Identification of liquid-liquid flow pattern in a horizontal pipe using artificial neural networks

Chemical Engineering Communications

Volumn 198, Issue 2, 2011, Pages 273-285

  Chakrabarti, D P ^a   Pilgrim, A ^a   Sastry, M K S ^a   Das, G ^b  

^a UNIVERSITY OF THE WEST INDIES   (Trinidad and Tobago)

^b INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

ANN; Flow pattern; Horizontal; Liquid liquid; Regime transition; Two phase flow

Indexed keywords

ANN; ARTIFICIAL NEURAL NETWORK; DATA SETS; EXPERIMENTAL INVESTIGATIONS; HIDDEN LAYERS; HORIZONTAL; HORIZONTAL PIPES; IDENTIFICATION OF LIQUIDS; IMMISCIBLE LIQUIDS; INPUT PARAMETER; INTERFACIAL TENSIONS; LEVENBERG-MARQUARDT LEARNING ALGORITHMS; LIQUID-LIQUID; LIQUID-LIQUID FLOW; NOVEL TECHNIQUES; PARAMETER MODELING; PHASE SUPERFICIAL VELOCITIES; PHYSICAL PARAMETERS; PIPE DIAMETER; PIPE MATERIAL; REGIME TRANSITION; WETTING CHARACTERISTICS;

FLOW PATTERNS; IDENTIFICATION (CONTROL SYSTEMS); LEARNING ALGORITHMS; NEURAL NETWORKS; PATTERN RECOGNITION; PHASE TRANSITIONS; PIPE; PIPE FLOW; TWO PHASE FLOW;

LIQUIDS;

EID: 78149434848     PISSN: 00986445     EISSN: 15635201     Source Type: Journal    
DOI: 10.1080/00986445.2010.499836     Document Type: Article

References (27)

1. Alizadehdakhel, A., Rahimi, M., Sanjari, J., and Alsairafi, A. A. (2009). CFD and artificial neural network modeling of two-phase flow pressure drop, Int. Commun. Heat Mass Transfer, 36, 850-856.
2. Angeli, P., and Hewitt, G. F. (1998). Pressure gradient in horizontal liquid-liquid flows, Int. J. Multiph. Flow, 24, 1183-1203.
3. Basu, S., Henshaw, P. F., Biswas, N., and Kwan, H. K. (2002). Prediction of gas-phase adsorption isotherms using neural nets, Can. J. Chem. Eng., 80(3), 506-512.
4. Chakrabarti, D. P., Das, G., and Das, P. K. (2006). The transition from water continuous to oil continuous flow pattern, AIChE J., 52, 3668-3678.
5. Chakrabarti, D. P., Das, G., and Das, P. K. (2007). Identification of stratified liquid-liquid flow through horizontal pipes by a non-intrusive optical probe, Chem. Eng. Sci., 62, 1861-1876.
6. Chakrabarti, D. P., Das, G., and Ray, S. (2005). Pressure drop in liquid-liquid two phase horizontal flow: Experiment and prediction, Chem. Eng. Technol., 28, 1003-1009.
7. Charles, M. E., Govier, G. W., and Hodgson, G. W. (1961). The horizontal flow of equal density oil-water mixtures, Can. J. Chem. Eng., 39, 287-295.
8. Flood, I., and Kartam, N. (1994). Neural networks in civil engineering. I: Principles and understanding, J. Comput. Civil Eng., 8, 131-148.
9. Gately, E. (1996). Neural Networks for Financial Forecasting, John Wiley, New York.
10. Hammad, F. A., Imberton, F., and Brunn, H. H. (1997). An optical probe for measurement in liquid-liquid two-phase flow, Meas. Sci. Technol., 8, 1122-1132.
11. Hammad, F. A., Pierscionek, B. K., and Brunn, H. H. (2000). A dual optical probe for volume fraction, drop velocity and drop size measurements in liquid-liquid two-phase flow, Meas. Sci. Technol., 11, 1307-1318.
12. Haykin, S. (1999). Neural Networks: A Comprehensive Foundation, 2nd ed., Prentice Hall, Upper Saddle River, N.J.
13. Jana, A. K., Das, G., and Das, P. K. (2006). A novel technique to identify flow patterns during liquid-liquid two-phase upflow through vertical pipe, Ind. Eng. Chem. Res., 45, 2381-2393.
14. Megahed, A. I., and Malik, O. P. (1999). An artificial neural network based digital differential protection scheme for synchronous generator stator winding protection, IEEE Trans. Power Deliv., 14, 130-138.
15. Morshed, J., and Kaluarachchi, J. J. (1998). Application of artificial neural network and genetic algorithm in flow and transport simulations, Adv. Water Resour., 22, 145-158.
16. Nasseh, S., Mohebbi, A., Sarrafi, A., and Taheri, M. (2009). Estimation of pressure drop in venturi scrubbers based on annular two-phase flow model, artificial neural networks and genetic algorithm, Chem. Eng. J., 150, 131-138.
17. Ngan, K. H., Ioannou, K., Rhyne, L. D., Wang, W., and Angeli, P. (2009). A methodology for predicting phase inversion during liquid-liquid dispersed pipeline flow, Chem. Eng. Res. Des., 87, 318-324.
18. Raj, T. S., Chakrabarti, D. P., and Das, G. (2005). Liquid-liquid stratified flow through horizontal conduit, Chem. Eng. Technol., 28, 899-907.
19. Ramos, R. T., Holmes, A., Wu, X., and Dussan, E. (2001). A local optical probe using fluorescence and reflectance for measurement of volume fractions in multi-phase flows, Meas. Sci. Technol., 12, 871-876.
20. Riesco, N., and Trusler, J. P. M. (2005). Novel optical flow cell for measurements of fluid phase behaviour, Fluid Phase Equilib., 228-229, 233-238.
21. Ripley, B. D. (2008). Pattern Recognition and Neural Networks, Cambridge University Press, Cambridge.
22. Russell, T. W. F., and Charles, M. E. (1959). The effect of the less viscous liquid in the laminar flow of two immiscible liquids, Can. J. Chem. Eng., 37, 18-24.
23. Salgado, C. M., Brandão, L. E. B., Schirru, R., Pereira, C. M. N. A., da Silva, A. X., and Ramos, R. (2009). Prediction of volume fractions in three-phase flows using nuclear technique and artificial neural network, Appl. Radiat. Isotopes, 67, 174-177.
24. Simmons, M. J. H., and Azzopardi, B. J. (2001). Drop size distributions in dispersed liquid liquid pipe flow, Int. J. Multiph. Flow, 27, 843-859.
25. Vasavada, S., Sun, X., Ishii, M., and Duval, W. (2007). Study of two-phase flows in reduced gravity using ground based experiments, Exp. Fluids, 43, 53-75.
26. Vasavada, S., Sun, X., Ishii, M., and Duval, W. (2009). Benchmarking of the one-dimensional one-group interfacial area transport equation for reduced-gravity bubbly flows, Int. J. Multiph. Flow, 35, 323-334.
27. Zaman, M. R., and Rahman, M. A. (1998). Experimental testing of artificial neural network based protection of power transformer, IEEE Trans. Power Deliv., 13, 510-517.