Abstract
The heat sink is one of the most widely used devices for thermal management of electronic devices and automotive systems. The present study approaches the design of the heat sink with the aim of enhancing their efficiency and keeping the material cost to a minimum. The above-mentioned purpose is achieved by posing the heat sink design problem as a bi-objective optimization problem where entropy generation rate and material cost are the two conflicting objective functions. The minimum entropy generation rate reduces irreversibilities inherent in the system, thus leading to improved performance, while the reduction in material cost ensures its economic feasibility. This bi-objective optimization problem is solved using Non-dominated Sorting Genetic Algorithm (NSGA-II) in the presence of geometric restrictions and functional requirements. Heat sinks with two different flow directions, namely flow-through air cooling system and impingement-flow air cooling system, are optimized to identify the best geometric and flow parameters. Subsequently a knowledge extraction exercise is carried out over non-dominated solutions obtained from the multi-objective optimization, to establish a relationship between the objective function and involved design parameters. The knowledge extracted has significant potential to simplify the calculations performed by thermal engineering experts in the selection of the heat sink for a specific application.
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References
Ahmadi, P., Hajabdollahi, H., Dincer, I.: Cost and entropy generation minimization of a cross-flow plate fin heat exchanger using multi-objective genetic algorithm. J. Heat Transf. 133(2), 021801 (2011)
Bar-Cohen, A.: Thermal packaging for the 21st century: challenges and options. In: Fifth Therminic-International Workshop Thermal Investigations of ICs and Systems, pp. 3–6 (1999)
Bechikh, S., Datta, R., Gupta, A. (eds.): Recent Advances in Evolutionary Multi-objective Optimization. ALO, vol. 20. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-42978-6
Bejan, A., Morega, A.M.: Optimal arrays of pin fins and plate fins in laminar forced convection. J. Heat Transf. 115(1), 75–81 (1993)
Chen, C.T., Chen, H.I.: Multi-objective optimization design of plate-fin heat sinks using a direction-based genetic algorithm. J. Taiwan Inst. Chem. Eng. 44(2), 257–265 (2013)
Chen, C.T., Wu, C.K., Hwang, C.: Optimal design and control of cpu heat sink processes. IEEE Trans. Compon. Packag. Technol 31(1), 184–195 (2008)
Culham, J.R., Khan, W.A., Yovanovich, M.M., Muzychka, Y.S.: The influence of material properties and spreading resistance in the thermal design of plate fin heat sinks. J. Electron. Packag. 129(1), 76–81 (2007)
Culham, J.R., Muzychka, Y.S.: Optimization of plate fin heat sinks using entropy generation minimization. IEEE Trans. Compon. Packag. Technol. 24(2), 159–165 (2001)
Datta, R., Pandey, S.R., Segev, A.: Multi-objective optimization and knowledge extraction of plate-fin heat sink using evolutionary algorithms. In: Global Optimization Conference (GOC-2017). The World Congress on Global Optimization (WCGO) (2017)
Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Hadidi, A.: A robust approach for optimal design of plate fin heat exchangers using biogeography based optimization (BBO) algorithm. Appl. Energy 150, 196–210 (2015)
Mohsin, S., Maqbool, A., Khan, W.A.: Optimization of cylindrical pin-fin heat sinks using genetic algorithms. IEEE Trans. Compon. Packag. Technol. 32(1), 44–52 (2009)
Ndao, S., Peles, Y., Jensen, M.K.: Multi-objective thermal design optimization and comparative analysis of electronics cooling technologies. Int. J. Heat Mass Transf. 52(19), 4317–4326 (2009)
Sanaye, S., Hajabdollahi, H.: Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm. Appl. Energy 87(6), 1893–1902 (2010)
Sharma, A.K., Datta, R., Elarbi, M., Bhattacharya, B., Bechikh, S.: Practical applications in constrained evolutionary multi-objective optimization. In: Bechikh, S., Datta, R., Gupta, A. (eds.) Recent Advances in Evolutionary Multi-objective Optimization. ALO, vol. 20, pp. 159–179. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-42978-6_6
Ventola, L., et al.: Unshrouded plate fin heat sinks for electronics cooling: validation of a comprehensive thermal model and cost optimization in semi-active configuration. Energies 9, 608 (2016)
Wang, Z., Li, Y.: A combined method for surface selection and layer pattern optimization of a multistream plate-fin heat exchanger. Appl. Energy 165, 815–827 (2016)
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Pandey, S.R., Datta, R., Segev, A., Bhattacharya, B. (2020). Evolutionary Bi-objective Optimization and Knowledge Extraction for Electronic and Automotive Cooling. In: Zamuda, A., Das, S., Suganthan, P., Panigrahi, B. (eds) Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing. SEMCCO FANCCO 2019 2019. Communications in Computer and Information Science, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-37838-7_8
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