Strongly swirling flow is widely encountered in engineering applications. However, accurate prediction of the flow is still challenging for turbulence modeling. The present study reports the assessment and validation of a newly developed self-adaptive turbulence modeling, denoted as very-large-eddy simulation (VLES), for the prediction of turbulent strongly swirling flow through a suddenly expanding circular pipe at Reynolds number of 6.0 × 10 4 and 1.0 × 10 5 , and the corresponding swirl numbers are 1.16 and 1.23, which are both very strongly swirling flow. The VLES method is a unified simulation approach enabling a seamless evolution from Reynolds-Averaged Navier–Stokes (RANS) to LES and finally approaching direct numerical simulation (DNS) depending on the numerical resolution. In the present work, a new proposed VLES turbulence closure model, namely, VLES BSL k - ω , and other two models, denoted as VLES k - ε and VLES k - ω , are applied for the strong swirling flow simulation. Two meshes containing about 0.9 million and 5.1 million cells are applied, with different mesh resolutions. The simulation results are compared with available experimental data and RANS results. It is observed that the present VLES models accurately predict the time-averaged and root-mean-square (rms) velocities compared with the measurements on both of the two meshes. The significant features of the present strongly swirling flow, including vortex breakdown and the vortex core precession, large recirculation region, and shear-layer instability, are well captured by the present VLES models. Furthermore, the anisotropy of the Reynolds stresses of the strongly swirling flow is also well predicted. Satisfactory predictions can be obtained using low grid resolution with the VLES models, which confirm the validity and accuracy of the VLES modeling for strongly swirling turbulent flow.


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    Title :

    Assessment and Validation of Very-Large-Eddy Simulation Turbulence Modeling for Strongly Swirling Turbulent Flow


    Contributors:
    Xia, Zhaoyang (author) / Han, Xingsi (author) / Mao, Junkui (author)

    Published in:

    AIAA Journal ; 58 , 1 ; 148-163


    Publication date :

    2020-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English