Adaptive symbiotic organisms search technique for cost optimization of shell and tube heat exchanger

Yıl 2024, Cilt: 10 Sayı: 4, 857 - 867, 29.07.2024

Jiten Makadia

Öz

Nature inspired meta heuristics like swarm intelligence (SI), Artificial neural networks (ANN), evolutionary computing (EC) etc. have been used by researchers to solve single and multi-objective optimization problems of different fields. This work uses a novel α-SOS (Adaptive sym-biotic organisms search) algorithm for cost optimization of shell and tube heat exchanger. This algorithm is implemented for cost optimization of two benchmark STHX problem which are used by several researchers. Validation of the results is presented by comparing the geometric, flow and operational parameters of the same design problems when solved using particle swarm optimization (PSO), Alpha tuned elephant herding optimization technique (α-EHO) and Gravitation search algorithm (GSA). Result indicates a 4.73% and 11.3% reduction in cost for both the case study respectively when compared to same problems solved using PSO. Although when comparing with α-EHO, results does not indicate any substantial difference. Furthermore, operational, and geometric dimensions are also calculated. This algorithm can be eventually applied to real world design engineering problems.

Anahtar Kelimeler

Adaptive SOS, Alpha EHO, Cost, GSA, Optimization, Nature Inspired Metaheuristics, STHX

Kaynakça

• [1] Asadi M, Song Y, Sunden B, Xie G. Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm. Appl Therm Engineer 2014;73:1032–1040. [CrossRef]
• [2] Makadia J, Sankhavara C. Application of symbiotic organisms search technique for design optimization of shell and tube heat exchanger from economic point of view. In: 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). IEEE; 2020. pp. 1–6. [CrossRef]
• [3] Fesanghary M, Damangir E, Soleimani I. Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm. Appl Therm Engineer 2009;29:1026–1031. [CrossRef]
• [4] Hadidi A, Hadidi M, Nazari A. A new design approach for shell-and-tube heat exchangers using imperialist competitive algorithm (ICA) from economic point of view. Energy Conver Manage 2013;67:66–74. [CrossRef]
• [5] Şahin AŞ, Kılıç B, Kılıç U. Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm. Energy Conver Manage 2011;52:3356–3362. [CrossRef]
• [6] Hadidi A, Nazari A. Design and economic optimization of shell-and-tube heat exchangers using biogeography-based (BBO) algorithm. Appl Therm Engineer 2013;51:1263–1272. [CrossRef]
• [7] Serna-González M, Ponce-Ortega JM, Castro-Montoya AJ, Jiménez-Gutiérrez A. Feasible design space for shell-and-tube heat exchangers using the Bell-Delaware method. Ind Engineer Chem Res 2007;46:143–155. [CrossRef]
• [8] Mizutani FT, Pessoa FL, Queiroz EM, Hauan S, Grossmann IE. Mathematical programming model for heat-exchanger network synthesis including detailed heat- exchanger designs. 1. Shell-and-tube heat-exchanger design. Ind Engineer Chem Res 2003;42:4009–4018. [CrossRef]
• [9] Caputo AC, Pelagagge PM, Salini P. Heat exchanger design based on economic optimisation. Appl Therm Engineer 2008;28:1151–1159. [CrossRef]
• [10] Hewitt GF, Barbosa J. Heat Exchanger Design Handbook. New York: Begell House; 2008.
• [11] Kern DQ. Process Heat Transfer. New York: McGraw-Hill; 1950.
• [12] Sinnott RK. Coulson & Richardson’s Chemical Engineering Vol. 6. 4th ed. Oxford, MA: Elsevier Butterworth-Heinemann; 2005.
• [13] Taal M, Bulatov I, Klemeš J, Stehlı́k P. Cost estimation and energy price forecasts for economic evaluation of retrofit projects. Appl Therm Engineer 2003;23:1819–1835. [CrossRef]
• [14] Patel VK, Rao RV. Design optimization of shell-and-tube heat exchanger using particle swarm optimization technique. Appl Therm Engineer 2010;30:1417–1425. [CrossRef]
• [15] Tejani GG, Savsani VJ, Patel VK. Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization. J Comput Des Engineer 2016;3:226–249. [CrossRef]
• [16] Makadia J, Sankhavara CD. Optimization of shell and tube heat exchanger using alpha tuning Elephant Herding Optimization (EHO) technique. Int J Engineer Res Africa 2021;52:92–101. [CrossRef]
• [17] Umam MIH, Santosa B. A hybrid symbiotic organisms search algorithm with variable neighbourhood search for solving symmetric and asymmetric traveling salesman problem. IOP Conf Ser Mater Sci Engineer 2018;337:012005. [CrossRef]
• [18] Mohanty DK. Gravitational search algorithm for economic optimization design of a shell and tube heat exchanger. Appl Therm Engineer 2016;107:184–193. [CrossRef]
• [19] Hanafi MFIM, Bahreininejad A, Uddin N. Optimization of shell and tube heat exchanger using the water cycle algorithm. IOP Conf Ser Mater Sci Engineer 2021;1173:012005. [CrossRef]
• [20] Rao RV, Saroj A. Economic optimization of shell-and-tube heat exchanger using Jaya algorithm with maintenance consideration. Appl Therm Engineer 2017;116:473– 487. [CrossRef]
• [21] Lemos JC, Costa AL, Bagajewicz MJ. Design of shell and tube heat exchangers considering the interaction of fouling and hydraulics. AIChE J 2022;68:e17586. [CrossRef]
• [22] Mohanty DK. Application of firefly algorithm for design optimization of a shell and tube heat exchanger from economic point of view. Int J Therm Sci 2016;102:228–238. [CrossRef]
• [23] Nakao A, Valdman A, Costa AL, Bagajewicz MJ, Queiroz EM. Incorporating fouling modeling into shell-and-tube heat exchanger design. Ind Engineer Chem Res 2017;56:4377–4385. [CrossRef]
• [24] Çelik E. A powerful variant of symbiotic organisms search algorithm for global optimization. Engineer Appl Artif Intell 2020;87:103294. [CrossRef]
• [25] Lahiri SK, Khalfe N. Improve shell and tube heat exchangers design by hybrid differential evolution and ant colony optimization technique. Asia-Pac J Chem Engineer 2014;9:431–448. [CrossRef]
• [26] Rao RV, Majethia M. Design optimization of shell-and-tube heat exchanger using Rao algorithms and their variants. Therm Sci Engineer Prog 2022;36:101520. [CrossRef]
• [27] Sai JP, Rao BN. Non-dominated sorting genetic algorithm II and particle swarm optimization for design optimization of shell and tube heat exchanger. Int Comm Heat Mass Transf 2022;132:105896. [CrossRef]
• [28] Montaño ODL, Gómez-Castro FI, Gutierrez-Antonio C. Design and optimization of a shell-and-tube heat exchanger using the univariate marginal distribution algorithm. Comput Aided Chem Engineer 2021;50:43–49. [CrossRef]
• [29] Rao RV, Saroj A. Constrained economic optimization of shell-and-tube heat exchangers using elitist-Jaya algorithm. Energy 2017;128:785–800. [CrossRef]
• [30] Daneshparvar MR, Beigzadeh R. Multi-objective optimization of helical baffles in the shell-and-tube heat exchanger by computational fluid dynamics and genetic algorithm. Energy Rep 2022;8:11064–11077. [CrossRef]
• [31] Caputo AC, Federici A, Pelagagge PM, Salini P. On the selection of design methodology for shell-and-tube heat exchangers optimization problems. Therm Sci Engineer Prog 2022;34:101384. [CrossRef]
• [32] Nia MF, Farzad H, Ansari AB, Ghodrat M, Nassab SAG, Behnia M. Performance improvement of a tubular heat exchanger by tube arrangement optimization using simulated annealing algorithm and blocked-off method. Therm Sci Engineer Prog 2023;40:101793. [CrossRef]
• [33] Mudhsh M, El-Said EM, Aseeri AO, Almodfer R, Abd Elaziz M, Elshamy SM, et al. Modelling of thermo-hydraulic behavior of a helical heat exchanger using machine learning model and fire hawk optimizer. Case Stud Therm Engineer 2023:103294. [CrossRef]
• [34] Alazwari MA, Safaei MR. Combination effect of baffle arrangement and hybrid nanofluid on thermal performance of a shell and tube heat exchanger using 3-D homogeneous mixture model. Mathematics 2021;9:881. [CrossRef]
• [35] Nadi M, Ehyaei MA, Ahmadi A, Turgut OE. Multi-objective particle swarm optimization of the k-type shell and tube heat exchanger (case study). J Therm Engineer 2021;7:570–583. [CrossRef]