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    Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade 

    Source: Journal of Engineering for Gas Turbines and Power:;2022:;volume( 145 ):;issue: 001:;page 11019-1
    Author(s): Bruni, Giuseppe; Krishnababu, Senthil; Jackson, Simon
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Machine learning has gone way beyond a ground-breaking technology a few decades ago to now taken for granted in many day-to-day activities. It is now providing new ways for manufacturing, assembling, operating, monitoring, ...
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    Multiscale Parallelized Computational Fluid Dynamics Modeling Toward Resolving Manufacturable Roughness 

    Source: Journal of Engineering for Gas Turbines and Power:;2020:;volume( 142 ):;issue: 002:;page 021001-1
    Author(s): Kapsis, Marios; He, Li; Li, Yan Sheng; Valero, Omar; Wells, Roger; Krishnababu, Senthil; Gupta, Gaurav; Kapat, Jayanta; Schaenzer, Megan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Typical turbomachinery aerothermal problems of practical interest are characterized by flow structures of wide-ranging scales, which interact with each other. Such multiscale interactions can be observed between the flow ...
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