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    DES of a Slingsby Firefly Aircraft: Unsteady Flow Feature Extraction Using POD and HODMD

    Source: Journal of Aerospace Engineering:;2022:;Volume ( 035 ):;issue: 005::page 04022063
    Author:
    Adrián Corrochano
    ,
    Ana F. Neves
    ,
    Bidur Khanal
    ,
    Soledad Le Clainche
    ,
    Nicholas J. Lawson
    DOI: 10.1061/(ASCE)AS.1943-5525.0001457
    Publisher: ASCE
    Abstract: In this paper, higher-order dynamic mode decomposition (HODMD) was applied to find the main patterns and frequencies of a transient aerodynamic flow field when an aircraft wing experiences stall. This method was applied to a computational flow simulation with a turbulence model based on a hybrid Reynolds-averaged Navier-Stokes large-eddy simulation (RANS/LES) [commonly known as detached-eddy simulation (DES)], where a combination of two-dimensional (2D) and three-dimensional (3D) flow visualization techniques are used to understand the vortex shedding from the main wing and its interaction with the tailplane. Simulation results were compared to the experimental ones and the results with proper orthogonal decomposition (POD) were compared with the HODMD analysis. The main advantage of HODMD resides in its identification of the main physical phenomena and the most relevant instabilities that lead the fluid dynamics. New flow control strategies can be defined when the underlying physics and the flow dynamics are known. Moreover, HODMD is robust in noisy and turbulent databases using less data than fast Fourier transform (FFT), which gives potential for future flow control applications, focused on improving the aircraft’s efficiency.
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      DES of a Slingsby Firefly Aircraft: Unsteady Flow Feature Extraction Using POD and HODMD

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4286321
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    contributor authorAdrián Corrochano
    contributor authorAna F. Neves
    contributor authorBidur Khanal
    contributor authorSoledad Le Clainche
    contributor authorNicholas J. Lawson
    date accessioned2022-08-18T12:16:13Z
    date available2022-08-18T12:16:13Z
    date issued2022/06/02
    identifier other%28ASCE%29AS.1943-5525.0001457.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4286321
    description abstractIn this paper, higher-order dynamic mode decomposition (HODMD) was applied to find the main patterns and frequencies of a transient aerodynamic flow field when an aircraft wing experiences stall. This method was applied to a computational flow simulation with a turbulence model based on a hybrid Reynolds-averaged Navier-Stokes large-eddy simulation (RANS/LES) [commonly known as detached-eddy simulation (DES)], where a combination of two-dimensional (2D) and three-dimensional (3D) flow visualization techniques are used to understand the vortex shedding from the main wing and its interaction with the tailplane. Simulation results were compared to the experimental ones and the results with proper orthogonal decomposition (POD) were compared with the HODMD analysis. The main advantage of HODMD resides in its identification of the main physical phenomena and the most relevant instabilities that lead the fluid dynamics. New flow control strategies can be defined when the underlying physics and the flow dynamics are known. Moreover, HODMD is robust in noisy and turbulent databases using less data than fast Fourier transform (FFT), which gives potential for future flow control applications, focused on improving the aircraft’s efficiency.
    publisherASCE
    titleDES of a Slingsby Firefly Aircraft: Unsteady Flow Feature Extraction Using POD and HODMD
    typeJournal Article
    journal volume35
    journal issue5
    journal titleJournal of Aerospace Engineering
    identifier doi10.1061/(ASCE)AS.1943-5525.0001457
    journal fristpage04022063
    journal lastpage04022063-14
    page14
    treeJournal of Aerospace Engineering:;2022:;Volume ( 035 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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