Journal of Thermal Analysis and Calorimetry

, Volume 136, Issue 4, pp 1869–1877 | Cite as

Heat transfer in an eight-pass oscillating loop heat pipe equipped with cooling tower

An experimental study
  • Javad Abolfazli EsfahaniEmail author
  • Soheil Safaiyan
  • Saman Rashidi


In this research, a series of experiments have been performed to study the thermal resistance of an oscillating heat pipe equipped with cooling tower. The effects of filling ratio and input heating power on the thermal resistance of the heat pipe and temperatures of different sections of evaporator and condenser of the heat pipe are investigated and discussed. All tests are taken for input heating power and filling ratio in the ranges of 20–200 W and 10–60%, respectively. A correlation for the thermal resistance is presented, which the effects of input heating power and filling ratio are taken into account in this correlation. The results showed that the heat pipe with filling ratio of 40% and input heating power of 160 W has the minimum value of thermal resistance among all cases considered in this research. Moreover, the thermal resistance decreases about 86% as the input heating power increases in the range of 20–120 W, while this reduction is only 23% by increasing the input heating power in the range of 160–200 W.


Oscillating heat pipe Thermal resistance Cooling tower Filling ratio Input heating power 

List of symbols


Filling ratio (%)


Specific heat at constant pressure (J kg−1 K−1)


Current (A)


Mass flow rate (kg s−1)


Power (W)


Heat load (W)


Thermal resistant (K W−1)


Temperature (K)


Mean temperature of the condenser (K)


Mean temperature of the evaporator (K)


Voltage (V)











Different locations on the evaporator


Different locations on the condenser



This research was supported by the Office of the Vice Chancellor for Research, Ferdowsi University of Mashhad, under Grant No. 45784.


  1. 1.
    Javani N, Dincer I, Naterer GF, Yilbas BS. Heat transfer and thermal management with PCMs in a Li-ion battery cell for electric vehicles. Int J Heat Mass Transfer. 2014;72:690–703.CrossRefGoogle Scholar
  2. 2.
    Javani N, Dincer I, Naterer GF, Rohrauer GL. Modeling of passive thermal management for electric vehicle battery packs with PCM between cells. Appl Therm Eng. 2014;73:307–16.CrossRefGoogle Scholar
  3. 3.
    Ishaq H, Dincer I, Naterer GF. Exergy-based thermal management of a steelmaking process linked with a multi-generation power and desalination system. Energy. 2018;159:1206–17.CrossRefGoogle Scholar
  4. 4.
    Gi K, Maezawa S. CPU cooling of notebook PC by oscillating heat pipe. In: Proceedings of eleventh international heat pipe conference, Tokyo, 1999;469–472.Google Scholar
  5. 5.
    Akbari A, Saidi MS. Experimental investigation of nanofluid stability on thermal performance and flow regimes in pulsating heat pipe. J Therm Anal Calorim. 2018. Scholar
  6. 6.
    Qu J, Wang C, Li X, Wang H. Heat transfer performance of flexible oscillating heat pipes for electric/hybrid-electric vehicle battery thermal management. Appl Therm Eng. 2018;135:1–9.CrossRefGoogle Scholar
  7. 7.
    Pachghare PR, Mahalle AM. Effect of pure and binary fluids on closed loop pulsating heat pipe thermal performance. Proc. Eng. 2013;51:624–9.CrossRefGoogle Scholar
  8. 8.
    Wang Z, Yang W. A review on loop heat pipe for use in solar water heating. Energy Build. 2014;79:143–54.CrossRefGoogle Scholar
  9. 9.
    Han X, Wang X, Zheng H, Xu X, Chen G. Review of the development of pulsating heat pipe for heat dissipation. Renew Sustain Energy Rev. 2016;59:692–709.CrossRefGoogle Scholar
  10. 10.
    Zhang X, Huo J, Wang S. Experimental investigation on temperature oscillation in a miniature loop heat pipe with flat evaporator. Exp Thermal Fluid Sci. 2012;37:29–36.CrossRefGoogle Scholar
  11. 11.
    Song H, Zhi-chun L, Jing Z, Chi J, Jin-guo Y, Wei L. Experimental study of an ammonia loop heat pipe with a flat plate evaporator. Int J Heat Mass Transfer. 2016;102:1050–5.CrossRefGoogle Scholar
  12. 12.
    Sun Q, Qu J, Li X, Yuan J. Experimental investigation of thermo-hydrodynamic behavior in a closed loop oscillating heat pipe. Exp Thermal Fluid Sci. 2017;82:450–8.CrossRefGoogle Scholar
  13. 13.
    Qu J, Zhao J, Rao Z. Experimental investigation on the thermal performance of three-dimensional oscillating heat pipe. Int J Heat Mass Transfer. 2017;109:589–600.CrossRefGoogle Scholar
  14. 14.
    Qu J, Wu H, Cheng P. Thermal performance of an oscillating heat pipe with Al2O3–water nanofluids. Int Commun Heat Mass Transfer. 2010;37:111–5.CrossRefGoogle Scholar
  15. 15.
    Riyad Tanshen Md, Munkhbayar B, Nine MdJ, Chung H, Jeong H. Effect of functionalized MWCNTs/water nanofluids on thermal resistance and pressure fluctuation characteristics in oscillating heat pipe. Int Commun Heat Mass Transfer. 2013;48:93–8.CrossRefGoogle Scholar
  16. 16.
    Qu J, Wu H. Thermal performance comparison of oscillating heat pipes with SiO2/water and Al2O3/water nanofluids. Int J Therm Sci. 2011;50:1954–62.CrossRefGoogle Scholar
  17. 17.
    Hung YH, Teng TP, Lin BG. Evaluation of the thermal performance of a heat pipe using alumina nanofluids. Exp Thermal Fluid Sci. 2013;44:504–11.CrossRefGoogle Scholar
  18. 18.
    Menlik T, Sozen A, Gürü M, Oztas S. Heat transfer enhancement using MgO/water nanofluid in heat pipe. J Energy Inst. 2015;88:247–57.CrossRefGoogle Scholar
  19. 19.
    Yin D, Wang H, Ma HB, Ji YL. Operation limitation of an oscillating heat pipe. Int J Heat Mass Transfer. 2016;94:366–72.CrossRefGoogle Scholar
  20. 20.
    Qu J, Li X, Cui Y, Wang Q. Design and experimental study on a hybrid flexible oscillating heat pipe. Int J Heat Mass Transfer. 2017;107:640–5.CrossRefGoogle Scholar
  21. 21.
    Valipour MS, Rashidi S, Masoodi R. Magnetohydrodynamics flow and heat transfer around a solid cylinder wrapped with a porous ring. J Heat Transfer. 2014;136:062601–9.CrossRefGoogle Scholar
  22. 22.
    Rashidi A, Fathi H, Brilakis I. Innovative stereo vision-based approach to generate dense depth map of transportation infrastructure. Transp Res Rec J Trans Res Board. 2011;2215:93–9.CrossRefGoogle Scholar
  23. 23.
    Rashidi A, Rashidi-Nejad H, Maghiar M. Productivity estimation of bulldozers using generalized linear mixed models. KSCE J Civ Eng. 2014;18:1580–89.CrossRefGoogle Scholar
  24. 24.
    Rashidi A, Sigari MH, Maghiar M, Citrin D. An analogy between various machinelearning techniques for detecting construction materials in digital images. KSCE J Civ Eng. 2016;20:1178–88.CrossRefGoogle Scholar
  25. 25.
    Rashidi A, Jazebi F, Brilakis I. Neurofuzzy genetic system for selection of construction project managers. J Constr Eng Manag. 2011;137:17–29.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  • Javad Abolfazli Esfahani
    • 1
    Email author
  • Soheil Safaiyan
    • 1
  • Saman Rashidi
    • 1
  1. 1.Department of Mechanical EngineeringFerdowsi University of MashhadMashhadIran

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