/POD-DMD-decompositions

POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for Fluid Dynamics under supervision of Professor Miguel A. Mendez.

Primary LanguageMATLAB

POD and DMD decomposition of numerical and experimental data

Screenshot

Proper Orthogonal Decomposition (POD) rank=3 approximation to the flow behind a cylinder

Short Training Programme at the von Karman Institute for Fluid Dynamics

This work has been produced as part of the Short Training Programme at the von Karman Institute for Fluid Dynamics in Belgium. The supervisor of my work was Miguel A. Mendez.

I applied two data decomposition methods: Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) to extract temporal and spatial features from numerical data representing fluid flows. To see the details, download my final report here.

Repository

This repository is a collection of my work done and is divided into:

training code

POD-DMD GUI

final report

datasets