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    Loss Prediction in an Axial Compressor Cascade at Off-Design Incidences With Free Stream Disturbances Using Large Eddy Simulation

    Source: Journal of Turbomachinery:;2018:;volume 140:;issue 007::page 71005
    Author:
    Leggett, John
    ,
    Priebe, Stephan
    ,
    Shabbir, Aamir
    ,
    Michelassi, Vittorio
    ,
    Sandberg, Richard
    ,
    Richardson, Edward
    DOI: 10.1115/1.4039807
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Axial compressors may be operated under off-design incidences due to variable operating conditions. Therefore, a successful design requires accurate performance and stability limits predictions under a wide operating range. Designers generally rely both on correlations and on Reynolds-averaged Navier–Stokes (RANS), the accuracy of the latter often being questioned. The present study investigates profile losses in an axial compressor linear cascade using both RANS and wall-resolved large eddy simulation (LES), and compares with measurements. The analysis concentrates on “loss buckets,” local separation bubbles and boundary layer transition with high levels of free stream turbulence, as encountered in real compressor environment without and with periodic incoming wakes. The work extends the previous research with the intention of furthering our understanding of prediction tools and improving our quantification of the physical processes involved in loss generation. The results show that while RANS predicts overall profile losses with good accuracy, the relative importance of the different loss mechanisms does not match with LES, especially at off-design conditions. This implies that a RANS-based optimization of a compressor profile under a wide incidence range may require a thorough LES verification at off-design incidence.
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      Loss Prediction in an Axial Compressor Cascade at Off-Design Incidences With Free Stream Disturbances Using Large Eddy Simulation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4253324
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    contributor authorLeggett, John
    contributor authorPriebe, Stephan
    contributor authorShabbir, Aamir
    contributor authorMichelassi, Vittorio
    contributor authorSandberg, Richard
    contributor authorRichardson, Edward
    date accessioned2019-02-28T11:09:41Z
    date available2019-02-28T11:09:41Z
    date copyright6/14/2018 12:00:00 AM
    date issued2018
    identifier issn0889-504X
    identifier otherturbo_140_07_071005.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4253324
    description abstractAxial compressors may be operated under off-design incidences due to variable operating conditions. Therefore, a successful design requires accurate performance and stability limits predictions under a wide operating range. Designers generally rely both on correlations and on Reynolds-averaged Navier–Stokes (RANS), the accuracy of the latter often being questioned. The present study investigates profile losses in an axial compressor linear cascade using both RANS and wall-resolved large eddy simulation (LES), and compares with measurements. The analysis concentrates on “loss buckets,” local separation bubbles and boundary layer transition with high levels of free stream turbulence, as encountered in real compressor environment without and with periodic incoming wakes. The work extends the previous research with the intention of furthering our understanding of prediction tools and improving our quantification of the physical processes involved in loss generation. The results show that while RANS predicts overall profile losses with good accuracy, the relative importance of the different loss mechanisms does not match with LES, especially at off-design conditions. This implies that a RANS-based optimization of a compressor profile under a wide incidence range may require a thorough LES verification at off-design incidence.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleLoss Prediction in an Axial Compressor Cascade at Off-Design Incidences With Free Stream Disturbances Using Large Eddy Simulation
    typeJournal Paper
    journal volume140
    journal issue7
    journal titleJournal of Turbomachinery
    identifier doi10.1115/1.4039807
    journal fristpage71005
    journal lastpage071005-11
    treeJournal of Turbomachinery:;2018:;volume 140:;issue 007
    contenttypeFulltext
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