Bayesian Optimization to identfy coherent structures in Turbulent boundary layers.

Here is the related abstract that was sent to APS-DFD 2020. Abstract

Contents of the repository.

SMR_W14_automation_heightV5.ipynb - Fully auomated framework that takes the PIV data as an input and produces the cumulative vortex properties convecting as a group in the captured flow. Includes analysis on the results and error estimates. The algorithm gives an ~80% efficiency, in terms of finding a converged global solution.

version-2 (V2) and version-4 (V4) of the above notebook show older implementations.

PIVutils.py - contains utility functions to handle the PIV data.

PODutils.py - contains utility functions to execute POD and other methods to analyse the PIV data.

grafteaux.py - evaluate the T2 function defined by Laurent Graftieaux et al. (2001) to identify vortex cores. (and other supporting functions.)

automateG.py - contains function to automate the graftieaux (G) based identification.

prom2d.py - finds the prominence regions of a 2d signal.