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RISInvestigation of the Accuracy of RANS Models to Predict the Flow Through a Low Pressure Turbine
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In the present paper, direct numerical simulation (DNS) data of a lowpressure turbine (LPT) are investigated in light of turbulence modeling. Many compressible turbulence models use Favreaveraged transport equations of the ...
Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Machine learning was applied to large-eddy simulation (LES) data to develop nonlinear turbulence stress and heat flux closures with increased prediction accuracy for trailing-edge cooling slot cases. The LES data were ...
Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Nonlinear turbulence closures were developed that improve the prediction accuracy of wake mixing in low-pressure turbine (LPT) flows. First, Reynolds-averaged Navier–Stokes (RANS) calculations using five linear turbulence ...
On the Identification and Decomposition of the Unsteady Losses in a Turbine Cascade
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The present paper describes the application of proper orthogonal decomposition (POD) to large eddy simulation (LES) of the T106A low-pressure-turbine profile with unsteady incoming wakes at two different flow conditions. ...
Development and Use of Machine-Learnt Algebraic Reynolds Stress Models for Enhanced Prediction of Wake Mixing in Low-Pressure Turbines
Publisher: American Society of Mechanical Engineers (ASME)
Abstract: Nonlinear turbulence closures were developed that improve the prediction accuracy of wake mixing in low-pressure turbine (LPT) flows. First, Reynolds-averaged Navier–Stokes (RANS) calculations using five linear turbulence ...