喷流中KelvinHelmholtz不稳定性的探索性数据分析
Exploratory Data Analysis of The KelvinHelmholtz instability in Jets
摘要：
Kelvin-Helmholtz（KH）不稳定性是在各种剪切层（射流、尾流、大气气流等）中经常观察到的基波不稳定性。对KH不稳定性、相干流结构的研究对理解流体动力学的基本原理具有重要影响。因此，需要能够识别和分析这些结构的方法。在这份期末作业中，我们使用机器学习的方法，如本征正交分解（POD）和动态模式分解（DMD）来分析相干流结构。我们使用2D同轴射流作为我们的数据，雷诺数对应于Re：10，000。POD模式和DMD模式的结果进行了讨论和比较。
英文摘要：
The KelvinHelmholtz (KH) instability is a fundamental wave instability that is frequently observed in all kinds of shear layer (jets, wakes, atmospheric air currents etc). The study of KH-instability, coherent flow structures has a major impact in understanding the fundamentals of fluid dynamics. Therefore there is a need for methods that can identify and analyse these structures. In this Final assignment, we use machine-learning methods such as Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) to analyse the coherent flow structures. We used a 2D co-axial jet as our data, with Reynolds number corresponding to Re: 10,000. Results for POD modes and DMD modes are discussed and compared.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
