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A Data-Driven Neural Network Model to Correct Derived Features in a RANS-Based Simulation of the Flow Around a Sharp-Edge Bluff Body
DownloadSpring 2023
In this dissertation, a machine-learning method is utilized to enhance the accuracy of wake parameters calculated by Reynolds Averaged Navier Stokes (RANS) k-ω SST model of flow on and around wall-mounted rectangular cylinders. Using high-quality results from Large Eddy Simulation (LES), this...
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Fall 2020
This dissertation characterizes the wake dynamics of long depth-ratio wall-mounted rectangular cylinders at a range of Reynolds numbers between 250-1000 at different incidence (yaw) angles, 0° - 45° with respect to the free stream flow. The effect of large depth-ratio on flow characteristics and...