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    Measurement and Simulation of Turbulent Mixing in a Jet in Crossflow

    Source: Journal of Engineering for Gas Turbines and Power:;2011:;volume( 133 ):;issue: 006::page 61504
    Author:
    Flavio Cesar Cunha Galeazzo
    ,
    Richard J. Valdes
    ,
    Werner Krebs
    ,
    Georg Donnert
    ,
    Peter Habisreuther
    ,
    Nikolaos Zarzalis
    DOI: 10.1115/1.4002319
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Computational fluid dynamics (CFD) has an important role in current research. While large eddy simulations (LES) are now common practice in academia, Reynolds-averaged Navier–Stokes (RANS) simulations are still very common in the industry. Using RANS allows faster simulations, however, the choice of the turbulence model has a bigger impact on the results. An important influence of the turbulence modeling is the description of turbulent mixing. Experience has shown that often inaccurate simulations of combustion processes originate from an inadequate description of the mixing field. A simple turbulent flow and mixing configuration of major theoretical and practical importance is the jet in crossflow (JIC). Due to its good fuel-air mixing capability over a small distance, JIC is favored by gas turbine manufacturers. As the design of the mixing process is the key to creating stable low NOx combustion systems, reliable predictive tools and detailed understanding of this basic system are still demanded. Therefore, the current study has re-investigated the JIC configuration under engine relevant conditions both experimentally and numerically using the most sophisticated tools available today. The combination of planar particle image velocimetry and laser induced fluorescence was used to measure the turbulent velocity and concentration fields as well as to determine the correlations of the Reynolds stress tensor ui′uj′¯ and the Reynolds flux vector ui′c′¯. Boundary conditions were determined using laser Doppler velocimetry. The comparisons between the measurements and simulation using RANS and LES showed that the mean velocity field was well described using the SST turbulence model. However, the Reynolds stresses and more so, the Reynolds fluxes deviate substantially from the measured data. The systematic variation of the turbulent Schmidt number reveals the limited influence of this parameter indicating that the basic modeling is amiss. The results of the LES simulation using the standard Smagorinsky model were found to provide much better agreement with the experiments also in the description of turbulent mixing.
    keyword(s): Turbulence , Engineering simulation , Measurement , Reynolds-averaged Navier–Stokes equations , Simulation , Stress AND Boundary-value problems ,
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      Measurement and Simulation of Turbulent Mixing in a Jet in Crossflow

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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorFlavio Cesar Cunha Galeazzo
    contributor authorRichard J. Valdes
    contributor authorWerner Krebs
    contributor authorGeorg Donnert
    contributor authorPeter Habisreuther
    contributor authorNikolaos Zarzalis
    date accessioned2017-05-09T00:43:38Z
    date available2017-05-09T00:43:38Z
    date copyrightJune, 2011
    date issued2011
    identifier issn1528-8919
    identifier otherJETPEZ-27165#061504_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/146008
    description abstractComputational fluid dynamics (CFD) has an important role in current research. While large eddy simulations (LES) are now common practice in academia, Reynolds-averaged Navier–Stokes (RANS) simulations are still very common in the industry. Using RANS allows faster simulations, however, the choice of the turbulence model has a bigger impact on the results. An important influence of the turbulence modeling is the description of turbulent mixing. Experience has shown that often inaccurate simulations of combustion processes originate from an inadequate description of the mixing field. A simple turbulent flow and mixing configuration of major theoretical and practical importance is the jet in crossflow (JIC). Due to its good fuel-air mixing capability over a small distance, JIC is favored by gas turbine manufacturers. As the design of the mixing process is the key to creating stable low NOx combustion systems, reliable predictive tools and detailed understanding of this basic system are still demanded. Therefore, the current study has re-investigated the JIC configuration under engine relevant conditions both experimentally and numerically using the most sophisticated tools available today. The combination of planar particle image velocimetry and laser induced fluorescence was used to measure the turbulent velocity and concentration fields as well as to determine the correlations of the Reynolds stress tensor ui′uj′¯ and the Reynolds flux vector ui′c′¯. Boundary conditions were determined using laser Doppler velocimetry. The comparisons between the measurements and simulation using RANS and LES showed that the mean velocity field was well described using the SST turbulence model. However, the Reynolds stresses and more so, the Reynolds fluxes deviate substantially from the measured data. The systematic variation of the turbulent Schmidt number reveals the limited influence of this parameter indicating that the basic modeling is amiss. The results of the LES simulation using the standard Smagorinsky model were found to provide much better agreement with the experiments also in the description of turbulent mixing.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMeasurement and Simulation of Turbulent Mixing in a Jet in Crossflow
    typeJournal Paper
    journal volume133
    journal issue6
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4002319
    journal fristpage61504
    identifier eissn0742-4795
    keywordsTurbulence
    keywordsEngineering simulation
    keywordsMeasurement
    keywordsReynolds-averaged Navier–Stokes equations
    keywordsSimulation
    keywordsStress AND Boundary-value problems
    treeJournal of Engineering for Gas Turbines and Power:;2011:;volume( 133 ):;issue: 006
    contenttypeFulltext
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