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    Direct Numerical Simulation Based Analysis of RANS Predictions of a Low-Pressure Turbine Cascade

    Source: Journal of Turbomachinery:;2017:;volume( 139 ):;issue: 008::page 81006
    Author:
    Müller-Schindewolffs, Christoph
    ,
    Baier, Ralf-D.
    ,
    Seume, Joerg R.
    ,
    Herbst, Florian
    DOI: 10.1115/1.4035834
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The state-of-the-art design of turbomachinery components is based on Reynolds-averaged Navier–Stokes (RANS) solutions. RANS solvers model the effects of turbulence and boundary layer transition and therefore allow for a rapid prediction of the aerodynamic behavior. The only drawback is that modeling errors are introduced to the solution. Researchers and computational fluid dynamics developers are working on reducing these errors by improved model calibrations which are based on experimental data. These experiments do not typically, however, offer detailed insight into three-dimensional flow fields and the evolution of model quantities in an actual machine. This can be achieved through a direct step-by-step comparison of model quantities between RANS and direct numerical simulation (DNS). In the present work, the experimentally obtained model correlations are recomputed based on DNS of the same turbine profile simulated by RANS. The actual local values are compared to the modeled RANS results, providing information about the source of model deficits. The focus is on the transition process on the blade suction side (SS) and on evaluating the development of turbulent flow structures in the blade's wake. It is shown that the source of disagreement between RANS and DNS can be traced back to three major deficiencies that should be the focus of further model improvements.
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      Direct Numerical Simulation Based Analysis of RANS Predictions of a Low-Pressure Turbine Cascade

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    contributor authorMüller-Schindewolffs, Christoph
    contributor authorBaier, Ralf-D.
    contributor authorSeume, Joerg R.
    contributor authorHerbst, Florian
    date accessioned2017-11-25T07:19:54Z
    date available2017-11-25T07:19:54Z
    date copyright2017/21/3
    date issued2017
    identifier issn0889-504X
    identifier otherturbo_139_08_081006.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236093
    description abstractThe state-of-the-art design of turbomachinery components is based on Reynolds-averaged Navier–Stokes (RANS) solutions. RANS solvers model the effects of turbulence and boundary layer transition and therefore allow for a rapid prediction of the aerodynamic behavior. The only drawback is that modeling errors are introduced to the solution. Researchers and computational fluid dynamics developers are working on reducing these errors by improved model calibrations which are based on experimental data. These experiments do not typically, however, offer detailed insight into three-dimensional flow fields and the evolution of model quantities in an actual machine. This can be achieved through a direct step-by-step comparison of model quantities between RANS and direct numerical simulation (DNS). In the present work, the experimentally obtained model correlations are recomputed based on DNS of the same turbine profile simulated by RANS. The actual local values are compared to the modeled RANS results, providing information about the source of model deficits. The focus is on the transition process on the blade suction side (SS) and on evaluating the development of turbulent flow structures in the blade's wake. It is shown that the source of disagreement between RANS and DNS can be traced back to three major deficiencies that should be the focus of further model improvements.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDirect Numerical Simulation Based Analysis of RANS Predictions of a Low-Pressure Turbine Cascade
    typeJournal Paper
    journal volume139
    journal issue8
    journal titleJournal of Turbomachinery
    identifier doi10.1115/1.4035834
    journal fristpage81006
    journal lastpage081006-11
    treeJournal of Turbomachinery:;2017:;volume( 139 ):;issue: 008
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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