Artificial neural network based modelling of head and power characteristics of pump-mixer

Chemical Engineering Science

Volumn 59, Issue 14, 2004, Pages 2937-2945

  Singh, K K ^a   Shenoy, K T ^a   Mahendra, A K ^a   Ghosh, S K ^a  

^a BHABHA ATOMIC RESEARCH CENTRE   (India)

Author keywords

Artificial neural network; Power number; Pump mixer; Reynolds number

Indexed keywords

COMPUTER SYSTEMS; CORRELATION METHODS; DATA PROCESSING; MATHEMATICAL MODELS; NEURAL NETWORKS; PUMPS;

MULTI-VARIABLE LEAST SQUARE BASED EMPIRICAL CORRELATIONS; PUNP-MIXERS;

CHEMICAL ENGINEERING;

MIXER; MIXING; NEURAL NETWORK; PUMP;

EID: 3042534886     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2004.04.025     Document Type: Article

References (31)

1. Almeida L.B. Handbook of neural computations 1997 IOP Publishing Ltd., Amsterdam and Oxford University Press Oxford
2. Altissimi R. Brambilla A. Deidda A. Semino D. Optimal operation of a separation plant using ANN Computers and Chemical Engineering 22 Suppl. 1 1998 S939
3. Armenante P.M. Nagamire E.U. Effect of low off-bottom impeller clearance on the minimum agitation speed for complete suspension of solids in stirred tanks Chemical Engineering Science 53 9 1998 1757
4. Bonney, C.F., Rowden, G.A., 1981. Liquid-liquid contacting apparatus US Patent 4, 282, 277.
5. Bujalski W. Nienow A.W. Chatwin S. Cooke M. The dependency on scale of power numbers of Rushton disc turbines Chemical Engineering Science 42 2 1987 317
6. Conti R. Sicardi S. Specchia V. Effect of the stirrer clearance on particle suspension in agitated vessels Chemical Engineering Journal 22 1981 247
7. Greaves M. Loh V.Y. Power consumption effect in three phase mixing Fluid Mixing II, I. Chemical Engineering Symposium Series No. 89 1984 69
8. Haykin S. Neural Networks: A Comprehensive Foundation 2001 Pearson Education Asia Singapore
9. Ibrahim S. Nienow A.W. Power curves and flow patterns for a range of impellers in newtonian fluids Chemical Engineering Research and Design 73 A 1995 485
10. Jackson T.O. Handbook of Neural Computations 1997 IOP Publishing Ltd., Amsterdam and Oxford University Press Oxford
11. Laity D.S. Treybal R.E. Dynamics of liquid agitation in the absence of an air-liquid interface A.I.Ch.E Journal 3 2 1957 176
12. Larachia F. Grandjean B.P.A. Application of neural networks to multiphase reactors Chemical Engineering and Processes 42 8-9 2003 588
13. Lott J.B. Warwick G.I. Scuffham J.B. Design of large scale mixer settlers Transactions of the Society of Mining Engineers of AIME 252 3 1972 27
14. Meleiro L. Finho R.M. A self-tuning adaptive control applied to an industrial large-scale ethanol production Computers and Chemical Engineering 24 2-1 2000 925
15. Michalopoulos J. Papadokonstadakis S. Arampatzis G. Lygeros A. Modelling of an industrial fluid catalytic cracking unit using neural networks Chemical Engineering Research and Design 79 2001 137
16. Montante G. Lee K.C. Brucato A. Yianneskis M. Experimental study of double-to-single-loop transition in stirred vessels Canadian Journal of Chemical Engineering 77 1999 649
17. Montante G. Lee K.C. Brucato A. Yianneskis M. Numerical simulations of dependency of flow pattern on impeller clearance in stirred vessels Chemical Engineering Science 56 2001 3751
18. Montante G. Lee K.C. Brucato A. Yianneskis M. Experiments and predictions of the transition of the flow pattern with impeller clearance in stirred tanks Computers and Chemical Engineering 25 2001 729
19. Nienow A.W. Suspension of solid particles in turbine agitated baffled vessels Chemical Engineering Science 23 1968 1453
20. Nienow, A.W., Wisdom, D.J., Middleton, J.C., 1977. Effect of scale and geometry on flooding recirculation and power in gassed stirred vessels. Proceedings of the Second European Conference on Mixing, Cambridge, pp. 1-16.
21. Parisi D.R. Laborde M.A. Modelling steady-state heterogeneous gas-solid reactors using feedforward neural networks Computers and Chemical Engineering 25 2001 1241
22. Rao N.V.R. Baird M.H.I. McKee combined mixer settler: some laboratory studies Canadian Journal of Chemical Engineering 62 1984 497
23. Rushton J.H. Costich E.W. Everett H.J. Power characteristics of mixing impellers Chemical Engineering and Progress 46 1950 395
24. Rutherford K. Mahmoudi S.M.S. Lee K.C. Yianneskis M. The influence of Rushton impeller blade and disk thickness on the mixing characteristics of stirred vessel Chemical Engineering Research and Design 74 A 1996 369
25. Sharma R. Singhal D. Ghosh R. Dwivedi A. Potential application of artificial neural networks to thermodynamics: Vapour-liquid equilibrium prediction Computers and Chemical Engineering 23 3 1999 285
26. Treybal R.E. Mass Transfer Operations 1981 McGraw-Hill Singapore
27. van't Reit, K., Smith, J.M., 1974. The hydrodynamics of Rushton turbine agitator blades. Proceedings of the First European Mixing Conference, Cambridge, UK, B2-17, B2-24.
28. Virkki-Hatakka T. Bulsari A. Scalability of neural network models makes industrial use easier Paperi ja Puu-Paper - Timber 84 7 2002 463
29. Wasserman P.D. Neural Computing: Theory and Practice 1989 Van Nastrand Reinhold New York
30. Xiong Q. Jutan A. Grey-box modelling and control of chemical processes Chemical Engineering Science 57 6 2002 1027
31. Zhou G. Kresta S.M. Distribution of energy between convective and turbulent flow for three frequently used impellers Chemical Engineering Research and Design 74 A 1996 379