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Proceedings Paper

Finding the temperature using image analysis techniques
Author(s): Ana Oprisan; Sorinel A. Oprisan; John Hegseth; Yves Garrabos; Daniel Beysens
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Paper Abstract

Many experiments used light scattering to visualize the fluctuations of fluid's density. Fluids near the critical point are affected by gravity because the compressibility of the fluid is very large near the critical point. Therefore, microgravity experiments allowed new phenomena to be discovered by reducing convection, sedimentation and buoyancy phenomena. In order to study, fluctuation and phase separation processes near the critical point of pure fluids without the influence of the Earth's gravity, a number of experiments were performed in microgravity. Our results refer to a set of experiments that studied local density fluctuations by illuminating a cylindrical cell filled with sulfur hexafluoride, near its liquid-gas critical point. Using image analysis, we estimated the temperature of the fluid in microgravity from the recorded images showing fluctuations of the transmitted and scattered light. Our method has the advantage of avoiding any reference to the spatial correlation of the pixels in the recorded images. We assumed that the variation of the scattered light intensity is proportional to the average value of the gray levels. Furthermore, we also assumed that a small fluctuation of the fluid density induces a change in the scattered light intensity that can be measured from average gray scale intensity of the image. We found that the histogram of an image can be fitted to a Gaussian relationship and by determining its width we were able to estimate the position of the critical point.

Paper Details

Date Published: 5 September 2008
PDF: 12 pages
Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 70750N (5 September 2008); doi: 10.1117/12.796591
Show Author Affiliations
Ana Oprisan, College of Charleston (United States)
Sorinel A. Oprisan, College of Charleston (United States)
John Hegseth, Univ. of New Orleans (United States)
Yves Garrabos, Institut de Chimie de la Matière Condensée de Bordeaux, CNRS, Univ. Bordeaux (France)
Daniel Beysens, Equipe du Supercritique pour l'Environnement (France)
Ecole Superieure de Physique et Chimie Industrielles (France)

Published in SPIE Proceedings Vol. 7075:
Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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