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    Compressible Direct Numerical Simulation of Low Pressure Turbines—Part I: Methodology

    Source: Journal of Turbomachinery:;2015:;volume( 137 ):;issue: 005::page 51011
    Author:
    Sandberg, Richard D.
    ,
    Michelassi, Vittorio
    ,
    Pichler, Richard
    ,
    Chen, Liwei
    ,
    Johnstone, Roderick
    DOI: 10.1115/1.4028731
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Modern low pressure turbines (LPT) feature high pressure ratios and moderate Mach and Reynolds numbers, increasing the possibility of laminar boundarylayer separation on the blades. Upstream disturbances including background turbulence and incoming wakes have a profound effect on the behavior of separation bubbles and the type/location of laminarturbulent transition and therefore need to be considered in LPT design. Unsteady Reynoldsaveraged Navier–Stokes (URANS) are often found inadequate to resolve the complex wake dynamics and impact of these environmental parameters on the boundary layers and may not drive the design to the best aerodynamic efficiency. LES can partly improve the accuracy, but has difficulties in predicting boundary layer transition and capturing the delay of laminar separation with varying inlet turbulence levels. Direct numerical simulation (DNS) is able to overcome these limitations but has to date been considered too computationally expensive. Here, a novel compressible DNS code is presented and validated, promising to make DNS practical for LPT studies. Also, the sensitivity of wake loss coefficient with respect to freestream turbulence levels below 1% is discussed.
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      Compressible Direct Numerical Simulation of Low Pressure Turbines—Part I: Methodology

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    http://yetl.yabesh.ir/yetl1/handle/yetl/159927
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    contributor authorSandberg, Richard D.
    contributor authorMichelassi, Vittorio
    contributor authorPichler, Richard
    contributor authorChen, Liwei
    contributor authorJohnstone, Roderick
    date accessioned2017-05-09T01:24:33Z
    date available2017-05-09T01:24:33Z
    date issued2015
    identifier issn0889-504X
    identifier otherturbo_137_05_051011.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/159927
    description abstractModern low pressure turbines (LPT) feature high pressure ratios and moderate Mach and Reynolds numbers, increasing the possibility of laminar boundarylayer separation on the blades. Upstream disturbances including background turbulence and incoming wakes have a profound effect on the behavior of separation bubbles and the type/location of laminarturbulent transition and therefore need to be considered in LPT design. Unsteady Reynoldsaveraged Navier–Stokes (URANS) are often found inadequate to resolve the complex wake dynamics and impact of these environmental parameters on the boundary layers and may not drive the design to the best aerodynamic efficiency. LES can partly improve the accuracy, but has difficulties in predicting boundary layer transition and capturing the delay of laminar separation with varying inlet turbulence levels. Direct numerical simulation (DNS) is able to overcome these limitations but has to date been considered too computationally expensive. Here, a novel compressible DNS code is presented and validated, promising to make DNS practical for LPT studies. Also, the sensitivity of wake loss coefficient with respect to freestream turbulence levels below 1% is discussed.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleCompressible Direct Numerical Simulation of Low Pressure Turbines—Part I: Methodology
    typeJournal Paper
    journal volume137
    journal issue5
    journal titleJournal of Turbomachinery
    identifier doi10.1115/1.4028731
    journal fristpage51011
    journal lastpage51011
    identifier eissn1528-8900
    treeJournal of Turbomachinery:;2015:;volume( 137 ):;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
    yabeshDSpacePersian