TY - GEN
T1 - Pressure drop fluctuation and flow regime identification for air-water two-phase flow
AU - Bai, Bofeng
AU - Wu, Tiejun
AU - Guo, Liejin
AU - Chen, Xuejun
N1 - Publisher Copyright:
© 2000 by ASME.
PY - 2000
Y1 - 2000
N2 - The fluctuating pressure drop for air-water two-phase flow was measured in the vertical upward section of U-type tube with 0.05m I.D. The feature of the fluctuations was extracted by means of statistical and chaotic theories. The influence of liquid superficial velocity on the features was also investigated. The results showed that the mean, root mean square, fractal dimension of pressure drop fluctuations is function of flow regimes. The fractal dimension can be larger than 1.5 in annular flow with great liquid superficial velocity which is reported for the first time. Furthermore, the present paper provided a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on basis of the combination of the Counter Propagation Network (CPN) and the FFT coefficients of the differential pressure fluctuations. The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN. With the presented test cases, the possibility can be greater than 90 percent for different liquid phase velocity.
AB - The fluctuating pressure drop for air-water two-phase flow was measured in the vertical upward section of U-type tube with 0.05m I.D. The feature of the fluctuations was extracted by means of statistical and chaotic theories. The influence of liquid superficial velocity on the features was also investigated. The results showed that the mean, root mean square, fractal dimension of pressure drop fluctuations is function of flow regimes. The fractal dimension can be larger than 1.5 in annular flow with great liquid superficial velocity which is reported for the first time. Furthermore, the present paper provided a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on basis of the combination of the Counter Propagation Network (CPN) and the FFT coefficients of the differential pressure fluctuations. The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN. With the presented test cases, the possibility can be greater than 90 percent for different liquid phase velocity.
UR - https://www.scopus.com/pages/publications/85119832891
U2 - 10.1115/IMECE2000-2059
DO - 10.1115/IMECE2000-2059
M3 - 会议稿件
AN - SCOPUS:85119832891
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
SP - 121
EP - 128
BT - Fluids Engineering
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2000 International Mechanical Engineering Congress and Exposition, IMECE 2000
Y2 - 5 November 2000 through 10 November 2000
ER -