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    Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low Pressure Turbine

    Source: Journal of Turbomachinery:;2016:;volume( 138 ):;issue: 012::page 121009
    Author:
    Pichler, R.
    ,
    Sandberg, R. D.
    ,
    Michelassi, V.
    ,
    Bhaskaran, R.
    DOI: 10.1115/1.4033507
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In the present paper, direct numerical simulation (DNS) data of a lowpressure turbine (LPT) are investigated in light of turbulence modeling. Many compressible turbulence models use Favreaveraged transport equations of the conservative variables and turbulent kinetic energy (TKE) along with other modeling equations. First, a general discussion on the turbulence modeling error propagation prescribed by transport equations is presented, leading to the terms that are considered to be of interest for turbulence model improvement. In order to give turbulence modelers means of validating their models, the terms appearing in the Favreaveraged momentum equations are presented along pitchwise profiles at three axial positions. These three positions have been chosen such that they represent regions with different flow characteristics. General trends indicate that terms related with thermodynamic fluctuations and Favre fluctuations are small and can be neglected for most of the flow field. The largest errors arise close to the trailing edge (TE) region where vortex shedding occurs. Finally, linear models and the scope for their improvement are discussed in terms of a priori testing. Using locally optimized turbulence viscosities, the improvement potential of widely used models is shown. On the other hand, this study also highlights the danger of pure local optimization.
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      Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low Pressure Turbine

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    http://yetl.yabesh.ir/yetl1/handle/yetl/162832
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    contributor authorPichler, R.
    contributor authorSandberg, R. D.
    contributor authorMichelassi, V.
    contributor authorBhaskaran, R.
    date accessioned2017-05-09T01:34:26Z
    date available2017-05-09T01:34:26Z
    date issued2016
    identifier issn0889-504X
    identifier othergtp_138_11_112804.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/162832
    description abstractIn the present paper, direct numerical simulation (DNS) data of a lowpressure turbine (LPT) are investigated in light of turbulence modeling. Many compressible turbulence models use Favreaveraged transport equations of the conservative variables and turbulent kinetic energy (TKE) along with other modeling equations. First, a general discussion on the turbulence modeling error propagation prescribed by transport equations is presented, leading to the terms that are considered to be of interest for turbulence model improvement. In order to give turbulence modelers means of validating their models, the terms appearing in the Favreaveraged momentum equations are presented along pitchwise profiles at three axial positions. These three positions have been chosen such that they represent regions with different flow characteristics. General trends indicate that terms related with thermodynamic fluctuations and Favre fluctuations are small and can be neglected for most of the flow field. The largest errors arise close to the trailing edge (TE) region where vortex shedding occurs. Finally, linear models and the scope for their improvement are discussed in terms of a priori testing. Using locally optimized turbulence viscosities, the improvement potential of widely used models is shown. On the other hand, this study also highlights the danger of pure local optimization.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleInvestigation of the Accuracy of RANS Models to Predict the Flow Through a Low Pressure Turbine
    typeJournal Paper
    journal volume138
    journal issue12
    journal titleJournal of Turbomachinery
    identifier doi10.1115/1.4033507
    journal fristpage121009
    journal lastpage121009
    identifier eissn1528-8900
    treeJournal of Turbomachinery:;2016:;volume( 138 ):;issue: 012
    contenttypeFulltext
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