Low order modeling of dynamic stall using vortex particle method and dynamic mode decomposition

IF 1.5 4区 工程技术 Q2 ENGINEERING, AEROSPACE International Journal of Micro Air Vehicles Pub Date : 2023-01-01 DOI:10.1177/17568293221147923
Van Duc Nguyen, V. D. Duong, Minh Hoang Trinh, Hoang Quan Nguyen, Dang Thai Son Nguyen
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引用次数: 1

Abstract

Low order modelings are performed in this paper, including iterative Brinkman penalized vortex method (IBVM) and data-driven dynamic mode decomposition (DMD) for dynamic stall study of symmetric airfoil. The data are extracted from IBVM as input for flow field reconstruction using combinations of DMD dominant modes, representing extracted flow features. The primary mode together with its harmonics, and the mean mode are termed to be dominant for the airfoil wake duplication at fixed angles of attack ([Formula: see text]) ranging from [Formula: see text] to [Formula: see text]. For the dynamic stall duplication, at small and large pitching amplitudes, the nearfield and farfield vorticty contours from the DMD generally agree well with those from the IBVM. In addition, the lift coefficient from the DMD collapses well with that from the IBVM and the experiment.
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基于涡粒子法和动力模态分解的动态失速低阶建模
本文对对称翼型进行了低阶建模,包括迭代Brinkman惩罚涡方法(IBVM)和数据驱动动态模式分解(DMD)。从IBVM中提取数据,作为使用DMD主模式组合进行流场重建的输入,代表提取的流动特征。初级模态及其谐波和平均模态被称为在固定攻角([公式:见正文])下翼型尾流复制的主导模态,范围从[公式:参见正文]到[公式:详见正文]。对于动态失速复制,在大小俯仰振幅下,来自DMD的近场和远场涡流轮廓通常与来自IBVM的轮廓一致。此外,DMD的升力系数与IBVM和实验的升力系数一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.00
自引率
7.10%
发文量
13
审稿时长
>12 weeks
期刊介绍: The role of the International Journal of Micro Air Vehicles is to provide the scientific and engineering community with a peer-reviewed open access journal dedicated to publishing high-quality technical articles summarizing both fundamental and applied research in the area of micro air vehicles.
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