Particle shape effect on heat transfer performance in an oscillating heat pipe
© Ji et al; licensee Springer. 2011
Received: 25 November 2010
Accepted: 5 April 2011
Published: 5 April 2011
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© Ji et al; licensee Springer. 2011
Received: 25 November 2010
Accepted: 5 April 2011
Published: 5 April 2011
The effect of alumina nanoparticles on the heat transfer performance of an oscillating heat pipe (OHP) was investigated experimentally. A binary mixture of ethylene glycol (EG) and deionized water (50/50 by volume) was used as the base fluid for the OHP. Four types of nanoparticles with shapes of platelet, blade, cylinder, and brick were studied, respectively. Experimental results show that the alumina nanoparticles added in the OHP significantly affect the heat transfer performance and it depends on the particle shape and volume fraction. When the OHP was charged with EG and cylinder-like alumina nanoparticles, the OHP can achieve the best heat transfer performance among four types of particles investigated herein. In addition, even though previous research found that these alumina nanofluids were not beneficial in laminar or turbulent flow mode, they can enhance the heat transfer performance of an OHP.
Utilizing the thermal energy added on the oscillating heat pipe (OHP), the OHP can generate the oscillating motion, which can significantly increase the heat transport capability. Compared with the conventional heat pipe, the OHP has a number of unique features: (1) an OHP has a higher thermal efficiency because it can convert some thermal energy from the heat generating area into the kinetic energy of liquid plugs and vapor bubbles to initiate and sustain the oscillating motion; (2) the liquid flow does not interfere with the vapor flow because both phases flow in the same direction resulting in low pressure drops; (3) the structure of liquid plugs and vapor bubbles inside the capillary tube can significantly enhance evaporating and condensing heat transfer; (4) the oscillating motion in the capillary tube significantly enhances the forced convection in addition to the phase-change heat transfer; and (5) as the input power increases, the heat transport capability of an OHP dramatically increases. Because of these features, extensive investigations of OHPs [1–12] have been conducted since the first OHP developed by Akachi in 1990 . These investigations have resulted in a better understanding of fluid flow and heat transfer mechanisms occurring in the OHP.
Most recently, it was found that when nanoparticles [13, 14] were added into the base fluid in an OHP, the heat transport capability can be increased. The thermally excited oscillating motion in the OHP helps suspend some types of particles in the base fluid that would otherwise settle out of solution. Although nanoparticles added on the base fluid cannot greatly increase the thermal conductivity , the oscillating motion of particles in the fluid might have an additional contribution to the heat transfer enhancement beyond enhancing thermal conductivity. Ma et al. [13, 14] charged the nanofluids (HPLC grade water and 1.0 vol.% diamond nanoparticles of 5-50 nm) into an OHP and found that the nanofluids significantly enhance the heat transport capability of the OHP. The investigated OHP charged with diamond nanofluids can reach a thermal resistance of 0.03°C/W at a power input of 336 W. Lin et al.  charged silver nanofluids with a diameter of 20 nm into an OHP and confirmed that the nanofluids can improve the heat transport capability of OHPs. With a filling ratio of 60%, their OHP can achieve a thermal resistance of 0.092°C/W. Qu et al.  conducted an investigation of the effect of spherical 56-nm alumina nanoparticles on the heat transport capability in an OHP, and found that the alumina particles can enhance heat transfer and there exists an optimal mass fraction. Although these investigations have demonstrated that the particles can enhance heat transfer in an OHP, it is not known whether there exists an optimum particle shape for a given type of particles.
In the current investigation, the particle shape effect on the heat transfer performance of an OHP was investigated experimentally. Ethylene glycol (EG) was used as the base fluid. Four types of nanoparticles with shapes of platelet (9 nm), blade (60 nm), cylinder (80 nm), and brick (40 nm) were studied to determine whether the optimum particle shape exists for the maximum heat transport capability of the OHP.
Before the nanofluids were charged into the OHP, the base fluid (mixture of EG and deionized water 50/50 vol%) was charged into the OHP by the back-filling method . All heat pipes were tested at a filling ratio of 50% in this paper. The OHP was tested vertically, i.e., the evaporator on the bottom and the condenser on the top. Prior to the test, the cooling bath (circulator) temperature was set at 20 or 60°C, which is defined as the operating temperature of the OHP. As soon as the cooling bath reached a temperature of 20 ± 0.3 or 60 ± 0.3°C, the power supply was switched on and the input power was added to the evaporator section of the OHP. The power was gradually increased in a step-wise mode with a power increment of 25 or 50 W depending on the total power. When the input power was less than 100 W, the increment was 25 W. When the input power was higher than 100 W, the increment was 50 W. When the input power was increased, the system needed time to reach a new steady state. The experimental data showed that when the power input was low, the time required to reach the steady state was about 30 min, and for a higher input power, it was about 10 min. When the evaporator average temperature changed less than 0.5°C within 1 min, it was defined that the test section reached steady state. The input power and the temperature data were then recorded by a computer. This was continued until the total power exceeded the 250 W limit of the heater used in the current investigation. Throughout the whole operating process, once the evaporator temperature exceeded 160°C, the test was stopped due to the temperature limit of the insulation materials. After the OHP charged with the base fluid was tested, the nanofluid of one shape particle with different volume fractions (0.3, 1, 3, 5 vol.%) were charged into the OHP and tested in the same way described above. It should be noted that a new OHP was manufactured for each nanoparticle shape and it was charged with the nanofluids from low volume fraction to high volume fraction to prevent nanoparticles left as residue inside the heat pipe from contaminating subsequent experiments.
Using the experimental setup and procedures described above, the effects of particle shape, particle volume fraction and operating temperature (20 and 60°C) on the heat transport capability in the OHP were studied. The evaporator temperature, T e, and the condenser temperature, T c, are based on the average temperature of six thermocouples placed on each of the evaporator and condenser sections, i.e., T e = ∑T ei /6 and T c = ∑T ci /6, respectively. The thermal resistance is defined as R = ΔT/Q, where ΔT is the temperature difference between evaporator and condenser and Q is the input power.
From Figure 3, it can be found that at the operating temperature of 20°C, the heat transport capability depends on the particle shape and volume fraction. When the input power is less than 100 W, the OHP charged with P1 (volume fraction < 3%), P2 (volume fraction < 1%), P3 (volume fraction < 3%), and P4 (volume fraction < 1%), respectively, can enhance the heat pipe performance. The heat transfer performance largely depends on the volume fraction. For the OHPs charged with P1, P2, and P4, respectively, the optimum volume fraction is about 0.3% while for the OHP charged with P3, the optimum fraction is about 1%. At a power input less than 100 W and a volume fraction of 0.3%, the OHP charged with P3 (cylinder) obtained the best heat transfer performance while the OHP charged with P4 (brick) showed the lowest among four types of particles. The sequence of heat transfer enhancement from the highest to lowest is: P3 (cylinder) > P2 (blade) > P1 (plate) > P4 (brick). However, when the input power is higher than 125 W, the OHP charged with P4 (brick) obtained the best heat transfer performance. The sequence of heat transfer enhancement from the highest to lowest becomes: P4 (brick) > P3 (cylinder) > P1 (plate) > P2 (blade).
From Figure 4, it can also be found that at the operating temperature of 60°C, the OHP heat transport capability depends on the particle shape and volume fraction. Almost all the nanofluids except P1V5 and P3V3 can enhance the heat transfer performance of the OHP. At a volume fraction of 0.3% and a power input less than 100 W, the sequence of heat transfer enhancement from the highest to lowest was: P3 (cylinder) > P2 (blade) > P1 (plate) > P4 (brick). But, as the input power increases, the sequence becomes: P2 (blade) > P3 (cylinder) > P4 (brick) > P1 (plate). It should be noted that the best volume fraction for all particles tested herein is 0.3%. From the results shown in Figures 3 and 4, it can be found that the operating temperature affects the heat transfer performance of the OHP as well. In previous work with these nanofluids , viscosity of the nanofluids decreases by at least half when the temperature increases from 20 to 60°C. This decreased viscosity significantly decreases the pressure drop, which can improve the oscillating motion in the OHP and therefore enhance the heat transfer performance of the OHP. This is one of those reasons why the operating temperature affects the heat transfer performance of the nanofluid OHP significantly.
By comparing the current results (Figure 5) with the results obtained by Timofeeva et al. , it can be found that (1) while Timofeeva et al.  found that none of the nanofluids were beneficial in laminar or turbulent flow, these nanofluids in the current study enhanced the OHP performance and the performance was dependent on the particle shape and volume fraction; (2) while the cylinder-like particle (P3) is almost the worst particle in laminar and turbulent flow mode , it is the best particle in the current study; and (3) while as the volume fraction increases, the heat transfer performance of all nanofluids in laminar and turbulent flow tested by Timofeeva et al.  decreases, the results in the current study do not support these conclusions. For an OHP, the thermally excited oscillating motion of liquid plugs and vapor bubbles existing in an OHP is very different from the single phase flow investigated by Timofeeva et al. . The oscillated nanoparticles in the OHP will directly affect the thermal and velocity boundary layers, which is very different from the one directional flow of laminar or turbulent flows. This might be the primary reason why the nanoparticles charged into an OHP can improve the heat transfer performance. However, the detailed mechanisms of heat transfer enhancement of these nanoparticles in an OHP are unclear and further research work is needed.
The alumina nanoparticle shape effect on the heat transfer performance of an OHP was investigated experimentally and it is concluded that the alumina nanoparticles added in the OHP can enhance the heat transfer performance of OHP significantly and it depends on particle shape and volume fraction. For the six-turn OHP investigated herein, when the OHP was charged with EG and cylinder-like alumina nanoparticles, the OHP can achieve the best heat transfer performance among four types of particles, i.e., a performance enhancement efficiency, η, of 75.8% with an operating temperature of 60°C and volume fraction of 0.3%. In addition, it is demonstrated that the alumina nanofluids, which are not beneficial in laminar or turbulent flow mode, can enhance the heat transfer performance of the six-turn OHP investigated herein.
oscillating heat pipe.
The authors would like to express our great thanks to Elena V. Timofeeva (Energy Systems Division, Argonne National Laboratory) for her help in the preparation of this investigation. We are also grateful to Sasol North America Inc. for providing the nanoparticle samples used in this work. This research work was supported by the National Natural Science Foundation of China under Grant Nos. 51076019 and 50909010, the Program of Dalian Science and Technology of China under Grant No. 2009E13SF177, and the Fundamental Research Funds for the Central Universities of China under Grant No. 2009QN014.
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