HETERODYNE BACKGROUND-ORIENTED SCHLIEREN FOR DIAGNOSTICS OF REACTIVE FLOWS

This research is the result of Austrian-German joint research project, funded by the Austrian Science Fund FWF within grant FWF-I5392-N and the Deutsche Forschungsgemeinschaft DFG within grant CZ 55/50-1. This project is a Lead-Agency D-A-CH project in cooperation between Graz University of Technology, Austria and Technische Universität Dresden, Germany, named "FOUR-DIMENSIONAL MEASUREMENT OF THERMOACOUSTIC OSCILLATIONS".

The underlying hypothesis of this project claims that four-dimensional detection of local thermoacoustic oscillations, based on the combination of a (camera-based) laser interferometric vibrometer with multidirectional background-oriented schlieren method, density tagging velocimetry and deep neural networks as binding element, will reveal local and coupled information on combustion, acoustics and fluid dynamics. 

As of Dec 2024, this repository contains the Python routines and sample data from this project.

This publication refers to the previous publication by

Tasmany, S., Kaiser, D., Woisetschläger, J. et al. Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Exp Fluids 65, 151 (2024). https://doi.org/10.1007/s00348-024-03890-1

Tasmany S, Woisetschläger J (2024) Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Graz Univ Technol. https://doi.org/10.3217/7k9f0-7wb03

Repository.zip is divided in 4 subfolders: 

HBOS

OH average fields

phase averages

tomography code and data

HBOS folder is subdivided in Data folder and Main Folder:

Data contains the data used as input for the HBOS elaboration; These data are divided in 3 folders (one for each background pattern here used), these three folders contains their respective pictures of reference background (in "Background" subfolder) and their respective picture of the deflected background, both for one phase step and for the time average signal.

Main contains the main python code for HBOS data elaboration (main.py); this code needs to be fed with the pictures in the Data folder.

OH average fields folder contains a folder called Images and a python code called python_script_to_read_Lavision_images.py:

Images contains the image data exported from LaVision software.

python_script_to_read_Lavision_images.py is the code necessary to read and average the data from LaVision through python.

Phase averages folder contains two folder called amplitude modulation and OH emission:

amplitude modulation contains the whole set of phase averaged results for fringe amplitude modulation of which only two are shown in the paper.

OH emission contains the whole set of phase averaged results for the OH emission data of which only two are shown in the paper.

Tomography code and data folder contains a folder called Gradient plots new and two python codes named Filtered_backprojection.py  and Radon_transform.py:

Gradient plots new contain all the average results obained for frequency and amplitude modulation from HBOS for the 9 projection angles [0,20,40,60,80,100,120,140,160]. There is a folder for each angle and inside each folder there are .npy files for the horizontal signal frequency modulation averages (average_0.npy, ... average_8.npy) and for the horizontal signal amplitude modulation (average_mod0.npy, ... average_mod8.npy). In each angle folder there is even a folder containing the correspondent vertical signal results.

 Filtered_backprojection.py performs the filtered back projection algorithm implemented by the authors. This code requires the amplitude modulation files from folder Gradient plot new.

Radon_transform.py the direct analytical Radon transform starting from the horizontal gradient files, hence the horizontal frequency modulation files from folder Gradient plot new.