0
Research Papers: Electronic Cooling

Nonlocal Modeling and Swarm-Based Design of Heat Sinks

[+] Author and Article Information
Ivan Catton

Morrin-Gier-Martinelli
Heat Transfer Memorial Laboratory,
Department of Mechanical
and Aerospace Engineering,
School of Engineering and Applied Science,
University of California, Los Angeles,
48-121 Engineering IV,
420 Westwood Plaza,
Los Angeles, CA 90095-1597

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received March 22, 2013; final manuscript received August 21, 2013; published online October 25, 2013. Assoc. Editor: Giulio Lorenzini.

J. Heat Transfer 136(1), 011401 (Oct 25, 2013) (11 pages) Paper No: HT-13-1158; doi: 10.1115/1.4025300 History: Received June 29, 2012; Revised February 26, 2013

Cooling electronic chips to satisfy the ever-increasing heat transfer demands of the electronics industry is a perpetual challenge. One approach to addressing this is through improving the heat rejection ability of air-cooled heat sinks, and nonlocal thermal-fluid-solid modeling based on volume averaging theory (VAT) has allowed for significant strides in this effort. A number of optimization methods for heat sink designers who model heat sinks with VAT can be envisioned due to VAT's singular ability to rapidly provide solutions, when compared to computational fluid dynamics (CFD) approaches. The particle swarm optimization (PSO) method appears to be an attractive multiparameter heat transfer device optimization tool; however, it has received very little attention in this field compared to its older population-based optimizer cousin, the genetic algorithm (GA). The PSO method is employed here to optimize smooth and scale-roughened straight-fin heat sinks modeled with VAT by minimizing heat sink thermal resistance for a specified pumping power. A new numerical design tool incorporates the PSO method with a VAT-based heat sink solver. Optimal designs are obtained with this new tool for both types of heat sinks, the performances of the heat sink types are compared, the performance of the PSO method is discussed with reference to the GA method, and it is observed that this new method yields optimal designs much quicker than traditional approaches. This study demonstrates, for the first time, the effectiveness of combining a VAT-based nonlocal thermal-fluid-solid model with population-based optimization methods, such as PSO, to design heat sinks for electronics cooling applications. The VAT-based nonlocal modeling method provides heat sink design capabilities, in terms of solution speed and model rigor, that existing modeling methods do not match.

FIGURES IN THIS ARTICLE
<>
Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.

References

Holland, J. H., 1992, Adaptation in Natural and Artificial Systems: An Introductory Analysis With Applications to Biology, Control and Artificial Intelligence, MIT Press, Cambridge, MA.
Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
Queipo, N., Devarakonda, R., and Humphrey, J. A. C., 1994, “Genetic Algorithms for Thermosciences Research: Application to the Optimized Cooling of Electronic Components,” Int. J. Heat Mass Transfer, 37(6), pp. 893–908. [CrossRef]
Manivannan, S., Devi, S. P., and Arumugam, R., “Optimization of Flat Plate Heat Sink Using Genetic Algorithm,” Proceedings of 2011 1st International Conference on Electrical Energy Systems (ICEES), pp. 78–81.
Mohsin, S., Maqbool, A., and Khan, W. A., 2009, “Optimization of Cylindrical Pin-Fin Heat Sinks Using Genetic Algorithms,” IEEE Trans. Compon. Packag. Technol., 32(1), pp. 44–52. [CrossRef]
Ndao, S., Peles, Y., and Jensen, M. K., 2009, “Multi-Objective Thermal Design Optimization and Comparative Analysis of Electronics Cooling Technologies,” Int. J. Heat Mass Transfer, 52(19-20), pp. 4317–4326. [CrossRef]
Fabbri, G., 2000, “Heat Transfer Optimization in Corrugated Wall Channels,” Int. J. Heat Mass Transfer, 43(23), pp. 4299–4310. [CrossRef]
Jian-hui, Z., Chun-xin, Y., and Li-na, Z., 2009, “Minimizing the Entropy Generation Rate of the Plate-Finned Heat Sinks Using Computational Fluid Dynamics and Combined Optimization,” Appl. Therm. Eng., 29(8-9), pp. 1872–1879. [CrossRef]
Wildi-Tremblay, P., and Gosselin, L., 2007, “Layered Porous Media Architecture for Maximal Cooling,” Int. J. Heat Mass Transfer, 50(3–4), pp. 464–478. [CrossRef]
Tye-Gingras, M., and Gosselin, L., 2008, “Thermal Resistance Minimization of a Fin-and-Porous-Medium Heat Sink With Evolutionary Algorithms,” Numer. Heat Transfer, Part A, 54(4), pp. 349–366. [CrossRef]
Leblond, G., and Gosselin, L., 2008, “Effect of Non-Local Equilibrium on Minimal Thermal Resistance Porous Layered Systems,” Int. J. Heat Fluid Flow, 29(1), pp. 281–291. [CrossRef]
Kennedy, J., and Eberhart, R., 1995, “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks, Vol. 1944, pp. 1942–1948.
Eberhart,R., and Kennedy, J., 1995, “A New Optimizer Using Particle Swarm Theory,” Proceedings of the Sixth International Symposium on Micro Machine and Human Science, MHS '95, pp. 39–43.
Eberhart, R., and Shi, Y., 1998, “Comparison Between Genetic Algorithms and Particle Swarm Optimization,” Evolutionary Programming VII, V.Porto, N.Saravanan, D.Waagen, and A.Eiben, eds., Springer, Berlin, pp. 611–616.
Eberhart, R. C., and Shi, Y., 2000, “Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization,” Proceedings of the 2000 Congress on Evolutionary Computation, Vol. 81, pp. 84–88.
Eberhart, and Yuhui, S., 2001, “Particle Swarm Optimization: Developments, Applications and Resources,” Proceedings of the 2001 Congress on Evolutionary Computation, Vol. 81, pp. 81–86.
Shi, Y., and Eberhart, R. C., 1999, “Empirical study of particle swarm optimization,” Proceedings of the 1999 Congress on Evolutionary Computation, CEC 99, Vol. 1953, p. 1950.
Xiaohui, H., and Eberhart, R., 2002, “Multiobjective Optimization Using Dynamic Neighborhood Particle Swarm Optimization,” Proceedings of the 2002 Congress on Evolutionary Computation, CEC '02, pp. 1677–1681.
Xiaohui, H., Eberhart, R. C., and Yuhui, S., 2003, “Particle Swarm With Extended Memory for Multiobjective Optimization,” Proceedings of the 2003 IEEE Swarm Intelligence Symposium, SIS '03, pp. 193–197.
Bureerat, S., and Srisomporn, S., 2010, “Optimum Plate-Fin Heat Sinks by Using a Multi-Objective Evolutionary Algorithm,” Eng. Optim., 42(4), pp. 305–323. [CrossRef]
Kanyakam, S., and Bureerat, S., 2011, “Multiobjective Evolutionary Optimization of Splayed Pin-Fin Heat Sink,” Eng. Appl. Comput. Fluid Mech., 5(4), pp. 553–565.
Kanyakam, S., and Bureerat, S., 2012, “Multiobjective Optimization of a Pin-Fin Heat Sink Using Evolutionary Algorithms,” J. Electron. Packag., 134(2), pp. 021008–021008. [CrossRef]
Xiong, Q., Li, B., Chen, F., Ma, J., Ge, W., and Li, J., 2010, “Direct Numerical Simulation of Sub-Grid Structures in Gas–Solid Flow—GPU Implementation of Macro-Scale Pseudo-Particle Modeling,” Chem. Eng. Sci., 65(19), pp. 5356–5365. [CrossRef]
Xiong, Q., Li, B., Zhou, G., Fang, X., Xu, J., Wang, J., He, X., Wang, X., Wang, L., Ge, W., and Li, J., 2012, “Large-Scale DNS of Gas–Solid Flows on Mole-8.5,” Chem. Eng. Sci., 71(0), pp. 422–430. [CrossRef]
Xiong, Q., Deng, L., Wang, W., and Ge, W., 2011, “SPH method for Two-Fluid Modeling of Particle–Fluid Fluidization,” Chem. Eng. Sci., 66(9), pp. 1859–1865. [CrossRef]
Catton, I., 2011, “Conjugate Heat Transfer Within a Heterogeneous Hierarchical Structure,” J. Heat Transfer, 133(10), p. 103001. [CrossRef]
Anderson, T. B., and Jackson, R., 1967, “Fluid Mechanical Description of Fluidized Beds. Equations of Motion,” Ind. Eng. Chem. Fundam., 6(4), pp. 527–539. [CrossRef]
Slattery, J. C., 1967, “Flow of Viscoelastic Fluids Through Porous Media,” AIChE J., 13(6), pp. 1066–1071. [CrossRef]
Marle, C. M., 1967, “Ecoulements monophasiques en milieu poreux,” Rev. Inst. Francais du Petrole, 22, pp. 1471–1509.
Whitaker, S., 1967, “Diffusion and Dispersion in Porous Media,” AIChE J., 13(3), pp. 420–427. [CrossRef]
Zolotarev, P. P., and Radushkevich, L. V., 1968, “An Approximate Analytical Solution of the Internal Diffusion Problem of Dynamic Absorption in the Linear Region of an Isotherm,” Russ. Chem. Bull., 17(8), pp. 1818–1820. [CrossRef]
Slattery, J. C., 1980, Momentum, Energy and Mass Transfer in Continua, Krieger, Malabar, FL.
Kaviany, M., 1995, Principles of Heat Transfer in Porous Media, Springer, New York.
Gray, W. G., Leijnse, A., Kolar, R. L., and Blain, C. A., 1993, Mathematical Tools for Changing Spatial Scales in the Analysis of Physical Systems, CRC Press, Boca Raton, FL.
Whitaker, S., 1977, “Simultaneous Heat, Mass and Momentum Transfer in Porous Media: A Theory of Drying,” Adv. Heat Transfer, 13, pp. 119–203. [CrossRef]
Whitaker, S., 1997, “Volume Averaging of Transport Equations,” Int. Ser. Adv. Fluid Mech., 13, pp. 1–60.
Kheifets, L. I., and Neimark, A. V., 1982, Multiphase Processes in Porous Media, Khimia, Moscow.
Dullien, F. A. L., 1979, Porous Media Fluid Transport and Pore Structure, Academic Press, New York.
Adler, P. M., 1992, Porous Media: Geometry and Transports, Butterworth-Heinemann, Waltham, MA.
Travkin, V., and Catton, I., 1992, Fundamentals of Heat Transfer in Porous Media, HTD Vol. 193, ASME, New York.
Travkin, V., and Catton, I., 1995, “A Two-Temperature Model for Turbulent Flow and heat Transfer in a Porous Layer,” J. Fluids Eng., 117(1), pp. 181–188. [CrossRef]
Travkin, V. S., and Catton, I., 1998, “Porous Media Transport Descriptions—Non-Local, Linear and Non-Linear Against Effective Thermal/Fluid Properties,” Adv. Colloid Interface Sci., 76-77(0), pp. 389–443. [CrossRef]
Travkin, V. S., Catton, I., and Gratton, L., 1993, Heat Transfer in Porous Media, HTD Vol. 240, ASME, New York.
Travkin, V. S., Catton, I., Hu, K., Ponomarenko, A. T., and Shevchenko, V. G., 1999, Application of Porous Media Methods for Engineered Materials, AMD Vol. 233, ASME, New York.
Nakayama, A., Ando, K., Yang, C., Sano, Y., Kuwahara, F., and Liu, J., 2009, “A Study on Interstitial Heat Transfer in Consolidated and Unconsolidated Porous Media,” Heat Mass Transfer, 45(11), pp. 1365–1372. [CrossRef]
Nakayama, A., and Kuwahara, F., 2008, “A General Macroscopic Turbulence Model for Flows in Packed Beds, Channels, Pipes, and Rod Bundles,” J. Fluids Eng., 130(10), p. 101205. [CrossRef]
Nakayama, A., Kuwahara, F., and Hayashi, T., 2004, “Numerical Modelling for Three-Dimensional Heat and Fluid Flow Through a Bank of Cylinders in Yaw,” J. Fluid Mech., 498, pp. 139–159. [CrossRef]
Nakayama, A., Kuwahara, F., and Kodama, Y., 2006, “An Equation for Thermal Dispersion Flux Transport and Its Mathematical Modelling for Heat and Fluid Flow in a Porous Medium,” J. Fluid Mech., 563(1), pp. 81–96. [CrossRef]
Travkin, V. S., and Catton, I., 2001, “Transport Phenomena in Heterogeneous Media Based on Volume Averaging Theory,” Advances in Heat Transfer, G. G.Hari, and A. H.Charles, eds., Elsevier, New York, pp. 1–144.
Geb, D., Zhou, F., DeMoulin, G., and Catton, I., 2013, “Genetic Algorithm Optimization of a Finned-Tube Heat Exchanger Modeled With Volume-Averaging Theory,” ASME J. Heat Transfer, 135(8), pp. 082602–082602. [CrossRef]
Zhou, F., DeMoulin, G. W., Geb, D. J., and Catton, I., 2012, “Closure for a Plane Fin Heat Sink With Scale-Roughened Surfaces for Volume Averaging Theory (VAT) Based Modeling,” Int. J. Heat Mass Transfer, 55(25–26), pp. 7677–7685. [CrossRef]
Zhou, F., and Catton, I., 2013, “Obtaining Closure for a Plane Fin Heat Sink With Elliptic Scale-Roughened Surfaces for Volume Averaging Theory (VAT) Based Modeling,” Int. J. Therm. Sci., 71, pp. 264–273. [CrossRef]
Zhou, F., and Catton, I., 2013, “A Numerical Investigation of Turbulent Flow and Heat Transfer in Rectangular Channels With Elliptic Scale-Roughened Walls,” ASME J. Heat Transfer, 135(8), p. 081901. [CrossRef]
Zhou, F., Hansen, N. E., Geb, D. J., and Catton, I., 2011, “Determination of the Number of Tube Rows to Obtain Closure for Volume Averaging Theory Based Model of Fin-and-Tube Heat Exchangers,” ASME J. Heat Transfer, 133(12), p. 121801. [CrossRef]
Zhou, F., and Catton, I., 2012, “Volume Averaging Theory (VAT) Based Modeling and Closure Evaluation for Fin-and-Tube Heat Exchangers,” Heat Mass Transfer, 48, pp. 1813–1823. [CrossRef]
Geb, D., Zhou, F., and Catton, I., 2012, “Internal Heat Transfer Coefficient Determination in a Packed Bed From the Transient Response Due to Solid Phase Induction Heating,” ASME J. Heat Transfer, 134(4), p. 042604. [CrossRef]
Geb, D., Ge, M., Chu, J., and Catton, I., 2013, “Measuring Transport Coefficients in Heterogeneous and Hierarchical Heat Transfer Devices,” ASME J. Heat Transfer, 135(6), p. 061101. [CrossRef]
Geb, D., Lerro, A., Sbutega, K., and Catton, I., 2013, “Internal Transport Coefficient Measurements in Random Fiber Matrix Heat Exchangers,” J. Therm. Sci. Eng. Appl. (in press).
Geb, D., 2013, “Hierarchical Modeling for Population-Based Heat Exchanger Design,“ Ph.D. thesis, UCLA, Los Angeles.
Zhou, F., Hansen, N. E., Geb, D. J., and Catton, I., 2011, “Obtaining Closure for Fin-and-Tube Heat Exchanger Modeling Based on Volume Averaging Theory (VAT),” ASME J. Heat Transfer, 133(11), p. 111802. [CrossRef]
Shi, Y., and Eberhart, R., 1998, “A Modified Particle Swarm Optimizer,” Proceedings of the 1998 IEEE International Conference on IEEE World Congress on Computational Intelligence Evolutionary Computation, pp. 69–73.
Xiaohui, H., Yuhui, S., and Eberhart, R., 2004, “Recent Advances in Particle Swarm,” Proceedings of Congress on Evolutionary Computation, CEC2004, Vol. 91, pp. 90–97.
Chang, S. W., Liou, T.-M., and Lu, M. H., 2005, “Heat Transfer of Rectangular Narrow Channel With Two Opposite Scale-Roughened Walls,” Int. J. Heat Mass Transfer, 48(19-20), pp. 3921–3931. [CrossRef]
Lyons, A., Krishnan, S., Mullins, J., Hodes, M., and Hernon, D., 2009, “Advanced Heat Sinks Enabled by Three-Dimensional Printing,” Twentieth Annual International Solid Freeform Fabrication Symposium.
Kays, W. M., and London, A. L., 1984, Compact Heat Exchangers, McGraw-Hill, New York.

Figures

Grahic Jump Location
Fig. 2

Flow chart of the VAT-based heat sink simulation routine

Grahic Jump Location
Fig. 1

Illustration of a straight-fin heat sink with tapered, (a) smooth and (b) scale-roughed surface fins

Grahic Jump Location
Fig. 3

Flow chart of PSO algorithm [62]

Grahic Jump Location
Fig. 4

Evolution of thermal resistance during the (a) PSO and (b) GA optimizations of a smooth surface straight-fin heat sink. Thin, light colored lines indicate the individual trials while thick, dark colored lines indicate the average of the ten trials.

Grahic Jump Location
Fig. 5

Evolution of the scaled design parameters during the (a) PSO and (b) GA optimizations of a smooth surface straight-fin heat sink. Thin, light colored lines indicate the individual trials while thick, dark colored lines indicate the average of the ten trials.

Grahic Jump Location
Fig. 8

Nonlocal fluid (left) and solid (right) temperature fields for the optimal scale-roughened straight-fin heat sink found by the PSO after its (a) first, (b) fourth, and (c) final iteration, along with those for the (d) optimal smooth straight-fin heat sink. The fully developed velocity field profiles and the 90 °C contour lines are indicated superimposed on the fluid and solid temperature fields, respectively.

Grahic Jump Location
Fig. 6

Evolution of thermal resistance during the (a) PSO and (b) GA optimizations of a scale-roughened straight-fin heat sink

Grahic Jump Location
Fig. 7

Evolution of the scaled design parameters during the (a) PSO and (b) GA optimizations of a scale-roughened straight-fin heat sink

Tables

Errata

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In