Sökning: "faltningsneurala nätverk"

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  1. 1. Deep learning for non-intrusive sensing in turbulence with passive scalars

    Master-uppsats, KTH/Strömningsmekanik och Teknisk Akustik

    Författare :Arivazhagan Geetha Balasubramanian; [2021]
    Nyckelord :Turbulent boundary layer; passive scalar; direct numerical simulation; Prandtl number; Machine learning; convolutional neural network; Turbulent gränsskikt; passiv skalär; direkt numerisk simulering; Prandtl-nummer; maskininlärning; faltningsneurala nätverk;

    Sammanfattning : The near-wall modelling of turbulent flows has been an active field of research due to the computational cost associated with the direct numerical simulations of such flow, which are characterized by a wide range of length and time scales. With the recent advancements in technological capabilities, the availability of high-fidelity data has enabled the construction of data-driven approaches to model turbulence. LÄS MER