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http://dx.doi.org/10.7316/KHNES.2012.23.6.678

Measurements of Transient Mixing Concentrations between Solid Powder and Liquid Fuel  

Doh, Deoghee (Div. of Mech. and Energy Systems Eng., Korea Maritime Univ.)
Yum, Jooho (Graduate School of Korea Maritime Univ.)
Cho, Gyeongrae (Div. of Mech. and Energy Systems Eng., Korea Maritime Univ.)
Min, Seongki (Agency for Defense Development, The 1st R&D Institute-5)
Kim, Myungho (Agency for Defense Development, The 1st R&D Institute-5)
Ryu, Gyongwon (Agency for Defense Development, The 1st R&D Institute-5)
Yoo, Namhyun (Ocean System Convergence Technology Research Center(KOSTEC), Kyungnam Univ.)
Publication Information
Transactions of the Korean hydrogen and new energy society / v.23, no.6, 2012 , pp. 678-687 More about this Journal
Abstract
Concentration fields of solid powder in a liquid fuel were quantitatively measured by a visualization technique. The measurement system consists of a camcoder and three LCD monitors. The solid powder (glass powder) were filled in a head tank which was installed over a main mixing tank ($D{\times}H$, $310{\times}370mm$). The main mixing tank was filled with JetA1 fuel oil. With a sudden opening of the upper tank by pressurized nitrogen gas with 1.9 bar, the solid powder were poured into the JetA1 oil. An impeller type agitator was being rotated in the mixing with 700 rpm for the enhancements of mixing. Uniform visualization for the mixing flow field was made by the light from the three LCD monitors, and the visualized images were captured by the camcoder. The color images captured by the camcoder The color information of the captured images was decoded into three principle colors R, G, and B to get quantitattive relations between the concentrations of the solid powder and the colors. To get better fitting for the strong non-linearity between the concentration and the color, a neural network which has strong fitting performances was used. Analyses on the transient mixing of the solid powders were quantitatively made.
Keywords
Solid powder-liquid fuel; Concentration; Transient mixing; Color information; Neural Network; Concentration;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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