Particle image velocimetry and near-field pressure were collected for an axisymmetric, Mach 0.6 jet. Some of the pressure sensors were in between the laser sheet and camera, causing occlusions in the particle image velocimetry data. Using ideas from the data fusion community, these occluded regions could be repaired. In this case, the particle image velocimetry data could be fused with the knowledge that the velocity field was symmetric about the center axis using a new technique called fused proper orthogonal decomposition, which is inspired by gappy proper orthogonal decomposition and image/wavelet fusion. Using this technique, 90% of the missing data could be estimated with 10% error.


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    Title :

    Repairing Occluded Data for a Mach 0.6 Jet via Data Fusion



    Published in:

    Publication date :

    2017




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.50 Luftfahrzeugtechnik / 55.60 Raumfahrttechnik / 55.60 / 50.93 / 55.50 / 50.93 Weltraumforschung
    Local classification TIB:    770/7040



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