ライブラリ登録: Guest
Begell Digital Portal Begellデジタルライブラリー 電子書籍 ジャーナル 参考文献と会報 リサーチ集
Journal of Flow Visualization and Image Processing
SJR: 0.161 SNIP: 0.312 CiteScore™: 0.1

ISSN 印刷: 1065-3090
ISSN オンライン: 1940-4336

Journal of Flow Visualization and Image Processing

DOI: 10.1615/JFlowVisImageProc.2016016303
pages 131-150

A NEW ALGORITHM TO DETERMINE THE 3D LOCATION OF PARTICLES IN A FLOW USING CYLINDRICAL INTERFEROMETRIC OUT-OF-FOCUS IMAGING

Pascal Lemaitre
Institut de Radioprotection et de Surete Nucleate (IRSN), PSN-RES, SCA, LECEV, Gif-sur-Yvette, 91192, France
L. Ouldarbi
UMR CNRS 6614 CORIA, Avenue de l'Universite, BP 12, 76801 Saint-Etienne du Rouvray cedex, France
H. Shen
UMR CNRS 6614 CORIA, Avenue de l'Universite, BP 12, 76801 Saint-Etienne du Rouvray cedex, France
Emmanuel Porcheron
Institut de Radioprotection et de Surete Nucleate (IRSN), PSN-RES, SCA, LECEV, Gif-sur-Yvette, 91192, France
J. Van Beeck
Institut von Karman, B-1640 Rhode-Saint-Genese, Belgium
Gerard Grehan
CORIA, Universite de Rouen, Site Universitaire du Madrillet BP 12 76801 Saint Etienne du Rouvray, France
M. Brunel
UMR CNRS 6614 CORIA, Avenue de l'Universite, BP 12, 76801 Saint-Etienne du Rouvray cedex, France

要約

The ability to simultaneously determine the 3D location, velocity, and size of droplets, bubbles or more complex particles remains a challenge for numerous applications. A new interferometric out-of-focus imaging setup has been recently developed to determine the 3D location and velocity of a particle. With this setup, the resulting interferograms are elliptical, and their ellipticity provides the longitudinal location of the particle. The main difficulty lies in accurately determining this ellipticity, especially for interferograms with significant overlapping. Here, we propose a new algorithm based on the gradient pair vectors (GPV) method. After a complete description of the algorithm, examples are given of its application to a large set of experimental and synthetic images, illustrating the effectiveness of the proposed ellipse-fitting approach even for very complex configurations. This new algorithm should have significant applications for the analysis of complex 3D multiphase flows such as encountered, for example, in nuclear engineering, fuel injection systems, or even meteorology.


Articles with similar content:

APPLICATION OF NEURAL NETWORKS TO QUANTITATIVE FLOW VISUALIZATION
Journal of Flow Visualization and Image Processing, Vol.1, 1993, issue 4
Ichiro Kimura, Mamoru Ozawa, Yasuaki Kuroe
VISUALIZATION AND ANALYSIS OF JET OSCILLATION UNDER TRANSVERSE ACOUSTIC PERTURBATION
Journal of Flow Visualization and Image Processing, Vol.14, 2007, issue 4
Benoit Fabre, Patricio de la Cuadra, Christophe Vergez
Combined Three-Dimensional Flow- and Temperature-Field Measurement Using Digital Light Field Photography
International Heat Transfer Conference 15, Vol.28, 2014, issue
Manuel Rietz, Reinhold Kneer, Oliver Garbrecht, Wilko Rohlfs
Pathological Speech Signal Analysis Using Time-Frequency Approaches
Critical Reviews™ in Biomedical Engineering, Vol.40, 2012, issue 1
Sridhar Krishnan, Behnaz Ghoraani, Karthikeyan Umapathy, Lakshmi Sugavaneswaran
QUANTITATIVE VISUALIZATION OF VELOCITY DISTRIBUTIONS IN MULTI-PHASE FLOW
ICHMT DIGITAL LIBRARY ONLINE, Vol.18, 1992, issue
Isao Shimizu, Norio Akino