动态模态分解
跨音速
雷诺数
叠加原理
翼型
瞬态(计算机编程)
数学
模式(计算机接口)
流量(数学)
参数统计
气动弹性
应用数学
控制理论(社会学)
统计物理学
物理
机械
计算机科学
数学分析
湍流
统计
空气动力学
人工智能
操作系统
控制(管理)
作者
Jiaqing Kou,Weiwei Zhang
标识
DOI:10.1016/j.euromechflu.2016.11.015
摘要
Dynamic mode decomposition (DMD) has been extensively utilized to analyze the coherent structures in many complex flows. Although specific flow patterns with dominant frequency and growth rate can be captured, extracting dominant DMD modes for flow reconstruction and dynamic modeling still needs a priori knowledge on flow physics, especially for some transient states of unstable flows. In this paper, a criterion to select dominant modes from DMD technique is developed. The unsteady flow can be described by the superposition of each normalized DMD mode multiplied by its time coefficient. The dominance of each DMD mode can be ordered by time integration of its time coefficient. Compared with standard DMD approach, which decides the dominance of DMD modes from the order of amplitude or mode norm, this criterion considers the evolution of each mode within the whole sampling space, and ranks them according to their contribution to all samples. The proposed mode selection strategy is evaluated by test cases including both equilibrium and transient states of a cylinder at Reynolds number of 60 and a transient state of a NACA0012 airfoil buffeting in transonic flow. Results indicate that using this criterion, dominant DMD modes can be identified and flow dynamics in unstable or transient systems can be reconstructed accurately with fewer modes. Besides, this approach has better convergence against mode number and lower sensitivity to the initial condition than standard DMD method.
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