A hybrid large-eddy simulation/Reynolds-averaged Navier–Stokes turbulence model is used to simulate the Mach 6 flow around a scaled model similar to NASA’s Orion multipurpose crew vehicle. The results for surface pressure and heat transfer are compared with experimental data from previous base flow experiments conducted at the Calspan—University at Buffalo Research Center. Using the highest Reynolds number test case ( 11 × 10 6 based on capsule diameter), different numerical aspects of the hybrid approach are addressed, such as use of a low-dissipation scheme, a modification to the eddy-viscosity blending function, time-averaging results, filtering computational results, and sensitivity to grid resolution. In addition, results are compared with Reynolds-Averaged Navier–Stokes using Menter’s two-equation baseline model and to detached-eddy simulation predictions. By introducing a new modification to the blending from Reynolds-averaged Navier–Stokes to large-eddy simulation within boundary layers, very good agreement with the experiment is obtained in regions where the boundary-layer grid spacing is too coarse for large-eddy simulation. The findings show that the high-fidelity schemes produce results that agree much better with the experimental data than Reynolds-averaged Navier–Stokes methods, which tend to underpredict base pressures and overpredict heat fluxes. The overall accuracy of each scheme is evaluated using a normalized root mean square error in different regions of the flow, and the analysis shows that, in separated regions, the integrated error is over 120% using a Reynolds-averaged Navier–Stokes model, and 30–50% using the higher fidelity schemes. Additionally, the hybrid methodology presented is further validated by considering a lower Reynolds number ( 6 × 10 6 ), where the flow is nominally transitional, and very accurate heat transfer predictions are also obtained.


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    Title :

    Mach 6 Wake Flow Simulations Using a Large-Eddy Simulation/Reynolds-Averaged Navier–Stokes Model


    Contributors:

    Published in:

    Publication date :

    2014-06-18


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English