Combustion Visualization and Characterization of Liquefying Hybrid Rocket Fuels

Abstract

Recent results of data evaluation techniques are summarized in this paper about optical investigations of the combustion behavior of different hybrid rocket fuels. They are analyzed by optical techniques in detail. Tests are performed in a 2D slab burner configuration with windows on two sides. Mainly liquefying Paraffin-based fuels including additives are tested in combination with gaseous oxygen (GOX). High speed video imaging enables the analysis of combustion phenomena at great detail. But at the same time a huge amount of data is created, that has to be evaluated carefully. Clearly, a manual analysis is rather time consuming and probably more susceptible to errors. Therefore, two different techniques are presented in this work, which are used within an automated video evaluation routine. First of all, the Proper Orthogonal Decomposition (POD) technique is applied. Its results deliver linearly uncorrelated variables which are the principal components of the flow field. This method enables a decomposition of the data set into mean, coherent and incoherent parts, thus recognizing the main structures of the flow field and the combustion flame appearing in the video data. Secondly, the Independent Component Analysis (ICA) technique is applied to the same data. It is able to search for statistically independent, or as independent as possible, structures hidden in the data, thus increasing the independence to higher statistical orders with respect to POD. The basis functions found with the ICA are expected to describe the essential structure of the data and to resemble some physical processes involved in the combustion. With both methods it is possible to compute spatial and temporal coefficients, which can be later analyzed by applying a Power Spectral Density (PSD) in order to obtain the excited frequencies and wavelengths during the combustion. Finally, the results of the two methods are compared in order to better understand and interpret them. A comparison between spatial and temporal ICA is also performed. The results collected so far and the comparison of both techniques show that their application is consistent and useful for the automated evaluation of combustion data.