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http://dx.doi.org/10.7316/KHNES.2018.29.5.523

Analyses of Steady State Mixing Process of Two-Liquids Using Artificial Intelligence  

KONG, DAEKYEONG (Division of Refrigeration & Air-conditioning Eng., Graduate School of Korea Maritime & Ocean University)
YUM, JUHO (Division of Refrigeration & Air-conditioning Eng., Graduate School of Korea Maritime & Ocean University)
CHO, GYEONGRAE (Division of Mechanical Eng., Korea Maritime & Ocean University)
DOH, DEOGHEE (Division of Mechanical Eng., Korea Maritime & Ocean University)
Publication Information
Transactions of the Korean hydrogen and new energy society / v.29, no.5, 2018 , pp. 523-529 More about this Journal
Abstract
Two liquids which are generally used as fuels of rockets are mixed and their mixing process is quantitatively investigated by the use of particle image velocimetry (PIV). As working fluids for the liquid mixing, Dimethylfuran (DMF) and JetA1 oils have been used. Since the specific gravity of DMF is larger than that of JetA1 oil, the DMF oil has been set at the lower part of the JetA1 oil. For better visualization of the mixing process, Rhodamin B powder has been blended into the DMF oil. An agitator having 3 blades has been used for mixing the two liquids. For quantitative visualization, a LCD monitor has been used as a light source. A color camera, camcoder, has been used for recording the mixing process. The images captured by the camcoder have been digitized into three color components, R, G, and B. The color intensities of R, G, and B have been used as the inputs of the neural network of which hidden layer has 20 neurons. Color-to-concentration calibration has been performed before commencing the main experiments. Once this calibration is completed, the temporal changes of the concentration of the DMF has been quantitatively analyzed by using the constructed measurement system.
Keywords
Two liquids; PIV; Dimethylfuran oil; JetA1; Color-to-concentration calibration; Steady state mixing;
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