleithner
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引用次数: 0

摘要

本研究介绍了基于簇的扩展网络建模(eCNM),这是一种分析复杂流体流动的方法。eCNM 专注于描述特定子空间或变量子集内的动力学特征,为复杂的流动现象提供有价值的见解。我们利用 PIV 测量数据、围绕 OH* 化学发光波长滤波的 UV 图像(以热释放率分布为特征)以及喷射入口探头的压力信号等同步数据,演示了 eCNM 在非强制条件下漩涡火焰中的有效性,该火焰的特征是一个前冲漩涡核心 (PVC)。分析工作从选择粗粒化过程的距离度量和模型的簇数开始。为此,我们设计了一种基于滤波相关矩阵的滤波距离度量,并使贝叶斯信息准则(BIC)得分最小化,从而在模型的拟合度和复杂度之间取得平衡。基于速度波动的标准聚类网络模型可以确定聚氯乙烯的特征频率。热释放率扩展聚类中心点的构建揭示了一种旋转火焰模式,主要集中在受聚氯乙烯涡卷影响的区域。通过进行空间子域分析,展示了在流体系统中关注特定区域的好处,并显著节省了计算量。此外,eCNM 还可以处理不同数据集的不同采样频率。利用作为参考数据集的高分辨率压力测量值和作为采样不足数据的速度分量,即使人为降低速度采样频率,也能成功估算出速度的扩展聚类中心点。这项研究展示了 eCNM 的适应性和稳健性,它是理解和分析复杂流体流动中相干结构的重要工具。
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Extended cluster-based network modeling for coherent structures in turbulent flows

This study introduces the Extended Cluster-based Network Modeling (eCNM), a methodology to analyze complex fluid flows. The eCNM focuses on characterizing dynamics within specific subspaces or subsets of variables, providing valuable insights into complex flow phenomena. The effectiveness of the eCNM is demonstrated on a swirl flame in unforced conditions, characterized by a precessing vortex core (PVC), using synchronized data from PIV measurements, UV-images filtered around the OH* chemiluminescence wavelength, featuring the heat release rate distribution, and pressure signals from jet inlet probes. The analysis starts with choosing the distance metric for the coarse-graining process and the number of clusters of the model. This has been pursued by designing a filtered distance metric based on the filtered correlation matrix and minimizing the Bayesian information criterion (BIC) score, balancing the goodness of the fit of a model with its complexity. The standard cluster-based network model on the velocity fluctuations allowed for determining the characteristic frequency of the PVC. The construction of extended cluster centroids of the heat release rate reveals a rotating flame pattern, predominantly localized within regions influenced by PVC’s vortices roll-up. Spatial subdomain analysis is carried out, demonstrating the benefits of focusing on specific regions of interest within the fluid system and providing significant computational savings. Furthermore, eCNM allows for the handling of different sampling frequencies among datasets. Leveraging high-resolution pressure measurements as a reference dataset and velocity components as undersampled data, extended cluster centroids for velocity are successfully estimated, even when the velocity sampling frequency is artificially reduced. This study showcases the adaptability and robustness of eCNM as a valuable tool for comprehending and analyzing coherent structures in complex fluid flows.

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来源期刊
CiteScore
5.80
自引率
2.90%
发文量
38
审稿时长
>12 weeks
期刊介绍: Theoretical and Computational Fluid Dynamics provides a forum for the cross fertilization of ideas, tools and techniques across all disciplines in which fluid flow plays a role. The focus is on aspects of fluid dynamics where theory and computation are used to provide insights and data upon which solid physical understanding is revealed. We seek research papers, invited review articles, brief communications, letters and comments addressing flow phenomena of relevance to aeronautical, geophysical, environmental, material, mechanical and life sciences. Papers of a purely algorithmic, experimental or engineering application nature, and papers without significant new physical insights, are outside the scope of this journal. For computational work, authors are responsible for ensuring that any artifacts of discretization and/or implementation are sufficiently controlled such that the numerical results unambiguously support the conclusions drawn. Where appropriate, and to the extent possible, such papers should either include or reference supporting documentation in the form of verification and validation studies.
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