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Differences and relations of objectives, constraints, and decision parameters in the optimization of individual heat exchangers and thermal systems

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Abstract

Performance improvement of heat exchangers and the corresponding thermal systems benefits energy conservation, which is a multi-parameters, multi-objectives and multi-levels optimization problem. However, the optimized results of heat exchangers with improper decision parameters or objectives do not contribute and even against thermal system performance improvement. After deducing the inherent overall relations between the decision parameters and designing requirements for a typical heat exchanger network and by applying the Lagrange multiplier method, several different optimization equation sets are derived, the solutions of which offer the optimal decision parameters corresponding to different specific optimization objectives, respectively. Comparison of the optimized results clarifies that it should take the whole system, rather than individual heat exchangers, into account to optimize the fluid heat capacity rates and the heat transfer areas to minimize the total heat transfer area, the total heat capacity rate or the total entropy generation rate, while increasing the heat transfer coefficients of individual heat exchangers with different given heat capacity rates benefits the system performance. Besides, different objectives result in different optimization results due to their different intentions, and thus the optimization objectives should be chosen reasonably based on practical applications, where the inherent overall physical constraints of decision parameters are necessary and essential to be built in advance.

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References

  1. Bergman T L, Lavine A S, Incropera F P, et al. Fundamentals of Heat and Mass Transfer. 7th ed. Hoboken: John wiley & Sons, 2011

    Google Scholar 

  2. Shah R K. Advances in science and technology of compact heat exchangers. Heat Transfer Eng, 2006, 27: 3–22

    Article  Google Scholar 

  3. Shah R K, Sekulic D P. Fundamentals of Heat Exchanger Design. New Jersey: John Wiley & Sons, 2003

    Book  Google Scholar 

  4. Xie G N, Sunden B, Wang Q W. Optimization of compact heat exchangers by a genetic algorithm. Appl Therm Eng, 2008, 28: 895–906

    Article  Google Scholar 

  5. Brito F P, Martins J, Hancer E, et al. Thermoelectric exhaust heat recovery with heat pipe-based thermal control. J Electron Mater, 2015, 44: 1984–1997

    Article  Google Scholar 

  6. Ordonez J C, Bejan A. Entropy generation minimization in parallel-plates counterflow heat exchangers. Int J Energ Res, 2000, 24: 843–864

    Article  Google Scholar 

  7. Salimpour M R, Bahrami Z. Thermodynamic analysis and optimization of air-cooled heat exchangers. Heat Mass Transfer, 2011, 47: 35–44

    Article  Google Scholar 

  8. Pussoli B F, Barbosa J R, da Silva L W, et al. Optimization of peripheral finned-tube evaporators using entropy generation minimization. Int J Heat Mass Tran, 2012, 55: 7838–7846

    Article  Google Scholar 

  9. Zhang L N, Yang C X, Zhou J H. A distributed parameter model and its application in optimizing the plate-fin heat exchanger based on the minimum entropy generation. Int J Therm Sci, 2010, 49: 1427–1436

    Article  Google Scholar 

  10. Satapathy A K. Thermodynamic optimization of a coiled tube heat exchanger under constant wall heat flux condition. Energy, 2009, 34: 1122–1126

    Article  Google Scholar 

  11. Kotcioglu I, Caliskan S, Cansiz A, et al. Second law analysis and heat transfer in a cross-flow heat exchanger with a new winglet-type vortex generator. Energy, 2010, 35: 3686–3695

    Article  Google Scholar 

  12. Haseli Y, Dincer I, Naterer G F. Entropy generation of vapor condensation in the presence of a non-condensable gas in a shell and tube condenser. Int J Heat Mass Tran, 2008, 51: 1596–1602

    Article  MATH  Google Scholar 

  13. Sreepathi B K, Rangaiah G P. Review of heat exchanger network retrofitting methodologies and their applications. Ind Eng Chem Res, 2014, 53: 11205–11220

    Article  Google Scholar 

  14. Assad M E. Effect of maximum and minimum heat capacity rate on entropy generation in a heat exchanger. Int J Energ Res, 2010, 34: 1302–1308

    Google Scholar 

  15. Shah R K, Skiepko T. Exchanger performance behavior through irreversibility analysis for 1-2 TEMA G heat exchangers. J Heat Transfer, 2005, 127: 1296–1304

    Article  Google Scholar 

  16. Chen L G, Sun F R, Wu C. Optimum heat conductance distribution for power optimization of a regenerated closed Brayton cycle. Int J Green Energy, 2005, 2: 243–258

    Article  Google Scholar 

  17. Zhao S Y, Chen Q. Design criteria of different heat exchangers for the optimal thermodynamic performance of regenerative refrigeration systems. Appl Therm Eng, 2016, 93: 1164–1174

    Article  Google Scholar 

  18. Alebrahim A, Bejan A. Thermodynamic optimization of heat-transfer equipment configuration in an environmental control system. Int J Energ Res, 2001, 25: 1127–1150

    Article  Google Scholar 

  19. Perez-Grande I, Leo T J. Optimization of a commercial aircraft environmental control system. Appl Therm Eng, 2002, 22: 1885–1904

    Article  Google Scholar 

  20. Lavric V, Baetens D, Plesu V, et al. Entropy generation reduction through chemical pinch analysis. Appl Therm Eng, 2003, 23: 1837–1845

    Article  Google Scholar 

  21. Manjunath K, Kaushik S C. Second law thermodynamic study of heat exchangers: A review. Renew Sust Energ Rev, 2014, 40: 348–374

    Article  Google Scholar 

  22. Alarcon-Rodriguez A, Ault G, Galloway S. Multi-objective planning of distributed energy resources: A review of the state-of-the-art. Renew Sust Energ Rev, 2010, 14: 1353–1366

    Article  Google Scholar 

  23. Ravagnani M A S S, Silva A P, Biscaia E C, et al. Optimal design of shell-and-tube heat exchangers using particle swarm optimization. Ind Eng Chem Res, 2009, 48: 2927–2935

    Article  Google Scholar 

  24. Costa A L H, Queiroz E M. Design optimization of shell-and-tube heat exchangers. Appl Therm Eng, 2008, 28: 1798–1805

    Article  Google Scholar 

  25. Chen L C, Sun F R, Wu C. Optimal allocation of heat-exchanger area for refrigeration and air-conditioning plants. Appl Energ, 2004, 77: 339–354

    Article  Google Scholar 

  26. Sarkar J, Bhattacharyya S, Gopal M R. Analytical minimization of overall conductance and heat transfer area in refrigeration and heat pump systems and its numerical confirmation. Energ Convers Manage, 2007, 48: 1245–1250

    Article  Google Scholar 

  27. Chen Q, Fu R H, Xu Y C. Electrical circuit analogy for heat transfer analysis and optimization in heat exchanger networks. Appl Energ, 2015, 139: 81–92

    Article  Google Scholar 

  28. Mian A, Martelli E, Marechal F. Framework for the multiperiod sequential synthesis of heat exchanger networks with selection, design, and scheduling of multiple utilities. Ind Eng Chem Res, 2016, 55: 168–186

    Article  Google Scholar 

  29. de Oliveira L O, Liporace F S, Queiroz E M, et al. Investigation of an alternative operating procedure for fouling management in refinery crude preheat trains. Appl Therm Eng, 2009, 29: 3073–3080

    Article  Google Scholar 

  30. Gololo K V, Majozi T. On synthesis and optimization of cooling water systems with multiple cooling towers. Ind Eng Chem Res, 2011, 50: 3775–3787

    Article  Google Scholar 

  31. Wang S W, Gao D C, Sun Y J, et al. An online adaptive optimal control strategy for complex building chilled water systems involving intermediate heat exchangers. Appl Therm Eng, 2013, 50: 614–628

    Article  Google Scholar 

  32. Zhou Q, Wang S W, Ma Z J. A model-based fault detection and diagnosis strategy for HVAC systems. Int J Energ Res, 2009, 33: 903–918

    Article  Google Scholar 

  33. Chen Q. Entransy dissipation-based thermal resistance method for heat exchanger performance design and optimization. Int J Heat Mass Tran, 2013, 60: 156–162

    Article  Google Scholar 

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Authors and Affiliations

  1. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing, 100084, China

    Qun Chen & YiFei Wang

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  1. Qun Chen
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  2. YiFei Wang
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Correspondence to Qun Chen.

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Chen, Q., Wang, Y. Differences and relations of objectives, constraints, and decision parameters in the optimization of individual heat exchangers and thermal systems. Sci. China Technol. Sci. 59, 1071–1079 (2016). https://doi.org/10.1007/s11431-016-6076-4

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  • DOI: https://doi.org/10.1007/s11431-016-6076-4

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