Optimal Design of Shell-and-Tube Heat Exchanger Based on Particle Swarm Optimization Technique

Document Type: Research Paper


Department of Mechatronics Engineering, College of Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran


The paper studies optimization of shell-and-tube heat exchangers using the particle swarm optimization technique. A total cost function is formulated based on initial and annual operating costs of the heat exchangers. Six variables – shell inside diameter, tube diameter, baffle spacing, baffle cut, number of tube passes and tube layouts (triangular or square) – are considered as the design parameters. The particle swarm optimization selects the parameters so that the system has minimum total cost. Although generalization is not possible for any case, for minimization of cost functions of the three different cases studied in this research, larger tube outer diameter, triangular layout, baffle cut equalling 0.25 of shell diameter and one pass for each tube result in optimum designs. The other two parameters show no fixed trend.


[1]. Selbas, R., Kizilkan, O., Reppich, M., “A new design approach for shell-and-tube heat exchangers using genetic algorithms from economic point of view”, Chem. Eng. Proc., 45, 268–275 (2006).
[2]. Muralikrishna K., Shenoy, U. V., “Heat exchanger design targets for minimum area and cost”, Institution of Chemical Engineers Trans IChemE, 78, 161-167 (2000).
[3]. Ali Kara, Y., Guraras, O., “A computer program for designing of shell-and-tube heat exchangers”, Applied Thermal Engineering, 24, 1797–1805 (2004).
[4]. Serna, M., Jimenez, A., “A compact formulation of the bell-delaware method for heat exchanger design and optimization”, Institution of Chemical Engineers Trans IChemE, 83, 539-550 (2005).
[5]. Eryener, D., “Thermoeconomic optimization of baffle spacing for shell and tube heat exchanger”, Energy Conversion and Management 47, 1478–1489 (2006).
[6]. Ozcelik, Y., “Exergetic optimization of shell and tube heat exchangers Using a genetic based algorithm”, Applied Thermal Engineering, 27, 1849–1856 (2007).
[7]. Babu, B.V., Munawar, S. A., “Differential evolution Strategies for optimal design of shell-and-tube heat exchangers”, Chemical Engineering Science, 62, 3720 –3739 (2007).
[8]. Costa, A. L .H., Queiroz, E. M., “Design optimization of shell-and-tube heat exchangers”, Applied Thermal Engineering, 28, 1798–1805 (2008).
[9]. Guo, J., Cheng, L., Xu, M., “Optimization Design of Shell-and-Tube Heat Exchanger by Entropy Generation Minimization and Genetic Algorithm”, Applied Thermal Engineering, 29, 2954–2960 (2009).
[10]. Engelbrecht, A. P., Computational Intelligence, John Wiley & Sons Ltd, USA (2007).
[11]. TEMA, Standard of tubular exchanger manufacturers association, Tarrytown, NY (1988).
[12]. Lee, P. S., Garimella, S.V., Liu, D., “Investigation of heat transfer in rectangular microchannels”, Int. J. of Heat and Mass Transfer, 48, 1688–1704 (2005).
[13]. Kern, D. Q., Process Heat Transfer, McGraw-Hill, New York (1950).
[14]. Hewitt, G.F., Heat Exchanger Design Handbook, Begell House, New York (1998).
[15]. Sinnott, R.K., Chemical Engineering Design, vol. 6, Butterworth-Heinemann (2005).
[16]. Taal, M., Bulatov, I., Klemes, J., Stehlik, P., “Cost estimation and energy price forecast for economic evaluation of retrofit projects”, Applied Thermal Engineering, 23, 1819–1835 (2003).
[17]. Haupt, R., Haupt, S., Practical Genetic Algorithm, Wiley Publication, USA (2004).
[18]. R. Hassan, B. Cohanim, O. De Weck, and G. Venter, “A comparison of particle swarm optimization and the genetic algorithm,” in Proceedings of the 1st AIAA multidisciplinary design optimization specialist conference, 18–21 (2005).
[19]. J. Vesterstrom and R. Thomsen, “A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems,” in Evolutionary Computation, CEC2004. Congress, 2, 1980–1987 (2004).
[20]. S. Panda and N. P. Padhy, “Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design,” Applied soft computing, 8, 1418–1427 (2008).
[21]. Caputo, A. C., Pelagagge, P. M., Salini, P., “Heat exchanger design based on economic optimization”, Applied Thermal Engineering, 28, 1151–1159 (2008).