Derivation of empirical equations for thermodynamic properties of a ozone safe refrigerant (R404a) using artificial neural network

Expert Systems with Applications

Volumn 37, Issue 2, 2010, Pages 1158-1168

  Sözen, Adnan ^a   Arcaklioǧlu, Erol ^b   Menlik, Tayfun ^a  

^a GAZI UNIVERSITY   (Turkey)

^b KIRIKKALE UNIVERSITY   (Turkey)

Author keywords

Neural networks; R404a; Thermodynamic properties

Indexed keywords

ACCURATE PREDICTION; ALTERNATIVE APPROACH; ANALYTIC EQUATIONS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; COMPUTATIONAL TIME; COMPUTER CODES; COMPUTER POWER; EMPIRICAL EQUATIONS; ENVIRONMENTALLY-FRIENDLY; EXPERIMENTAL UNCERTAINTY; MATHEMATICAL MODELING; OZONE SAFE REFRIGERANTS; POTENTIAL APPLICATIONS; R404A; SATURATED LIQUID; SPECIFIC VOLUME; SUPERHEATED VAPOR; TESTING DATA; TRAINING DATA; VAPOR QUALITY; VAPOR REGION;

BACKPROPAGATION; BINARY MIXTURES; COMPUTER SIMULATION; DIFFERENTIAL EQUATIONS; OZONE; REFRIGERANTS; THERMODYNAMIC PROPERTIES; VAPORS;

NEURAL NETWORKS;

EID: 71749097370     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.06.016     Document Type: Article

References (40)

1. Arcaklioglu E. Performance comparison of CFCs with their substitutes using artificial neural network. International Journal of Energy Research 28 12 (2004) 1113-1125
2. Arcaklioglu E., Cavusoglu A., and Erisen A. Thermodynamic analyses of refrigerant mixtures using artificial neural networks. Applied Energy 78 2 (2004) 219-230
3. Attiti R. First and second order methods for learning: Between steepest descent and Newton's method. Neural Computing 4 2 (1992) 141-166
4. Bechtler H., Browne M.W., Bansal P.K., and Kecman V. New approach to dynamic modeling of vapour-compression liquid chillers: Artificial neural networks. Applied Thermal Engineering 21 (2001) 941-953
5. Chang Y.S., Kim M.S., and Ro S.T. Performance and heat transfer characteristics of hydrocarbon refrigerants in a heat pump system. International Journal of Refrigeration 23 (2000) 232-242
6. Chouai A., Laugier S., and Richon D. Modeling of thermodynamic properties using neural networks. Application to refrigerants. Fluid Phase Equilibria 199 (2002) 1-10
7. Chow T.T., Zhang G.Q., Lin Z., and Song C.L. Global optimization of absorption chiller system by genetic algorithm and neural network. Energy and Buildings 34 (2002) 103-109
8. Fukuta M., Yanagisawa T., Iwata H., and Tada K. Performance of compression/absorption hybrid refrigeration cycle with propane/mineral oil combination. International Journal of Refrigeration 25 (2002) 907-915
9. Hagan M.T., and Menhaj M.B. Training feed-forward networks with the Marquardt algorithm. IEEE Transactions on Neural Network 5 6 (1994) 989-993
10. Haykin S. Neural networks: A comprehensive foundation (1994), Macmillan, New York
11. Haykin S. Neural networks: A comprehensive foundation (1994), Macmillan, New York
12. Jang J.-S.R., Sun C.T., and Mizutani E. Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence (1997), Prentice-Hall International
13. Jung D.S., and Radermacher R. Performance simulation of single evaporator refrigerator with pure and mixed refrigerants. International Journal of Refrigeration 14 (1991) 223-232
14. Koyfman A., Jelinek M., Levy A., and Borde I. An experimental investigation of bubble pump performance for diffusion absorption refrigeration system with organic working fluids. Applied Thermal Engineering 23 (2003) 1881-1894
15. Marquardt D. An algorithm for least squares estimation of non-linear parameters. Journal of the Society for Industrial and Applied Mathematics (1963) 431-441
16. Mellit A., Benghanem M., and Kalogirou S.A. Modeling and simulation of a stand-alone photovoltaic system using an adaptive artificial neural network: Proposition for a new sizing procedure. Renewable Energy 32 2 (2007) 285-313
17. Menlik, T. (2005). Alternatif Aki{dotless}şkanli{dotless} İki Kademeli Soǧutma Sisteminin Tasari{dotless}mi{dotless}, İmali ve Performansi{dotless}, Gazi University, Yüksek Lisans Tezi, Ankara [in Turkish].
18. Mohandes M., Rehman S., and Halawani T.O. Estimation of global solar radiation using artificial neural networks. Renewable Energy 14 (1998) 179-184
19. Pacheco-Vega A., Sen M., Yang K.T., and McClain R.L. Neural network analysis of fin-tube refrigerating heat exchanger with limited experimental data. International Journal of Heat and Mass Transfer 44 (2001) 763-770
20. Palau A., Velo E., and Puigjaner L. Use of neural networks and expert systems to control a gas/solid sorption chilling machine. International Journal of Refrigeration 22 (1999) 59-66
21. Pilatowsky I., Rivera W., and Romero R.J. Thermodynamic analysis of monomethylamine-water solutions in a single-stage solar absorption refrigeration cycle at low generator temperatures. Solar Energy Materials and Solar Cells 70 (2001) 287-300
22. Rivera C.O., and Rivera W. Modeling of an intermittent solar absorption refrigeration system operating with ammonia-lithium nitrate mixture. Solar Energy Materials and Solar Cells 76 (2003) 417-427
23. 3OH + xLiBr} for the application in absorption refrigeration machines and heat pumps, The Journal of Chemical Thermodynamics, 35, 1929-1937.
24. Scalabrin G., Piazza L., and Richon D. An equation of state for R227ea from density data through a new extended corresponding states-neural network technique. Fluid Phase Equilibria 199 (2002) 33-51
25. Sharma R., Singhal D., Ghosh R., and Dwivedi A. Potential applications of artificial neural networks to thermodynamics: Vapor-liquid equilibrium predictions. Computers and Chemical Engineering 23 (1999) 385-390
26. Sözen A. Effect of heat exchangers of performance on absorption refrigeration system. Energy Conversion and Management 42 (2001) 1699-1716
27. Sözen A., and Akçayol M. Modelling the performance parameters of a solar driven ejector-absorption cycle (using artificial neural networks). Applied Energy 79 (2004) 309-325
28. Sözen A., and Arcaklioglu E. Prediction of net energy consumption based on economic indicators (GNP and GDP) in Turkey. Energy Policy 35 10 (2007) 4981-4992
29. Sözen A., and Arcaklioglu E. Exergy analysis of an ejector-absorbtion heat transformer using artificial neural network approach. Applied Thermal Engineering 27 2-3 (2007) 481-491
30. Sözen A., Arcaklioglu E., and Özalp M. A new approach to thermodynamic analysis of ejector-absorption cycle: Artificial neural networks. Applied Thermal Engineering 23 (2003) 937-952
31. Sözen A., Arcakli{dotless}oǧlu E., and Özalp M. Formulation based on artificial neural network of thermodynamic properties of ozone friendly refrigerant/absorbent couples. Applied Thermal Engineering 25 (2005) 1808-1820
32. Sözen A., Arcakli{dotless}oǧlu E., and Özalp M. Calculation for the thermodynamic properties of an alternative refrigerant (R508b) using artificial neural network. Applied Thermal Engineering 27 (2007) 551-559
33. Sözen A., Arcaklioglu E., and Tekiner Z. Estimation of net energy consumption using different indicators. Energy Sources, Part B 4 3 (2009) 261-277
34. Sözen A., Gülseven Z., and Arcaklioglu E. Estimation of GHG emissions in using energy and economic indicators. Energy Sources, Part A 31 13 (2009) 1141-1154
35. Sözen A., Menlik T., and Ünvar S. Determination of efficiency of flate-plate solar collectors using neural network approach. Expert System with Application 35 4 (2008) 1533-1539
36. Sözen A., and Özalp M. Performance improvement of absorption refrigeration system using triple-pressure-level. Applied Thermal Engineering 23 (2003) 1577-1593
37. Sözen A., and Ozalp M. Solar driven ejector-absorption cooling system. Applied Energy 80 1 (2005) 97-113
38. Sozen A., Ozalp M., and Arcaklioglu E. Investigation of thermodynamic properties of refrigerant/absorbent couples using artificial neural networks. Chamical Engineering and Processing 43 10 (2004) 1253-1264
39. Yucesu S., Sözen A., Topgül T., and Arcaklioglu E. Comparative study of mathematical and experimental analysis of spark ignition engine performance used ethanol-gasoline blend fuel. Applied Thermal Engineering 27 2-3 (2007) 358-368
40. Zhang J.J. Introduction to artificial neural network (2000), Bellingham AI Robotics Society, Bellingham WA