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    Uncertainty Quantification and Conjugate Heat Transfer: A Stochastic Analysis 

    Source: Journal of Turbomachinery:;2013:;volume( 135 ):;issue: 003:;page 31014
    Author(s): Montomoli, F.; D’Ammaro, A.; Uchida, S.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Conjugate heat transfer is gaining acceptance for predicting the thermal loading in high pressure nozzles. Despite the accuracy nowadays of numerical solvers, it is not clear how to include the uncertainties associated to ...
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    Uncertainty Quantification, Rare Events, and Mission Optimization: Stochastic Variations of Metal Temperature During a Transient 

    Source: Journal of Engineering for Gas Turbines and Power:;2015:;volume( 137 ):;issue: 004:;page 42101
    Author(s): Montomoli, F.; Amirante, D.; Hills, N.; Shahpar, S.; Massini, M.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Gas turbines are designed to follow specific missions and the metal temperature is usually predicted with deterministic methods. However, in the real life, the mission is subjected to strong variations which can affect the ...
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    Uncertainty Quantification: A Stochastic Method for Heat Transfer Prediction Using LES 

    Source: Journal of Turbomachinery:;2013:;volume( 135 ):;issue: 005:;page 51021
    Author(s): Carnevale, M.; Montomoli, F.; D’Ammaro, A.; Salvadori, S.; Martelli, F.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In computational fluid dynamics (CFD), it is possible to identify namely two uncertainties: epistemic, related to the turbulence model, and aleatoric, representing the randomunknown conditions such as the boundary values ...
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    Design for Additive Manufacturing: Internal Channel Optimization 

    Source: Journal of Engineering for Gas Turbines and Power:;2017:;volume( 139 ):;issue: 010:;page 102101
    Author(s): Pietropaoli, M.; Ahlfeld, R.; Montomoli, F.; Ciani, A.; D'Ercole, M.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The new possibilities offered by additive manufacturing (AM) can be exploited in gas turbines to produce a new generation of complex and efficient internal coolant systems. The flexibility offered by this new manufacturing ...
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