가압기포탑계에서 기체-액체 흐름의 복합적인 현상에 의해 유발되는 압력변동 특성을 측정하고 이를 최근의 새로운 개념인 chaos 해석방법을 도입하여 통계적으로 해석하였다 즉, 가압기포탑계에서 얻은 시간의 변화에 따른 압력변동자료들로부터 위상공간투영을 구성하여 계의 특성에 맞는 최적의 시간 lag를 결정하여 자료에 의해 표현되는 strange attractor를 찾아내고 거동의 특성을 분석하였으며 이를 파라미터화하고자 상관차원(correlation dimension)을 구하였다. 또한, 가압기포탑계에서 기체-액체 부피물질전달 계수를 축방향 분산모델을 적용하여 구하였으며, 이를 수력학적 특성과 연관하여 검토하였다. 본 연구결과, 가압기포탑에서 압력변동의 상관차원은 기체의 유속(0.02-0.25 m/s)이 증가함에 따라 증가하였으나, 압력(0.1-0.6 MPa)이 증가함에 따라 감소하는 경향을 나타내어 가압기포탑내의 기체-액체흐름의 불균일성 정도와 동적거동특성을 잘 나타낼 수 있었다. 또한, 기체-액체 부피물질전달계수는 기체의 유속과 압력이 증가함에 따라 증가 경향을 나타냈으며,기체-액체 계면에서의 물질전달특성을 기체-액체 흐름현상의 특성을 나타내는 통계학적 파라미터에 의해 정량적으로 해석될 수 있었다.

Since the gas-liquid flow behavior in the pressurized bubble column is highly irregular, random and stochastic, it has been analyzed by resorting to somewhat noble chaos analysis : the resultant pressure fluctuations describing the complex flow behavior of gas-liquid in the system have been manipulated to form the multidimensional phase-space portraits from which the strange attractor can be obtained. The chaos behavior of pressure fluctuations has been represented by means of correlation dimension. The volumetric gas-liquid mass transfer coefficient in the pressurized bubble column has been determined by adopting the axial dispersion model, and the relation between the hydrodynamic characteristics and the mass transfer coefficient has been also discussed. As a result of this study, the correlation dimension of pressure fluctuations has increased with increasing gas velocity(0.02-0.25 m/s), but it has decreased with an increase in the pressure(0.1-0.6 MPa) in the column, representing the dynamic gas-liquid flow behavior in the column. The volumetric gas-liquid mass transfer coefficient has increased with increasing gas velocity and pressure. The gas-liquid mass transfer has been well predicted by means of chaotic behavior of gas-liquid flow in the pressurized bubble column.

Pressurized Bubble Column Phase Space Portrait Correlation Dimension Chaos Analysis Volumetric Mass Transfer Coefficient

Deckwer WD, Schumpe A, Chem. Eng. Sci., 48, 889 (1993) 
Allen DG, Robinson CW, Biotechnol. Bioeng., 34, 731 (1989) 
Joshi JB, Trans. Instn. Chem. Engrs., 58, 155 (1980)
Jiang P, Lin TJ, Luo X, Fan LS, Trans. I ChemE, 73, 269 (1995)
Wilkinson PM, Spek AP, Dierendonck LL, AIChE J., 38, 544 (1992) 
Wilkinson PM, Haringa H, Stokman FPA, Chem. Eng. Sci., 48, 1785 (1993) 
Olsson SE, Wiman J, Almstedt AE, Chem. Eng. Sci., 50(4), 581 (1995) 
Idogawa K, Ikeda K, Fukuda T, Morooka S, Int. Chem. Eng., 26, 468 (1986)
Kang Y, Lim WM, Kim SD, HWAHAK KONGHAK, 25(5), 460 (1987)
Kang Y, Min BT, Nah JB, Kim SD, AIChE J., 36, 1255 (1990) 
Kang Y, Min BT, Nah JB, Kim SD, J. Chem. Technol. Biotechnol., 51, 235 (1991)
Kang Y, Shim JS, Cho SH, Choi MJ, Lee KW, Kim SD, J. Chem. Technol. Biotechnol., 63, 225 (1995) 
Kang Y, Kim SD, Chem. Ind. Technol., 13(1), 27 (1995)
Kwon HW, Kang Y, Kim SD, Yashima M, Fan LT, Ind. Eng. Chem. Res., 33(7), 1852 (1994) 
Kang Y, Cho YJ, Woo KJ, Kim KI, Kim SD, Chem. Eng. Sci., in press (1999)
Yashima M, Nassar R, Fan LT, Kang Y, AIChE J., 38, 629 (1991)
Priestler MB, Spectral Analysis and Time Series, Vol. I & II, AP Inc. (1981)
Schumwang RH, "Applied Statistical Time Series Analysis,' Prentice Hall, NJ (1988)
Hillborn RC, "Chaos and Nonlinear Dynamics," Oxford University Press, N.Y. (1994)
Sigeti D, Phys. Rev., A, 35, 2276 (1987) 
Schroeder MR, "Fractals, Chaos, Power Laws," Freeman and Company, N.Y. (1991)
Greenside HS, Ahlers G, Hohenberg PC, Walden RW, Physica D, 5, 322 (1982) 
Brandstater A, Swinney H, Phys. Rev., A, 35, 2207 (1987) 
Fan LT, Kang Y, Nieogi D, Yashima M, AIChE J., 39, 513 (1993) 
Fraser A, Physica, D34, 391 (1989)