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    Modeling High-Pressure Hydrogen Gas Leakages With Graph Neural Networks 

    Source: Journal of Energy Resources Technology, Part A: Sustainable and Renewable Energy:;2025:;volume( 001 ):;issue: 003:;page 32102-1
    Author(s): Cerbarano, Davide; Tieghi, Lorenzo; Delibra, Giovanni; Minotti, Stefano; Corsini, Alessandro
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The introduction of hydrogen–methane blends as fuel in gas turbines raises concerns on the capability of state-of-art ventilation systems to dilute possible fuel leaks in the enclosures. Traditional numerical methods to ...
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    Characterization of High-Pressure Hydrogen Leakages 

    Source: Journal of Engineering for Gas Turbines and Power:;2023:;volume( 146 ):;issue: 005:;page 51019-1
    Author(s): Cerbarano, Davide; Tieghi, Lorenzo; Delibra, Giovanni; Lo Schiavo, Ermanno; Minotti, Stefano; Corsini, Alessandro
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Reduction of gas turbine (GT) carbon emissions relies on a strategy for fueling the engines with pure or blended hydrogen. The major technical challenges to solve are (i) the adjustments to the engine and in particular the ...
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