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RISGeneralization of Machine-Learned Turbulent Heat Flux Models Applied to Film Cooling Flows
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The design of film cooling systems relies heavily on Reynolds-averaged Navier–Stokes (RANS) simulations, which solve for mean quantities and model all turbulent scales. Most turbulent heat flux models, which are based on ...
Physical Interpretation of Machine Learning Models Applied to Film Cooling Flows
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Current turbulent heat flux models fail to predict accurate temperature distributions in film cooling flows. The present paper focuses on a machine learning (ML) approach to this problem, in which the gradient diffusion ...
The Discrete Green's Function for Convective Heat Transfer—Part 2: Semi-Analytical Estimates of Boundary Layer Discrete Green's Function
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: This is the second paper in a set that defines the discrete Green's function (DGF). This paper focuses first on the turbulent boundary layer and presents two different methods to estimate the DGF. The long-element formulation ...
A Machine Learning Approach for Determining the Turbulent Diffusivity in Film Cooling Flows
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In film cooling flows, it is important to know the temperature distribution resulting from the interaction between a hot main flow and a cooler jet. However, current Reynolds-averaged Navier–Stokes (RANS) models yield poor ...