Aircraft icing remains a significant threat to aviation safety. Software that predicts the impingement and ice accretion on full aircraft geometries and aircraft components are in demand and NASA Glenn is committed to produce software that meets this need. One of the key parameters affecting an accurate prediction of iced geometry is the effect of ice roughness on the heat transfer coefficient. While many efforts have been made to implement the roughness in the flow solver, this report takes a correlation for roughness height distribution that is based on experimental measurements and demonstrates how to relate those measurements to an augmentation to the heat transfer coefficient provided by the flow solution. The outcome of this effort was the callibration of defaults for user supplied parameters to this correlation through comparison with 95 large glaze conditions from experiment by adjusting user-supplied parameters in the roughness augmentation equation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Roughness Parameter Optimization of the McClain Model in GlennICE


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    International Conference on Icing of Aircraft, Engines, and Structures ; 2023



    Publication date :

    2023-06-15




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Roughness Parameter Optimization of the McClain Model in GlennICE

    Wright, William / Rigby, David / Ozoroski, Thomas | British Library Conference Proceedings | 2023


    Optimized Parameters for McClain Correlation in GlennICE

    William Wright / Thomas Ozoroski / David Rigby | NTRS


    Optimized Parameters for McClain Correlation in GlennICE

    W. Wright / T. Ozoroski / D. Rigby | NTIS | 2023


    McClain leaves Xylem

    Online Contents | 2013


    GlennICE Manual 4.1.0

    C. Porter / M. Potapczuk / T. Ozoroski et al. | NTIS | 2024