Open Access Open Access  Restricted Access Subscription or Fee Access

Air-Water Flow through 3mm and 4mm Tubes – Experiment and ANN Prediction

Nirjhar Bar, Tapan Kumar Ghosh, Manindra Nath Biswas, Sudip Kumar Das

Abstract


Experimental investigations have been carried out to determine the flow regime for air-water two-phase flow through 3 mm and 4 mm transparent tubes by visual observation. The feasibility of Artificial Neural Network (ANN) based techniques for the classifications of flow regimes are presented. Total 218 experimental data points are used in the ANN prediction. Five different well known ANN models have been tried to predict the flow regime. The ANN model based on MLP with Levenberg-Marquardt algorithm gives slightly better predictability over the other networks used.

Keywords


Flow Regime, Multilayer Perceptron, Radial Basis Function, Support Vector Machine, Principal Component Analysis.

Full Text:

PDF

References


M. Suo and P. Griffith, “Two-phase flow in capillary tubes,” J. Basic Eng., vol 86, 1964, pp 576 –582.

D. Barnea, Y. Luninski and Y. Taitel, “Flow Pattern in Horizontal and Vertical Two Phase Flow in Small Diameter Pipes,” Can. J. Chem. Engg., vol. 61, 1983, pp 617 – 620.

A. M. Barajas and R. L. Panton, “The effect of contact angle on two-phase flow in capillary tubes,” Int. J. Multiphase Flow, vol 19, 1993, pp 337–346.

T. Fukano and A. Kariyasaki, “Characteristics of gas–liquid two-phase flow in a capillary,” Nucl. Eng. Design, vol 141, 1993, pp 59–68.

K. Mishima, T. Hibiki and H. Nishihara, “Some characteristics of air–water two-phase flow in small diameter tubes,” Proc 2nd Int. Conf. Multiphase Flow, vol. 4, April 3–7, 1995, Tokyo, Japan, pp. 39– 46.

K. Mishima and T. Hibiki, “Some characteristics of air–water two-phase flow in small diameter vertical tubes,” Int. J. Multiphase Flow, vol 22, 1996, pp 703–712.

K. A. Triplett, S. M. Ghiaasiaan, S. I. Adbel-Khalik and D. L. Sadowski, “Gas–liquid two-phase flow in microchannels. Part I: Two-phase flow patterns,” Int. J. Multiphase Flow , vol 25, 1999, pp 377–394.

J.W. Coleman and S. Garimella, “Characteristics of two-phase patterns in small diameter round and rectangular tubes,” Int. J. Heat Mass Transfer, vol 42, 1999, pp 2869–2881.

C. Y. Yang and C. C. Shieh, “Flow pattern of air–water and two-phase R-134a in small circular tubes,” Int. J. Multiphase Flow, vol 27, 2001, pp 1163–1177.

T. S. Zhao and Q. C. Bi, “Co-current air–water two-phase flow patterns in vertical triangular microchannels,” Int. J. Multiphase Flow, vol 27, 2001, pp 765–782.

M. K. Akbar, D. A. Plummer and S. M. Ghiaasiaan, “On gas–liquid two-phase flow regimes in microchannels,” Int. J. multiphase flow, vol 29, 2003, pp 855 – 865.

C. Jones, Jr. and N. Zuber, “The interrelation between void fraction fluctuations and flow patterns in two-phase flow,” vol 2, 1975, pp 273 – 306.

C. A. Damianides and J. W. Westwater, “Two-phase flow patterns in a compact heat exchanger and in small tubes,” In: Proc. Second UK National Conf. On Heat Transfer, Glasgow, 14–16 September. Mechanical Engineering Publications, London, 1988, pp 1257–1268.

S. M. Ghiaasiaan and S. I. Abdel-Khalik, “Two-phase flow in microchannels,” Adv. Heat Transfer vol 34, 2001, pp 145–254.

D. C. Lowe and K. S. Rezkallah, “Flow regime identification in microgravity two-phase flow using void fraction signals,” Int. J. Multiphase Flow, vol 25, 1999, pp 433–457.

K. S. Rezkallah, “Weber number based flow-pattern maps for liquid–gas flows at microgravity,” Int. J. Multiphase Flow , vol 22, 1996, pp 1265–1270.

A. Serizawa and Z. P. Feng, 2001. Two-phase flow in microchannels. Proc. 4th International Conf. Multiphase Flow, May 27–June 1, New Orleans, LA, USA.

L. Zhao and K. S. Rezkallah, “Gas–liquid flow patterns at microgravity conditions,” Int. J. Multiphase Flow, vol 19, 1993, pp 751–763.

D. M. Himmelblau, “Application of artificial neural network in chemical engineering,” Korean J. Chem. Engg., vol. 17, 2000, pp 373 – 392.

D. Rumelhart, G. Hinton and R. Williams, Learning internal representations by error propagation. In: Rumelhart and McClelland (Eds.), Parallel Distributed Processing, MIT Press, 1986.

D. S. Broomhead and D. Lowe, “Multivariate functional interpolation and adaptive networks,” Complex Syst., vol. 2, 1988, pp 321 – 355.

S. J. Hanson and D. J. Burr, “Minkowski-s back propagation: learning in connectionist models with non-Euclidean error Signals,” Neural Info. Proc. Sys., American Institute of Physics, New York, 1988, pp 348 – 357.

M. A. Niranjan, A. J. Robinson and F. Fallside, “Pattern recognition with potential functions in the context of neural networks,” Proceedings Sixth Scandinavian Conference on Image Analysis, Oulu, Finland, vol. 1, 1989, pp 96 – 103.

J. Moody and C. J. Darken, “Fast learning in networks of locally tuned processing units,” Neural Comput., vol. 1, 1989, pp 281 – 294.

T. Poggio and F. Girosi, “Regularization algorithms for learning that are equivalent to multilayer networks,” Science, vol. 247, 1990, pp 978 – 982.

H. Glucksman, “On improvement of a linear separation by extending the adaptive process with a stricter criterion,” IEEE Trans. On Electronic Computers, vol. EC-15 (6), 1966, pp 941 – 944.

B. Boser, I. Guyon and V. Vapnik, “A training algorithm for optimal margin classifiers,” Fith Annual Workshop on Computational Learning Theory, New York, ACM Press, 1992.

C. Cortes and V. Vapnik, “Support-vector Networks.” Machine Learning, vol. 20, 1995, pp 273 – 297.

E. Oja, “Principal components, minor components, and linear neural networks,” Neural Networks, vol. 5, 1992, pp 927 – 935.

T. D. Sanger, “Optimal unsupervised learning in a single-layer neural network,” Neural Networks, vol. 2, 1989, pp 459 – 473.

K. I. Diamantaras and S. Y. Kung, “Principal Component NeuralNetworks: Theory and Applications.” J. Wiley and Sons, New York, 1996.


Refbacks

  • There are currently no refbacks.