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Recent advances in feature extraction techniques for high-speed flowfields
Progress in Aerospace Sciences ( IF 9.6 ) Pub Date : 2023-06-18 , DOI: 10.1016/j.paerosci.2023.100918
S. Unnikrishnan

Space–time scale-resolved diagnostic and computational campaigns routinely produce high-fidelity multi-disciplinary truth-model quality datasets for complex configurations. The extraction of the primary features of engineering or scientific interest and modeling of potential low-rank dynamics has proven challenging because of the massive sizes of the databases. One approach to overcome these challenges has been through system identification based decomposition techniques. In the present work, we build on comprehensive reviews on the subject by elucidating recent advances and applications for aerodynamic flow problems. Through a succinct but panoramic treatment exemplified with relevant applications, we expect to inform the reader of method capabilities in a manner that can guide selection strategies promising critical insights into complex fluid dynamics problems. The methods are broadly classified into modal-based and physics-based. Major advances in the former are extensions of the linear framework to non-homogeneous flowfields and Floquet analysis of secondary instability, applicable to broad ranges of complexity in basic states and speed regimes. Forced response analysis has aided our understanding of non-modal instability mechanisms which extend in some ways analogous to those in the global stability literature; applications to three-dimensional flows and operator-free concepts have been particularly illustrative. Advances in modal techniques for nonlinear flowfields have sharpened focus on prescribed spectral and interaction characteristics, expanded applicability to large-scale databases through streaming approaches, and integrated multi-physics into analyzed data. Physics-based techniques, motivated by the fundamental splitting theorem of Kovasznay, have proven particularly valuable in educing mechanisms sustaining multi-modal dynamics with unique physical aspects. Helmholtz decomposition combined with signal processing procedures have provided insights into the behavior of wall-bounded and free-shear turbulence, emphasizing the effects of compressibility on energy dynamics, coherent structures, and acoustics. The generalization of physics-based eduction techniques using momentum potential theory has improved our understanding of aeroacoustics of a broad class of flowfields, and further provided direction for flow control of shear-layer noise and hypersonic boundary layer dynamics.



中文翻译:

高速流场特征提取技术的最新进展

时空尺度解析的诊断和计算活动通常会为复杂的配置产生高保真度的多学科真值模型质量数据集。由于数据库规模庞大,工程或科学兴趣的主要特征的提取以及潜在低阶动力学的建模已被证明具有挑战性。克服这些挑战的一种方法是通过基于系统识别的分解技术。在目前的工作中,我们通过阐明空气动力流动问题的最新进展和应用,在对该主题进行全面回顾的基础上。通过简洁但全景式的处理并举例说明相关应用,我们希望以一种可以指导选择策略的方式向读者介绍方法的功能,从而对复杂的流体动力学问题提供重要的见解。这些方法大致分为基于模态的方法和基于物理的方法。前者的主要进展是将线性框架扩展到非均匀流场和二次不稳定性的 Floquet 分析,适用于基本状态和速度状态的广泛复杂性。受迫响应分析有助于我们理解非模态不稳定机制,这些机制在某些方面与全球稳定文献中的机制类似;三维流和无操作员概念的应用特别具有说明性。非线性流场模态技术的进步更加关注规定的光谱和相互作用特性,通过流方法扩展了对大规模数据库的适用性,并将多物理场集成到分析数据中。事实证明,受 Kovasznay 基本分裂定理启发的基于物理的技术在推导具有独特物理方面的多模态动力学维持机制方面特别有价值。亥姆霍兹分解与信号处理程序相结合,提供了对壁限湍流和自由剪切湍流行为的见解,强调了可压缩性对能量动力学、相干结构和声学的影响。

更新日期:2023-06-18
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