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Single- and Multi-objective Design Optimization of Heat Pipes and Heat Sinks Using Jaya Algorithm and Its Variants

  • Ravipudi Venkata RaoEmail author
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Abstract

This chapter presents the application of Jaya algorithm and its variants for the single objective as well as multi-objective design optimization of heat pipes and heat sinks. Design of heat pipes and heat sinks involves a number of geometric and physical parameters with high complexity and the design processes are mostly based on trial and error. General design approaches become tedious and time consuming and these processes do not guarantee the achievement of an optimal design. Therefore, meta-heuristic based computational methods are preferred. This chapter presents the results of application of Jaya algorithm and its variants such as self-adaptive Jaya algorithm, SAMP-Jaya algorithm and SAMPE-Jaya algorithm to the design optimization problems of heat pipes and heat sinks. The results are found better than those obtained by other optimization techniques such as TLBO, Grenade Explosion Method (GEM), Niched Pareto Genetic Algorithm (NPGA), Generalized External optimization (GEO) and a hybrid multi-objective evolutionary algorithm.

Keywords

Jaya Algorithm Heat Pipe Teaching–learning-based Optimization (TLBO) Hybrid MOEA Grenade Explosion Method (GEM) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Agha, S. R. (2011). Heat pipe performance optimization: A taguchi approach. Journal of Research in Mechanical Engineering and Technology, 31, 3410–3419.Google Scholar
  2. Bertossi, R., Guilhem, N., Ayel, V., Romestant, C., & Bertin, Y. (2012). Modeling of heat and mass transfer in the liquid film of rotating heat pipes. International Journal of Thermal Sciences, 52, 40–49.CrossRefGoogle Scholar
  3. Buksa, J. J., & Hillianus, K. A. (1989). Sprite: a computer code for the optimization of space based heat pipe radiator systems. In: Energy Conversion Engineering Conference 1989; Proceeding of the 24th Intersociety. vol. 1, 39–44.Google Scholar
  4. Chong, S. H., Ooi, K. T., & Wong, T. N. (2002). Optimization of single and double layer counters flow microchannel heat sinks. Applied Thermal Engineering, 22, 1569–1585.CrossRefGoogle Scholar
  5. Cui, X., Zhu, Y., Li, Z., & Shun, S. (2014). Combination study of operation characterstics and heat transfer mechanism for pulsating heat pipe. Applied Thermal Engineering, 65, 394–402.CrossRefGoogle Scholar
  6. Dong, Q. X., Zhen, L., JiAn, M., & ZhiXin, L. (2012). Entransy dissipation analysis and optimization of separated heat pipe system. Science China, 55(8), 2126–2131.CrossRefGoogle Scholar
  7. Faghri, A. (2014). Heat pipes: Review, opportunities and challenges. Frontiers in Heat Pipes (FHP), 5, 1–48.Google Scholar
  8. Hu G., & Xu, S. (2009). Optimization design of microchannel heat sink based on SQP method and numerical simulation. In Proceedings of IEEE, 89–92.Google Scholar
  9. Husain, V., & Kim, K. Y. (2008). Optimization of a micro-channel heat sink with temperature dependent fluid properties. Applied Thermal Engineering, 28, 1101–1107.CrossRefGoogle Scholar
  10. Husain, V., & Kim, K. Y. (2010). Enhanced multi-objective optimization of a micro-channel heat sink through evolutionary algorithm coupled with multiple surrogate models. Applied Thermal Engineering, 30, 1683–1691.CrossRefGoogle Scholar
  11. Incropera, F. P., & DeWitt, D. P. (1996). Fundamentals of heat and mass transfer. New York: Wiley.Google Scholar
  12. Jeevan, K. Azid, I.A., & Seetharamu, K.N. (2004). Optimization of double layer counter flow (DLCF) micro-channel heat sink used for cooling chips directly, In Proceedings of the Eectronics Packaging Technology Conference, Singapore, 553–558.Google Scholar
  13. Jeong, M. J., Kobayami, T., & Yoshimura, S. (2007). Multidimensional visualization and clustering for multiobjective optimization of artificial satellite heat pipe design. Journal of Mechanical Science and Technology, 21, 1964–1972.CrossRefGoogle Scholar
  14. Karathanassis, I. K., Papanicolaou, E., Belessiotis, V., & Bergeles, G. C. (2013). Multi-objective design optimization of a micro heat sink for concentrating photovoltaic/thermal (CPVT) systems using a genetic algorithm. Applied Thermal Engineering, 59, 733–744.CrossRefGoogle Scholar
  15. Kim, S. J., Seo, J. K., & Do, K. H. (2003). Analytical and experimental investigation on the operational characteristics and thermal optimization of a miniature heat pipe with a grooved structure. International Journal of Heat and Mass Transfer, 46, 2051–2063.CrossRefGoogle Scholar
  16. Kiseev, V. M., Vlassov, V. V., & Muraoka, I. (2010a). Experimental optimization of capillary structured for loop heat pipes and heat switches. Applied Thermal Engineering, 30, 1312–1329.CrossRefGoogle Scholar
  17. Kiseev, V. M., Vlassov, V. V., & Muraoka, I. (2010b). Optimization of capillary structures for inverted meniscus evaporators of loop heat pipes and heat switches. International Journal of Heat and Mass Transfer, 53, 2143–2148.CrossRefGoogle Scholar
  18. Kobus, C. J., & Oshio, T. (2005a). Development of a theoretical model for predicting the thermal performance characteristics of a vertical pin-fin array heat sink under combined forced and natural convection with impinging flow. International Journal of Heat Mass Transfer, 48(6), 1053–1063.CrossRefGoogle Scholar
  19. Kobus, C. J., & Oshio, T. (2005b). Predicting the thermal performance characteristics of staggered vertical pin fin array heat sinks under combined mode radiation and mixed convection with impinging flow. International Journal of Heat Mass Transfer, 48(13), 2684–2696.CrossRefGoogle Scholar
  20. Liang, T. S., & Hung, Y. M. (2010). Experimental investigation of thermal performance and optimization of heat sink U-shape heat pipes. Energy Conversion and Management, 51, 2109–2116.CrossRefGoogle Scholar
  21. Lin, L., Chang, Z., Zang, X., & Wang, X. (2014). Optimization of geometry and flow rate distribution for double-layer microchannel heat sink. International Journal of Thermal Sciences, 78, 158–168.CrossRefGoogle Scholar
  22. Lips, S., & Lefevre, F. (2011). A general analytical model for the design conventional heat pipes. International Journal of Heat and Mass Transfer, 72, 288–298.CrossRefGoogle Scholar
  23. Maheshkumar, P., & Muraleedharan, C. (2011). Minimization of entropy generation in flat heat pipe. International Journal of Heat and Mass Transfer, 54, 645–648.CrossRefGoogle Scholar
  24. Maziuk, V., Kulakov, A., Rabetsky, M., Vasiliev, L., & Vukovic, M. (2009). Miniature heat-pipe thermal performance prediction tool-software development. Applied Thermal Engineering, 21, 559–571.CrossRefGoogle Scholar
  25. Morawietz, K., & Hermann, M. (2014). Integrated development and modeling of heat pipe solar collectors. Energy Procedia, 48, 157–162.CrossRefGoogle Scholar
  26. Nithiynandam, K., & Pitchumani, R. (2011). Analysis and optimization of latent thermal energy storage system with embedded heat pipes. International Journal of Heat and Mass Transfer, 54, 4596–4610.CrossRefGoogle Scholar
  27. Park, K., Choi, D. H., & Lee, K. S. (2004). Numerical shape optimization for high-performance of a heat sink with pin–fins. Numerical Heat Transfer Part A, 46, 909–927.CrossRefGoogle Scholar
  28. Rao, R. V. (2007). Vendor selection in a supply chain using analytic hierarchy process and genetic algorithm methods. International Journal of Services and Operations Management, 3, 355–369.CrossRefGoogle Scholar
  29. Rao, R. V., & More, K. C. (2015). Optimal design of heat pipe using TLBO (teaching-learning-based-optimization) algorithm. Energy, 80, 535–544.CrossRefGoogle Scholar
  30. Rao, R. V. (2016). Teaching learning based optimization algorithm and its engineering applications. Switzerland: Springer International Publishing.CrossRefGoogle Scholar
  31. Rao, R. V., More, K. C., Taler, J., & Oclon, P. (2016). Dimensional optimization of a micro-channel heat sink using Jaya algorithm. Applied Thermal Engineering, 103, 572–582.CrossRefGoogle Scholar
  32. Rao, R. V., & More, C. (2017). Design optimization and analysis of selected thermal devices using self-adaptive Jaya algorithm. Energy Conversion and Management, 140, 24–35.CrossRefGoogle Scholar
  33. Rao, R. V., & Rakhade, R. D. (2011). Multi-objective optimization of axial “U” shaped micro grooves heat pipe using grenade explosion method (GEM). International Journal of Advances in thermal Engineering, 2(2), 61–66.Google Scholar
  34. Riegler, R. L. (2003). Heat transfer optimization of grooved heat pipe. Columbia: University of Missouri.Google Scholar
  35. Roper, C. S. (2011). Multi-objective optimization for design of multifunctional sandwich panel heat pipes with micro-architected truss cores. International Journal of Heat and Fluid Flow, 32, 239–248.CrossRefGoogle Scholar
  36. Said, S. A., & Akash, B. A. (1999). Experimental performance of a heat pipe. International Communications in Heat and Mass Transfer, 26, 679–684.CrossRefGoogle Scholar
  37. Senthilkumar, R. (2010). Thermal analysis of heat pipe using Taguchi method. International Journal of Engineering Science and Technology, 2(4), 564–569.Google Scholar
  38. Shabgard, H., & Faghri, A. (2011). Performance characteristics of cylindrical heat pipes with multiple heat sources. Applied Thermal Engineering, 31, 3410–3419.CrossRefGoogle Scholar
  39. Shi, P. Z., Chua, K. M., Wong, Y. M., & Tan, Y. M. (2006). Design and performance optimization of miniature heat pipes in LTCC. Journal of Physics: Conference Series, 34, 142–147.Google Scholar
  40. Sousa, F. L., Vlassov, V., & Ramos, F. M. (2004). Generalized extremal optimization: An application in heat pipe design. Applied Thermal Engineering, 28, 911–931.zbMATHGoogle Scholar
  41. Subhashi, S., Sahin, B., & Kaymaz, I. (2016). Multi-objective optimization of a honeycomb heat sink using Response Surface Method. International Journal of Heat and Mass Transfer, 101, 295–302.CrossRefGoogle Scholar
  42. Tuckerman, D. B., & Pease, R. F. W. (1981). High-performance heat sinking for VLSI. IEEE Electron Devices Letters, 5, 126–129.CrossRefGoogle Scholar
  43. Turgut, O. E., & Çoban, M. T. (2016). Thermal design of spiral heat exchangers and heat pipes. Heat Mass Transfer, 53, 899–916.CrossRefGoogle Scholar
  44. Vlassov, V. V., Souza, F. L., & Takahashi, W. K. (2006). Comprehensive optimization of a heat pipe radiator assembly filled with ammonia or acetone. International Journal of Heat and Mass Transfer, 49, 4584–4595.CrossRefGoogle Scholar
  45. Wang, Z., Wang, X., & Tang, Y. (2012). Condenser design optimization and operation characteristics of a novel miniature loop heat pipe. Energy Conversion and Management, 64, 35–42.CrossRefGoogle Scholar
  46. Wang, J. C. (2014). U and L-shaped heat pipes heat sinks for cooling electronic components employed a least square smoothing method. Microelectronics and Reliability, 54, 1344–1354.CrossRefGoogle Scholar
  47. Xie, G., Chen, Z., Sunden, B., & Zhang, W. (2013). Numerical predictions of the flow and thermal performance of water-cooled single-layer and double-layer wavy microchannel heat sinks. Numerical Heat Transfer, Part A: Applications, 63, 201–225.CrossRefGoogle Scholar
  48. Yang, X., Karamanoglu, M., Luan, T., & Koziel, S. (2014). Mathematical modeling and parameter optimization of pulsating heat pipes. Journal of Computational Science, 5, 119–125.MathSciNetCrossRefGoogle Scholar
  49. Yau, Y. H., & Ahmadzadehtalpatapeh, M. (2010). A review on the application of horizontal heat pipe heat exchangers in air conditioning systems in the tropics. Applied Thermal Engineering, 30, 77–84.CrossRefGoogle Scholar
  50. Zhang, C., Chen, Y., Shi, M., & Peterson, G. P. (2009). Optimization of heat pipe with axial “U” shaped micro grooves based on a niched Pareto genetic algorithm (NPGA). Applied Thermal Engineering, 29, 3340–3345.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringS.V. National Institute of TechnologySuratIndia

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