Minimization of Entransy Dissipations of a Finned Shell and Tube Heat Exchanger

Document Type: Research Paper


Department of Mechanical Engineering, Shahrood University of Technology, Shahrood,Iran.


Improving heat transfer and performance in a radial, finned, shell and tube heat exchanger is studied in this study. According to the second law of thermodynamics, the most irreversibilities of convective heat transfer processes are due to fluid friction and heat transfer via finite temperature difference. Entransy dissipations are due to the irreversibilities of convective heat transfer. Therefore, the number of entrancy dissipation is considered as the optimization objective. Thirteen optimization variables are considered, such as the number of tubes, tube diameter, tube length, fin height, fin thickness, the number of fins per inch length of tube and baffle spacing ratio. The “Delaware modified” technique is used to determine heat transfer coefficients and the shell-side pressure drop. In this technique, the baffle cut is 20 percent. The results show that using genetic algorithm the optimization can be improve the heat transfer by 13 percent and performance of heat exchanger increased by 18 percent. In order to show the accuracy of the algorithm the results compared to the particle swarm optimization.


Main Subjects

[1]           A. Bejan, 1982, Entropy generation through heat and fluid flow, Wiley,

[2]           J. Hesselgreaves, Rationalisation of second law analysis of heat exchangers, International Journal of Heat and Mass Transfer, Vol. 43, No. 22, pp. 4189-4204, 2000.

[3]           Z.-Y. Guo, H.-Y. Zhu, X.-G. Liang, Entransy—a physical quantity describing heat transfer ability, International Journal of Heat and Mass Transfer, Vol. 50, No. 13-14, pp. 2545-2556, 2007.

[4]           G.-Z. Han, Z.-Y. Guo, Physical mechanism of heat conduction ability dissipation and its analytical expression, in Proceeding of, 98-102.

[5]           S. Wang, Q. Chen, B. Zhang, An equation of entransy transfer and its application, Chinese science bulletin, Vol. 54, No. 19, pp. 3572, 2009.

[6]           Q. Chen, J. Ren, Generalized thermal resistance for convective heat transfer and its relation to entransy dissipation, Chinese science bulletin, Vol. 53, No. 23, pp. 3753-3761, 2008.

[7]           S. Xia, L. Chen, F. Sun, Optimization for entransy dissipation minimization in heat exchanger, Chinese science bulletin, Vol. 54, No. 19, pp. 3587, 2009.

[8]           J. Guo, M. Xu, L. Cheng, Principle of equipartition of entransy dissipation for heat exchanger design, Science China Technological Sciences, Vol. 53, No. 5, pp. 1309-1314, 2010.

[9]           H. Wei, X. Du, L. Yang, Y. Yang, Entransy dissipation based optimization of a large-scale dry cooling system, Applied Thermal Engineering, Vol. 125, pp. 254-265, 2017.

[10]         Y.-C. Xu, Q. Chen, Z.-Y. Guo, Optimization of heat exchanger networks based on Lagrange multiplier method with the entransy balance equation as constraint, International Journal of Heat and Mass Transfer, Vol. 95, pp. 109-115, 2016.

[11]         A. M. Abed, I. A. Abed, H. S. Majdi, A. N. Al-Shamani, K. Sopian, A new optimization approach for shell and tube heat exchangers by using electromagnetism-like algorithm (EM), Heat and Mass Transfer, Vol. 52, No. 12, pp. 2621-2634, 2016.

[12]         X. Liu, J. Meng, Z. Guo, Entropy generation extremum and entransy dissipation extremum for heat exchanger optimization, Chinese science bulletin, Vol. 54, No. 6, pp. 943-947, 2009.

[13]         M. Xu, J. Guo, L. Cheng, Application of entransy dissipation theory in heat convection, Frontiers of Energy and Power Engineering in China, Vol. 3, No. 4, pp. 402, 2009.

[14]         L. Chen, Progress in entransy theory and its applications, Chinese science bulletin, Vol. 57, No. 34, pp. 4404-4426, 2012.

[15]         R. V. Rao, A. Saroj, Economic optimization of shell-and-tube heat exchanger using Jaya algorithm with maintenance consideration, Applied Thermal Engineering, Vol. 116, pp. 473-487, 2017.

[16]         M. Mirzaei, H. Hajabdollahi, H. Fadakar, Multi-objective optimization of shell-and-tube heat exchanger by constructal theory, Applied Thermal Engineering, Vol. 125, pp. 9-19, 2017/10/01/, 2017.

[17]         J. C. Lemos, A. L. Costa, M. J. Bagajewicz, Linear method for the design of shell and tube heat exchangers including fouling modeling, Applied Thermal Engineering, Vol. 125, pp. 1345-1353, 2017.

[18]         Y. Lei, Y. Li, S. Jing, C. Song, Y. Lyu, F. Wang, Design and performance analysis of the novel shell-and-tube heat exchangers with louver baffles, Applied Thermal Engineering, Vol. 125, pp. 870-879, 2017.

[19]         P. Bichkar, O. Dandgaval, P. Dalvi, R. Godase, T. Dey, Study of Shell and Tube Heat Exchanger with the Effect of Types of Baffles, Procedia Manufacturing, Vol. 20, pp. 195-200, 2018.

[20]         X. Gu, M. Wang, Y. Liu, S. Wang, Multi-parameter optimization of shell-and-tube heat exchanger with helical baffles based on entransy theory, Applied Thermal Engineering, Vol. 130, pp. 804-813, 2018.

[21]         W. Gander, Starting and Using Matlab,  in: Learning MATLAB, Eds., pp. 1-9: Springer, 2015.

[22]         R. K. Shah, D. P. Sekulic, 2003, Fundamentals of heat exchanger design, John Wiley & Sons,

[23]         H. Sadeghzadeh, M. Aliehyaei, M. A. Rosen, Optimization of a Finned Shell and Tube Heat Exchanger Using a Multi-Objective Optimization Genetic Algorithm, Sustainability, Vol. 7, No. 9, pp. 11679-11695, 2015.

[24]         R. W. Serth, T. Lestina, 2014, Process heat transfer: Principles, applications and rules of thumb, Academic Press,

[25]         S. Kakac, H. Liu, A. Pramuanjaroenkij, 2012, Heat exchangers: selection, rating, and thermal design, CRC press,

[26]         F. McQuiston, D. Tree, Optimum space envelopes of the finned tube heat transfer surface, ASHRAE Trans, Vol. 78, No. 2, pp. 144-152, 1972.

[27]         D. Q. Kern, 1950, Process heat transfer, Tata McGraw-Hill Education,

[28]         H. Hausen, Darstellung des Warmeuberganges in Rohren durch verallgemeinerte Potenzbeziehungen, Z. VDI Beih. Verfahrenstech, Vol. 4, pp. 91-98, 1943.

[29]         E. N. Sieder, G. E. Tate, Heat transfer and pressure drop of liquids in tubes, Industrial & Engineering Chemistry, Vol. 28, No. 12, pp. 1429-1435, 1936.

[30]         J. Henry, Headers, nozzles, and turnarounds, Heat Exchanger Design Handbook, Vol. 2, 1982.

[31]         J. Taborek, 1991, Industrial heat exchanger design practice, Wiley, New York,

[32]         Z. Guo, X. Cheng, Z. Xia, Least dissipation principle of heat transport potential capacity and its application in heat conduction optimization, Chinese science bulletin, Vol. 48, No. 4, pp. 406-410, 2003.

[33]         J. Guo, L. Cheng, M. Xu, Entransy dissipation number and its application to heat exchanger performance evaluation, Chinese science bulletin, Vol. 54, No. 15, pp. 2708-2713, 2009.

[34]         Y.-H. Oh, T.-K. Chung, M.-K. Kim, H.-K. Jung, Optimal design of electric machine using genetic algorithms coupled with direct method, IEEE Transactions on Magnetics, Vol. 35, No. 3, pp. 1742-1745, 1999.

[35]         S. Sanaye, M. Chahartaghi, Thermal—economic modelling and optimization of gas engine-driven heat pump systems, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, Vol. 224, No. 4, pp. 463-477, 2010.

[36]         A. Fanni, M. Marchesi, A. Serri, M. Usai, A greedy genetic algorithm for continuous variables electromagnetic optimization problems, IEEE Transactions on Magnetics, Vol. 33, No. 2, pp. 1900-1903, 1997.

[37]         C. R. Houck, J. Joines, M. G. Kay, A genetic algorithm for function optimization: a Matlab implementation, Ncsu-ie tr, Vol. 95, No. 09, pp. 1-10, 1995.

[38]         G. Cammarata, A. Fichera, D. Guglielmino, Optimization of a liquefaction plant using genetic algorithms, Applied energy, Vol. 68, No. 1, pp. 19-29, 2001.

[39]         J. Guo, L. Cheng, M. Xu, Multi-objective optimization of heat exchanger design by entropy generation minimization, Journal of Heat Transfer, Vol. 132, No. 8, pp. 081801, 2010. 

Volume 50, Issue 2
December 2019
Pages 246-255
  • Receive Date: 14 April 2018
  • Revise Date: 19 May 2018
  • Accept Date: 23 May 2018