Open Access
Mechanics & Industry
Volume 17, Number 2, 2016
Article Number 209
Number of page(s) 8
Published online 08 February 2016
  1. A. Bejan, Entropy Generation Minimization, CRC Press, Boca Raton FL, 1996 [Google Scholar]
  2. R.S. Berry, V.A. Kazakov, S. Sieniutycz, Z. Szwast, A.M. Tsirlin, Thermodynamic Optimization of Finite Time Processes, Wiley, Chichester, 1999 [Google Scholar]
  3. L. Chen, C. Wu, F. Sun, Finite time thermodynamics optimization or entropy generation minimization of energy systems, J. Non-Equilibrium Thermodyn. 24 (1999) 327 [Google Scholar]
  4. C. Wu, L. Chen, J. Chen, (eds.), Recent Advances in Finite Time Thermodynamics, Nova Science Publishers, New York, 1999 [Google Scholar]
  5. B. Sahin, A. Kodal, H. Yavuz, Maximum power density analysis of an endoreversible Carnot heat engine, Energy, Int. 21 (1996) 1219 [Google Scholar]
  6. L. Berrin, A. Sisman, H. Yavuz, Analysis of Ericsson cycle at maximum power density conditions, ECOS 1996, pp. 25–27 [Google Scholar]
  7. L. Chen, J. Lin, F. Sun, C. Wu, Efficiency of an Atkinson engine at maximum power density, Energy Convers. Mgmt. 39 (1998) 337 [CrossRef] [Google Scholar]
  8. H. L. Yavuz, L.B. Erbay, General performance characteristics of an Ericsson refrigerator, ECOS 1998, Nancy, France, pp. 565–571 [Google Scholar]
  9. L.B. Erbay and H. Yavuz, The maximum cooling density of a realistic Stirling refrigerator, J. Phys. D. 31 (1998) 291 [CrossRef] [Google Scholar]
  10. J.A. Mc Cormick, Progress on the development of miniature turbo-machines for low capacity reverse Brayton cryocooler, Proc. 9-th Int. Cryocooler Conf., 1996 [Google Scholar]
  11. L.G. Chen, C. Wu, F.R. Sun, Finite time thermodynamic optimization or entropy generation minimization of energy system, J. Non-Equil. Thermodyn. 24 (2005) 327−359 [Google Scholar]
  12. L.G. Chen, L. Zhang, F.R. Sun, Power, efficiency, entropy-generation rate and ecological Optimization for a class of generalized irreversible universal heat-engine cycles, Appl. Energy84 (2007) 512–525 [CrossRef] [Google Scholar]
  13. A. Durmayaz, O.S. Sogut, B. Sahin, H. Yavuz, Optimization of thermal systems based on finite-time thermodynamics and thermoeconomics, Prog. Energy Combust. Sci. 30 (2004) 175–21 [CrossRef] [Google Scholar]
  14. C.K. Chen, Y.F. Su, Exergetic efficiency optimization for an irreversible Brayton refrigeration cycle, Int. J. Therm. Sci. 44 (2005) 303–310 [CrossRef] [Google Scholar]
  15. Y. Tu, L.G. Chen, F.R. Sun, C. Wu, Cooling load and efficient of performance optimizations for real air-refrigerators, Appl. Energy83 (2006) 1289–1306 [CrossRef] [Google Scholar]
  16. X.Q. Zhu, L.G. Chen, F.R. Sun, C. Wu, Effect of heat transfer law on the ecological optimization of a generalized irreversible Carnot heat pump, Int. J. Exergy2 (2005) 423–436 [Google Scholar]
  17. L.G. Chen, X.Q. Zhu, F.R. Sun, C. Wu, Ecological optimization of a generalized irreversible Carnot refrigerator for a generalized heat transfer law, Int. J. Ambient Energy28 (2007) 213–219 [CrossRef] [Google Scholar]
  18. X.Q. Zhu, L.G. Chen, F.R. Sun, C. Wu, Exergy based ecological optimization for a generalized irreversible Carnot refrigerator, J. Energy Inst. 79 (2006) 42–46 [CrossRef] [Google Scholar]
  19. L.G. Chen, J. Li, F.R. Sun, Generalized irreversible heat-engine experiencing a complex heat-transfer law, Appl. Energy85 (2008) 52–60 [CrossRef] [Google Scholar]
  20. J. Chen, X. Chen, C. Wu, Optimization of rate of exergy output of a multistage endoreversible combined refrigeration system, Exergy 1 (2001) 100–106 [CrossRef] [Google Scholar]
  21. T. Morosuk, G. Tsatsaronis, Advanced exergetic evaluation of refrigeration machines using different working fluids, Energy 34 (2009) 2248–2258 [CrossRef] [Google Scholar]
  22. Y. Ust, Performance analysis and optimization of irreversible air refrigeration cycles based on ecological coefficient of performance criterion, Appl. Therm. Eng. 29 (2009) 47–55 [CrossRef] [Google Scholar]
  23. F. Angulo-Brown, An ecological optimization criterion for finite-time heat engines, J. Appl. Phys. 69 (1991) 7465–7469 [CrossRef] [Google Scholar]
  24. Z. Yan, Comment on ecological optimization criterion for finite-time heat-engines, J. Appl. Phys. 73 (1993) 3583 [CrossRef] [Google Scholar]
  25. D.A.V. Veldhuizen, G.B. Lamont, Multi-objective Evolutionary Algorithms: Analyzing the State-of-the-Art, Evolutionary Computation 8 (2000) 125–147 [Google Scholar]
  26. A. Konak, D.W. Coit, A.E. Smith, Multi-objective optimization using genetic algorithms: A tutorial, Reliability Engineering & System Safety 91 (2006) 992–1007 [Google Scholar]
  27. T. Bck, D. Fogel, Z. Michalewicz, Handbook of evolutionary computation, Oxford Univ., Press, 1997 [Google Scholar]
  28. M.H. Ahmadi, H. Hosseinzade, H. Sayyaadi, A.H. Mohammadi, F. Kimiaghalam, Application of the multi-objective optimization method for designing a powered Stirling heat engine: design with maximized power, thermal efficiency and minimized pressure loss, Renew. Energy 60 (2013) 313–22 [Google Scholar]
  29. M.H. Ahmadi, H. Sayyaadi, A.H. Mohammadi, A. Marco, Barranco-Jimenez. Thermo-economic multi-objective optimization of solar dish-Stirling engine by implementing evolutionary algorithm, Energy Convers. Manag. 73 (2013) 370–380 [Google Scholar]
  30. M.H. Ahmadi, M.A. Ahmadi, A.H. Mohammadi, M. Mehrpooya, M. Feidt, Thermodynamic optimization of Stirling heat pump based on multiple criteria, Energy Convers. Manag. 80 (2014) 319–328 [Google Scholar]
  31. A. Lazzaretto, A. Toffolo, Energy, economy and environment as objectives in multi-criterion optimization of thermal systems design, Energy 29 (2004) 1139–1157 [CrossRef] [Google Scholar]
  32. M.H. Ahmadi, M.A. Ahmadi, A.H. Mohammadi, M. Feidt, S.M. Pourkiaei, Multi-objective optimization of an irreversible Stirling cryogenic refrigerator cycle, Energy Convers. Manage. 82 (2014) 351–360 [CrossRef] [Google Scholar]
  33. M.H. Ahmadi, A.H. Mohammadi, S. Dehghani, Evaluation of the maximized power of a regenerative endoreversible Stirling cycle using the thermodynamic analysis, Energy Convers. Manage. 76 (2013) 561–570 [CrossRef] [Google Scholar]
  34. S. Toghyani, A. Kasaeian, M.H. Ahmadi, Multi-objective optimization of Stirling engine using non-ideal adiabatic method, Energy Convers. Manage. 80 (2014) 54-62 [Google Scholar]
  35. H. Sayyaadi, M.H. Ahmadi, S. Dehghani, Optimal Design of a Solar-Driven Heat Engine Based on Thermal and Ecological Criteria, J. Energy Eng. (2014), DOI: 10.1061/(ASCE)EY.1943-7897.0000191, 04014012 [Google Scholar]
  36. H. Sahraie, M.R. Mirani, M.H. Ahmadi, M. Ashouri, Thermo-economic and thermodynamic analysis and optimization of a two-stage irreversible heat pump, Energy Convers. Manage. 99 (2015) 81–91 [CrossRef] [Google Scholar]
  37. M.H. Ahmadi, M.A. Ahmadi, M. Mehrpooya, H. Hosseinzade, M. Feidt, Thermodynamic and thermoeconomic analysis and optimization of performance of irreversible four-temperature-level absorption refrigeration, Energy Convers. Manage. 88 (2014) 1051–1059 [CrossRef] [Google Scholar]
  38. M.H. Ahmadi, M.A. Ahmadi, Thermodynamic analysis and optimization of an irreversible Ericsson cryogenic refrigerator cycle, Energy Convers. Manage. 89 (2015) 147−55 [CrossRef] [Google Scholar]
  39. M.H. Ahmadi, M.A. Ahmadi, M. Mehrpooya, M. Sameti, Thermo-ecological analysis and optimization performance of an irreversible three-heat-source absorption heat pump, Energy Convers. Manage. 90 (2015) 175–183 [Google Scholar]
  40. M.H. Ahmadi, M.A. Ahmadi, M. Feidt, Performance optimization of a solar-driven multi-step irreversible Brayton cycle based on a multi-objective genetic algorithm. Oil & Gas Science and Technology – Rev. IFP Energies nouvelles 2014. [Google Scholar]
  41. M.H. Ahmadi, M.A. Ahmadi, M. Feidt, Thermodynamic analysis and evolutionary algorithm based on multi-objective optimization of performance for irreversible four-temperature-level refrigeration, Mechanics & Industry 16 (2015) 207 [CrossRef] [EDP Sciences] [Google Scholar]
  42. S.A. Sadatsakkak, M.H. Ahmadi, M.A. Ahmadi, Thermodynamic and thermo-economic analysis and optimization of an irreversible regenerative closed Brayton cycle, Energy Convers. Manage. 94 (2015) 124–129 [CrossRef] [Google Scholar]
  43. S.A. Sadatsakkak, et al., Optimization density power and thermal efficiency of an endoreversible Braysson cycle by using non-dominated sorting genetic algorithm, Energy Convers. Manage. 93 (2015) 31–39 [CrossRef] [Google Scholar]
  44. S.A. Sadatsakkak, M.H. Ahmadi, M.A. Ahmadi, Optimization performance and thermodynamic analysis of an irreversible nano scale Brayton cycle operating with Maxwell–Boltzmann gas, Energy Convers. Manage. 101 (2015) 592–605 [CrossRef] [Google Scholar]
  45. L.G. Chen, F.R. Sun, C. Wu, Ecological optimization criteria for an endoreversible Carnot refrigerator (in Chinese), Nat. J. 15 (1992) [Google Scholar]
  46. J.M. Gordon, K.C. Ng, Thermodynamic modeling of reciprocating chillers, J. Appl. Phys. 75 (1994) 2769–2774 [CrossRef] [Google Scholar]
  47. F.R. Sun, C. Wu, L.G. Chen, Optimal performance and rate of entropy production for forward and reverse irreversible Carnot cycles, Chin. J. Eng. Thermophys. 12 (1991) 357–360 [Google Scholar]
  48. M.M. Ait-Ali, A class of internally irreversible refrigeration cycles. J. Phys. D29 (1996) 593–599 [Google Scholar]
  49. M.M. Ait-Ali, The maximum coefficient of performance of internally irreversible refrigerators and heat pumps, J. Phys. D 29 (1996) 975–980 [CrossRef] [Google Scholar]
  50. L.G. Chen, X. Zhu, F.R. Sun, C. Wu, Ecological optimization for generalized irreversible Carnot refrigerators, J. Phys. D35 (2005) 113–118 [Google Scholar]
  51. J. Xu, L. Pang, J. Wang, Performance Optimization of Generalized Irreversible Refrigerator Based on a New Ecological Criterion, Entropy 15 (2013) 5277–5291 [CrossRef] [Google Scholar]

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