Journals / International Journal of Intelligent Systems and Applications in Engineering / 2018 / Cilt: 6 - Sayı: 1

Multi objective design optimization of plate fin heat sinks using improved differential search algorithm

Pages
1–13
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Convergence speed of the algorithm is enhanced with the local search based perturbation schemes and this improvement yields favorable solution outputs according to the results obtained from the widely quoted optimization test problems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study provides the multi-objective optimization of plate fin heat sinks equipped with flow – through and impingement-flow air-cooling system by using Improved Differential Search algorithm.
📊
Key Findings & Data:Convergence speed of the algorithm is enhanced with the local search based perturbation schemes and this improvement yields favorable solution outputs according to the results obtained from the widely quoted optimization test problems.
💡
Conclusion & Impact:Results retrieved from the case studies show that reliable outcomes could be achieved in terms of solution accuracy through Improved Differential Search optimizer
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This study provides the multi-objective optimization of plate fin heat sinks equipped with flow – through and impingement-flow air-cooling system by using Improved Differential Search algorithm. Differential Search algorithm mimics the subsistence characteristics of the living beings through the migration process. Convergence speed of the algorithm is enhanced with the local search based perturbation schemes and this improvement yields favorable solution outputs according to the results obtained from the widely quoted optimization test problems. Improved algorithm is employed on multi-objective design optimization of plate fins heat sink considering the objective functions of entropy generation rate and total material cost. Total of seven decision variables such as oncoming stream velocity, number of fins on the plate, gap between consecutive fins, base thickness of the plate, width, length and height of the plate fin heat sink are selected to be optimized. Pareto frontiers are constructed for both flow-through and impingement flow air-cooling system design and best solutions are obtained by means of widely reputed decision-making theories of LINMAP, TOPSIS, and Shannon’s entropy theory. Results retrieved from the case studies show that reliable outcomes could be achieved in terms of solution accuracy through Improved Differential Search optimizer

🔖

Cite This Article

TURGUT, O. E. (2018). Multi objective design optimization of plate fin heat sinks using improved differential search algorithm. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 6 - Sayı: 1, 1–13. https://ajindex.com/articles/167201

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (1)

  1. C.T. Chen, H.I. Chen, “Multi objective optimization design of plate-fin heat sinks using a direction-based genetic algorithm,” J. Taiwan Inst. Chem., vol.44, pp.257 – 265, 2013 [2] A.D. Kraus, A. Bar-Cohen, “Design and analysis of heat sinks”, Wiley, New York, 1995. [3] J.R Culham, Y.S. Muzychka, “Optimization of plate fin heat sinks using entropy generation minimization,” IEEE T. Compo Pack T., vol. 24, pp. 159 – 165, 2001. [4] E.M. Sparrow, B.R., Baliga, and S.V. Patankar, “Forced convection heat transfer from a shrouded fin arrays with and without tip clearance,” J. Heat Trans T. ASME, vol.100, pp.572-579, 1978. [5] N. Goldberg, “Narrow channel forces air heat sink,” IEEE Trans. Compon. Packag. Manuf. Tech, vol.7, pp.154-159, 1984 [6] R.W. Knight, J.S. Goodling, D.J. Hall, “Optimal thermal design of forced convection heat sinks- Analytical”. J Electron Packaging, vol.113, pp.313-321, 1991. [7] R.W. Knight, J.S. Goodling, Gross. B.E. “Optimal thermal design of air-cooled forced convection finned heat sinks – Experimental verification,” IEEE Trans. Compon. Packag. Manuf. Tech, vol.15, pp.754-760, 1992. [8] A. Bejan, “Entropy generation through heat and fluid flow,” Wiley, New York, 1982. [9] W.A. Khan, J.R. Culham, M.M. Yovanovich, “Optimization of pin-fin heat sinks using entropy generation minimization,” IEEE Trans. Compon. Packag. Manuf. Tech., vol.28, pp.247-254, 2005 [10] S. Ndao, Y. Peles, M.K. Jensen, “Multi-objective thermal design optimization and comparative analysis of electronic cooling technologies,” Int. J Heat Mass Transf, vol. 52, pp.4317- 4326, 2009 [11] M.Iyengar, A. Bar-Cohen, “Least-energy optimization of forced convection plate-fin heat sinks,” IEEE T. Compo Pack T., vol.26, pp.62-70, 2003 [12] A. Bejan, A.M. Morega, “Optimal arrays of pin fins and plate fins in laminar forced convection,” J. Heat Trans T. ASME, vol.115, pp.75-81, 1993 [13] I.K. Karathanassis, E. Papanicolaou, V. Belessiotis, G.C. Bergeles, “Multi-objective design optimization of a micro heat sink for Concentrating Photovoltaic/Thermal (CPVT) systems using a genetic algorithm,” Appl. Therm. Eng. vol.59, pp.733-744, 2013 [14] R. Baby, C. Balaji, “Thermal optimization of PCM based pin fin heat sinks: An experimental study,” Appl. Therm. Eng. vol.54, pp.65-77, 2013 [15] D.K. Kim, “Thermal optimization of plate-fin heat sinks with fins of variable thickness under natural convection,” Int. J. Heat Mass Transfer, vol.55, pp.752 – 761, 2012. [16] S. Soleimani, D.D. Ganji