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Analysis on the influences of atomization characteristics on heat transfer characteristics of spray cooling
Sustainable Cities and Society 51 (2019) 101799
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Analysis on the influences of atomization characteristics on heat transfer characteristics of spray cooling
T
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Jun Bao, Yu Wang , Xinjie Xu, Xiaoyi Niu, Jinxiang Liu, Lanlan Qiu College of Urban Construction, Nanjing Tech University, Nanjing 210009, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Spray cooling Spray atomization PIV Flow pattern distribution Heat transfer coefficient Nano-alumina additive
The development of big data leads to the increasing heat dissipation of data center chips. As an efficient pattern to remove high heat flux, spray cooling has huge potential for data center cooling. Spray cooling system was established combined with PIV (Particle Image Velocimetry) system. The PIV was used to measure the flow pattern distribution of different nozzle sprays, while the surface heat flux and heat transfer coefficient were obtained by the thermocouples. The results show that as the spray diameter decreases, the outlet pressure and outlet velocity of the droplet increase, and the spray cone angle increases, causing only a small amount of droplets actually participate in the heat exchange, resulting in a higher velocity and a smaller heat transfer coefficient. It is also inferred that better uniformity of droplets velocity is beneficial for the heat transfer performance. Moreover, to further enhance the heat transfer performance, nano-alumina solution with five different fractions was applied to the experimental system. It is found that the heat transfer coefficient of the surface reaches an optimum value with a maximum velocity obtained by the PIV when the mass fraction of the solution is 0.08%.
1. Introduction With the sharp increase of the data amount in Internet, the demand for data centers’ processing capacity is getting higher. The augment of server racks power consumption and the improvement of chip integration lead to higher requirements for heat dissipation ability in data center. The power density of each rack achieved 7 kW in traditional data centers (Kant, 2009), while the cooling capacities could be better between 10–15 kW per rack in the new generation data centers (Marcinichen, Olivier, & Thome, 2012). Air cooling is the most widely used cooling method to remove heat which caused by servers in data centers. In a conventional data center, about 40% of the total used electricity is consumed by cooling system (Zhang, Shao, Xu, Zou, & Tian, 2014). Therefore, how to improve the energy efficiency of the data room and reduce energy waste is great importance. Eduard Oró et al. Or, Taddeo, and Salom (2019) evaluated the energy and economic viability of a heat-recycling program in an air-cooled data center, which showed the infeasibility of a heat recovery scheme based on a combination of a high-temperature heat pump and a commercial chiller. Kyuman Cho et al. Cho, Chang, Jung, and Yoon (2017) analyzed the economic performance of a cooling strategy developed by a combination of seven data center cooling systems and the results showed that in comparison ⁎
to the conventional cooling system, the air-side economizer and supplementary cooling by a mechanical system saved 26.84% of economic expenditure. Researchers suggested that the maximum heat dissipation capacity of air cooling is about 37 W/ cm2 (Saini & Webb, 2002) and it is hard to meet the heat generation rate of processors which is about 65 W/ cm2 (Marcinichen, Thome, & Michel, 2010). Research shows that liquidcooled data centers can reduce overall data center consumption by 30% (Oró, Allepuz, Martorell, & Salom, 2018). In order to ensure the reliability and stability of chips, new efficient heat removal technologies need to be adopted urgently. As a new promising cooling method for data center, spray cooling has attracted more and more attention by researchers. It realizes the high heat flux removal while maintaining the uniform surface temperature of chips and provides more uniform cooling than liquid jet impingement (Kandlikar & Bapat, 2007). Plenty of studies concerning the factors affecting spray cooling heat transfer characteristics have been proposed including the coolant flow flux, types of working substance, orifice-to-surface distance and so on. Experiments were performed by Chen, Chow, and Navedo (2002) and studied the factors affecting critical heat flux in which the mean droplet velocity has the most significant effect on CHF and the second important factor is the droplet flux. Sozbir, Chang, and Yao (2003) studied the atomization
Corresponding author. E-mail address: [email protected] (Y. Wang).
https://doi.org/10.1016/j.scs.2019.101799 Received 28 March 2019; Received in revised form 22 August 2019; Accepted 22 August 2019 Available online 26 August 2019 2210-6707/ © 2019 Elsevier Ltd. All rights reserved.
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Nomenclature D g H q Re ti T1 T2 T3 T4 Ti
Tj Tin Tw
equivalent diameter (cm) mass flux (kg/(s.m2)) surface heat transfer coefficient, W/m2.K heat flux density at the heat source surface, W/m2 Reynold number thermocouple number i temperature measured by thermocouple t1, °C temperature measured by thermocouple t2, ° temperature measured by thermocouple t3, °C temperature measured by thermocouple t3, °C temperature measured by thermocouple ti, °C
temperature measured by thermocouple tj, °C substance nozzle inlet temperature, °C temperature of the heat source surface, °C
Greek letter Δδ δ1 λ μ
heat transfer coefficient under different inlet flow rates in the membrane boiling zone by air atomizing nozzle and found that the heat transfer coefficient is linear with the inlet flow of water. Chen et al. (2002) and Oliphant, Webb, and McQuay (1998) both concluded that surface heat transfer coefficient increases with the mass flux rise of the medium through investigations. Experiments about different type working substance which includes FC-72, FC-87, and water on a small area of heat source were conducted by Estes & Mudawar (1995) and they found that droplets with a larger diameter and faster velocity could impede its evaporation. Hsieh and Yao (2006) performed a single nozzle spray cooling experiment with 25 °C pure water and 14 °C R134a as the working medium. The results show that the degree of subcooling has little effect on the heat transfer performance of R134a spray cooling, and the cooling effect of R134a is much lower than that of water. (Mudawar and Estes (1996) found that the flow of working fluid reaching the surface of the heat source could be changed indirectly by altering the orifice-to-surface distance and the CHF could reach peak when the atomization area of the droplet and the heat dissipation surface were just inscribed. Cheng, Liu, Zhao, and Fan (2010) pointed out that the nozzle height is optimal when the working fluid utilization rate is the highest, but not when the spray completely covers the heated surface. From the aspect of cooling performance enhancing, enhanced surfaces (Bostanci, Altalidi, & Nasrazadani, 2018; Bostanci et al., 2012; Silk, Kim, & Kiger, 2006), and medium with stronger heat transfer parameters (Hsieh & Yao, 2006; Xu, Si, Shao, & Tian, 2014) are the most commonly used techniques. Experiments (Hou, Tao, & Huai, 2014) were conducted on heat transfer characteristics and mechanisms of spray cooling in which micro-structured surfaces include the cubic fins and the straight pin fins served as heat exchange surfaces. It was found that the heat transfer performance of the straight pin fins is optimal in the single-phase region, and the heat transfer performance of the cubic fins is better in the two-phase region. A dimensionless number (DM) was created to characterize the heat transfer performance of different microstructures in single-phase heat transfer. The heat transfer effect of the surface in spray cooling was studied experimentally by Xie et al. (2013). Experiments show that the arrangement of fins plays a decisive role in the cooling performance of the macro-structured surface. With same surface geometries, the surface heat transfer enhancement effect of the multi-scale structure with microstructure is superior to macro-structured surface. Experiments on two heaters with different surface roughness were performed by Eduardo (MartínezGalván, Antón, Ramos, & Khodabandeh, 2013). It was found that for rough surfaces, the value of CHF increases with volume flow rate and for smooth surfaces, the value of CHF is independent of volume flow. The mixture of ethanol and water were used for spray cooling experiments by Ravikumar, Jha, Sarkar, Pal, and Chakraborty (2014). The cooling enhancement effect is optimal with the ethanol fraction of 500 ppm. In the ethanol-water-tween 20 mixture spray experiment proposed by Bhatt et al. (2017), the achieved CHF (2.1 MW/m2) is 1.6
distance between two adjacent thermocouples, mm distance from simulated heat source surface to the thermocouple T1, mm thermal conductivity of the heat source material copper, W/m.K dynamic viscosity (mPa∙S)
times that of pure water. The maximum heat transfer coefficient is obtained when the fraction of ethanol is 500 ppm. The heat transfer enhancement by the addition of high-alcohol surfactant and dissolving salt additive were studied by Cheng, Xie, Han, and Chen (2013). The optimum fractions of NaCl, Na2SO4, 1-Octanol, and 2-ethyl hexanol additives were demonstrated to be 1.72%, 2.76%, 0.02%, and 0.015%, respectively. The pool boiling characteristics of alumina, zirconia, and silica as nanoparticles of nanofluid were experimentally studied by Kim, Bang, Buongiorno, and Hu (2007). A significant increase in critical heat flux (CHF) was achieved at moderate nanoparticle fractions (< 0. 1 % by volume). Utomo, Poth, Robbins, and Pacek (2012), Nguyen, Roy, Gauthier, and Galanis (2007) and Vafaei & Borca-Tasciuc, 2014) also obtained research results about spray cooling with nano-additives. However, little research was proposed on the heat transfer characteristics of spray cooling through visualization, especially from the view of nozzle atomization. In this investigation, a spray cooling system has been established in combination with PIV system aiming to achieve visualization for investigating the relationship between atomization effects of nozzles with different pore sizes and the heat transfer performance. Besides, the heat transfer characteristics and the nozzle atomization of the nanofluid prepared by adding nano-alumina particles were also studied by combining the PIV system. The results of this study will not only provide a reference for nozzle selection, nanofluid fraction configuration, but also for flow and heat transfer characteristics optimization in spray cooling system design. 2. Equipment and methods 2.1. Bench construction The spray cooling system experimental bench established in this study mainly consists of a spray liquid supply system, a simulated heat source heating system, a data acquisition system, and a PIV (Particle Image Velocimetry) system. The nozzles selected in the experiment are 304 stainless steel solid cone nozzles, and the nozzle pore size is 0.8 mm, 1.2 mm, 1.5 mm, 2.0 mm. The experimental medium is water and nanofluid at constant room temperature. The surface area of the simulated heat source is a circular shape with a diameter of 24 mm and the maximum heat that the simulated heat source can achieve is about 1800 W. The distance from the nozzle to the surface of the simulated heat source is 100 mm. Other parameters are listed in Table 1. The photo of the spray cooling system and the spray system schematic are Table 1 Spray cooling experimental conditions.
2
Orifice-to-surface distance
10 mm
Nozzle inlet temperature Working fluid flow Ambient temperature
6-12 ℃ 20-40 L/h 3-15 ℃
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following formula.
shown in Fig. 1. The micro-high pressure pump is used to supply the liquid to the spray system, and the flow rate is adjusted by the flow regulating valve. The flow rate can be accessed by the flow meter LZ500 of Suzhou xianchi Co. which has a range of 0–200 L/h and maximum uncertainty of ± 5 L/h. The cooling medium could be atomized by the pressure nozzle into droplets and sprayed onto the surface of the heating block. A copper block was applied to simulate the heating part of the server, and the electric heating rod is installed at the lower end of the copper block. A power regulator is used to regulate the heating power which is transferred upward through the copper block to the surface to simulate different heat flux densities. Two different series of nozzles were selected for the experiments, the structures of which are shown in Fig. 2. As shown in Fig.2, the structure of No.2 nozzle is less complex than that of No.1 nozzle, resulting in a lower flow resistance. Comparison experiments were carried out at a flow rate of 40 L/h using a No. 1 series nozzle and a No. 2 series nozzle with a pore size of 2.0 mm. All rest experiments were carried out by using No. 1 series nozzles with different pore size.
Tw = T1 −
(Ti − Tj) δ1 Δδ
Where Tw is the temperature of the heat source surface, δ1 is the distance from the simulated heat source surface to the thermocouple T1. From the fitting of the temperature variation gradient, the relationship between T1 and the surface temperature can be obtained. The surface heat transfer coefficient can be calculated as below.
H=
q (Tw − Tin )
2.4. Experimental procedure The experiments conducted in this paper were divided into two parts, as shown in Fig. 4. The first part of the experiment is the heat transfer performance experiment. Pure water and different fractions of nano-alumina solution were used as the spray medium. The spray cooling effect under different working conditions could be obtained by altering the nozzle type, heating power and flow rate of the working
As an effective method to measure flow fields, many researchers have made many contributions to the application of this technology for research (Molezzi & Dutton, 1993; Schrijer, Scarano, van Oudheusden, & Bannink, 2005). A 2D PIV system SM3-5M200 of Beijing lifangtiandi Co. was applied in this research. PIV system consists of an illumination laser, a sync controller, an image acquisition board which was built in a computer in advance, a high-speed digital camera, and a computer which was used for recording and calculation. The model types of the specific equipment used in this research are shown in Table 2. The principle of the PIV system is to calculate the measured fluid velocity vector from the displacement of a small region in the flow field at a known time interval. Appropriate tracer particles have been sprinkled in the fluid in the area to be tested, and a laser pulse generated by a two-pulse laser with a time interval of Δ t forms a laser sheet to illuminate the flow field region to be studied. The flow field could be deduced by using a digital camera to obtain a flow field image of the two frames to be tested. Then the two photos of the flow field information would be transmitted to the data processor in which the velocity of each point or region by using cross-correlation analysis algorithm could be calculated to form the original vector. The schematic diagram of the experimental system is shown in Fig. 3. 2.3. Heat flux measurement and data acquisition instrument In order to calculate the surface heat transfer coefficient of the spray cooling simulated heat source, four K-type thermocouples were arranged in the vertical direction from the surface of the simulated heat source to the bottom, and the distance to the hot surface was t1 T1 :17 mm、t2 T2 : 25 mm、t3 T3 :33 mm、t4 T4 :41 mm respectively. The temperature is obtained by an Agilent 34972A data acquisition instrument. The maximum uncertainty of a K-type thermocouple is ± 0.8 ℃. According to one-dimensional Fourier heat conduction law, the radial temperature distribution and heat flux of the simulated heat source surface can be derived.
Ti − Tj Δδ
q= λ
Ti − Tj Δδ
(3)
Where H is the surface heat transfer coefficient, Tin is the spray substance nozzle inlet temperature. The nozzle inlet temperature is obtained by PT100 platinum resistor, the maximum uncertainty is ± 0.15 ℃.
2.2. PIV system introduction
q=λ
(2)
(1)
Where q is heat flux density at the heat source surface, λ is the thermal conductivity of the heat source material copper, Ti 、 Tj is the temperature measured by thermocouple ti Ti 、tj(1 < i < j < 4) Tj, Δδ is the distance between two adjacent thermocouples. According to our previous work, the uncertainty of heat flux is ± 4.9 % (Wang, Zhou, Yang, & Jiang, 2016). The temperature of the heat source surface can be calculated by the
Fig. 1. Spray cooling system. (a) No. 1 series nozzle (b) No. 2 series nozzle 3
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Fig. 2. Two different series of nozzle structures.
laser film thickness to about 1 mm and ensure that the light can illuminate the study area; (2) Place the camera in proper position and adjust the camera to a proper height; (3) Fix the charge coupled device (CCD) camera on the camera frame; connect the power cable of the CCD and the data cable which connect the CCD and the image board; (4) Take a photo of the ruler at the piece of light and calibrate the image of the ruler to determine the magnification of the system image; (5) Run the spray system, take the photo of the flow field, and ensure the particle distribution is uniform and the number is large; (6) Adjust system parameters until a satisfactory particle image is acquired; (7) Save the image sequence to perform subsequent processing including analyzing the velocity distribution of the flow field；(8) Import the velocity data collected by the PIV system into Tecplot and convert it into the velocity contour.
Table 2 PIV system equipment model. Device name
Model type
Illumination laser Sync controller Digital camera
Vlite-200 SM-Micropulse725 CLB-B2520M-SC000
2.5. Data selection In the experiment, measured data was used for analysis when steady state was achieved. For instance, the temperature variation rates of the four thermocouples for a nozzle with the pore size of 0.8 mm, flow rate of 20 L/h and input power of 50 W/cm2 are shown in Fig. 5. The heat transfer is considered to be in steady state when the temperature variation rate of each thermocouple is less than 1 °C in 5 min. 3. Results and discussions 3.1. Effect of the flow rate change on atomization state and heat transfer performance
Fig. 3. Operating principle diagram of the PIV system. (a) PIV system experimental procedure (b) Spray cooling experimental procedure
The heat transfer coefficient of the simulated heat source at the flow rate of 20 L/h and 30 L/h for the nozzle with the pore size of 0.8 mm was compared. It can be seen from Fig. 6 that the heat transfer coefficient increases with the increase of input heating power. However, the heat transfer coefficient tends to decrease when the heating power of 200 W/ cm2 is achieved with the flow rate of 20 L/h. This is because, with the development of heat flux, the droplets become vapor at the time they fall on the heating surface. The substance droplets are blocked by the vapor, which impairs the heat transfer. With the increase of droplet velocity, the droplets have the ability to overcome the vapor. Therefore with the flow rate of 30 L/h the heat transfer is still enhanced when the heat flux of 200 W/ cm2 is achieved. The velocity distributions of spray from a nozzle with a pore size of 0.8 mm at flow rates of 20 L/h and 30 L/h were obtained by the PIV system, as shown in Fig. 7. It can be seen from the two figures that the spray droplet are symmetrically distributed. The maximum velocity of the droplets appears at the axis of the cone and the velocity gradually decreases with the extend of the axis. Since the flow rate in Fig. 7(b) is 30 L/h which is larger than the flow rate in Fig. 7(a), the spray range in Fig. 7(b) is larger than that of Fig. 7(a). It can be seen from Fig. 7 that the spray coverage range is -30 mm to 30 mm when the flow rate is 20 L/h, and the value is -40 mm to 40 mm when the flow rate is 30 L/h,
fluid. The second part of the experiment is the application of PIV system to take visual graphics of the spray flow field. The procedures of the heat transfer experiment are as follows: (1) Adjust the height of the adjustable nozzle to the heating surface to a preset position by rotating the thread above the spray chamber; (2) Turn on the power switch of the solution pump and adjust the flow meter to make water the flow rate reaches a setting value; (3) Adjust the voltage of the regulated power supply for heating the heating rods to a setting value; (4) Turn on the computer and data acquisition instrument to record the temperature of the thermocouples in the simulated heat source; (5) When the temperature variation rate of each thermocouple is less than 1 °C within 5 min, the heat transfer is considered to reach a steady state; (6) Adjust the voltage value and proceed to the next set of experiments; (7) When the experiment of one nozzle is completed, turn off the power of the heating rod. After the simulated heating surface is cooled to environment temperature, replace the nozzles and repeat the above steps (3)–(6); (8) Different fractions of nano-alumina solution were prepared as working fluids, then repeat steps (3)–(6). The experimental procedures with the PIV system are listed as follows: (1) Adjust the laser light to the measurement position, set the 4
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Fig. 4. Experimental flow chart.
Fig. 5. Transient temperature variations under one case. Fig. 6. Comparison of heat transfer coefficients for a nozzle with a pore size of 0.8 and flow rates of 20 L/h and 30 L/h.
respectively. By comparing the surface heat transfer coefficients at the two flow rates in Fig. 6, it is found that the heat transfer coefficient at the flow rate of 30 L/h is smaller than the heat transfer coefficient at the flow rate of 20 L/h which is contrary to previous PIV experimental studies. As shown in Fig. 8, by observing the droplet distribution in the spray chamber, and the comparison of the velocity distributions at the two flow rates in Fig. 7, it is found that when the flow rate is 20 L/h, the nozzle cone spray with the pore size of 0.8 mm cannot reach the setting operation angel. Therefore the droplets can concentrate on the surface of the heating block and dissipate heat sufficiently. When the flow rate is 30 L/h, the cone spray angle reaches the maximum value, and the droplets ejected from the nozzle are scattered over the heat dissipating surface, which means some droplets do not participate in the heat exchange with the heating surface. The heat transfer coefficient is influenced by the dimensionless parameter Re. The Reynolds number Re is the ratio of inertial force to viscous forces with in a fluid, which indicates the flow state of the liquid droplets and the liquid film (Wang,
Jiang, Chen, & Zhou, 2017).
Re =
gD μ
(4)
With the flow rate of 30 L/h, as seen from Fig.7, the droplet number participated in the heat transfer is smaller than that with the flow rate of 20 L/h. Therefore, in this case less cooling medium is flowing through the heating surface, causing a lower Reynolds number, which means an insignificant surface heat transfer capability. 3.2. Effect of nozzle pore size variation on atomization state and heat transfer performance The velocity distribution of the same series of nozzles with the pore size of 1.2 mm, 1.5 mm, 2.0 mm at a flow rate of 40 L/h and a spray 5
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Fig. 7. Flow field distribution with a nozzle pore of 0.8 mm and different flow rate.
of 40 L/h can be obtained. The heat transfer coefficient of the heating block surface increases with the augment of the heating power. When the flow rate is constant, the heat exchange effect of the nozzle with larger diameter is better. Especially the droplets ejected from the nozzle with a diameter of 1.2 mm are smaller than the droplets ejected from the nozzles of 1.5 mm and 2.0 mm, and are more easily vaporized at an input power of 200 W/cm2 to form vapor layer on the heating surface. A formed vapor layer prevents subsequent droplets from contacting and transferring heat with the heating surface. By comparing the velocity maps of the three nozzles combined with the droplet distribution state which are shown in Fig. 11, it is found that although the droplets ejected by the small-caliber nozzle are large in initial velocity, the droplet distribution is not as uniform as that with large-diameter ones, and the edge velocity is weakened causing the surface not completely covered. The droplet velocity of the large holes is small, but the velocity distribution is more uniform and can evenly cover the entire surface. Therefore, compared with the velocity values, the velocity uniformity has a major effect on heat transfer.
height of 10 cm are shown in Fig. 9 respectively. It can be observed from Fig. 9 (a) that droplet velocity with the pore size of 1.2 mm at the spray axis can reach 7 m/s, and most of the droplets with high velocity are concentrated at the axis of the cone. It can be seen from Fig. 9 (b) that speed of droplets ejected by the nozzle with the pore size of 1.5 mm can reach 4.2 m/s, and part of the droplets which has a faster velocity deviates from the axis of the cone, resulting the droplet to not uniformly cover the surface of the heating block. What can be found in Fig. 9 (c) is that the fastest droplets ejected from the nozzle with the pore size of 2.0 mm could reach 2.8 m/s, and the faster droplets could well cover the surface of the heating block. Comparing the three velocity distribution images above, it can be found that as the diameter of the nozzle increases, the droplet velocity of the nozzle ejection decreases. The reason is that when the flow rate is constant, the pressure difference between the inlet and outlet of the nozzle decreases as the diameter of the nozzle increases. As the pressure difference decreases, the droplet velocity also decreases, and the degree of fluid fragmentation becomes smaller so that the initial droplet velocity is relatively lower. From Fig. 10 the relationship between heat transfer coefficients of droplets ejected from three nozzles with different calibers at a flow rate
Fig. 8. Droplet distribution in the spray chamber at different flow rate. 6
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Fig. 9. Flow field distribution with different pore sizes at a flow rate of 40 L/h.
in the experiment. The velocity distributions of two different series of nozzles with a pore size of 2.0 mm (as shown in Fig.2) are shown in Fig. 12, and a comparison of heat transfer coefficients is shown in Fig. 13. Comparing the speed profiles in Fig. 12, combined with the line graph of the heat transfer coefficient generated by the droplets ejected from the two nozzles, it is found that the velocity uniformity of the droplets ejected by the No. 2 nozzle on the heating surface is not as good as the uniformity of the droplets ejected from the No. 1, resulting in uneven heat distribution of the simulated heat source and affecting the heat transfer effect. The No. 2 nozzle has a droplet velocity up to 7.5 m/s. When the droplets hit the surface of the heat source, the droplets residence time is too short to exchange heat with the heating surface and the former droplets are replaced by the subsequent droplets. The droplet velocity distribution on the heat source surface of the No. 1 nozzle is uniform and the speed is not too large, and the droplets can exchange heat with the surface fully. These results also indicate that compared with high droplet velocity, the uniform velocity distribution plays a more significant role in enhancing the spray cooling heat transfer ability. When the heat flux is small, the evaporation of droplets is less than the supplement of droplets. Due to the uneven distribution of droplet velocity ejected from nozzle No. 2, the droplet at the edge is pushed away by the fluid at the center without exchanging heat. Therefore, the a liquid film is formed on the surface of a relatively high temperature, which hinders heat exchange, thereby increasing the thermal
Fig. 10. Comparison of heat transfer coefficients for nozzles with a pore size of 1.2 mm, 1.5 mm, 2.0 mm and flow rate of 40 L/h.
3.3. Comparison of velocity distribution and heat transfer characteristics of two different series of nozzles with a diameter of 2.0 mm In order to investigate the influence of droplet velocity uniformity, two different series of nozzles with the same diameter were conducted 7
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Fig. 11. Droplet distribution in the spray chamber of nozzles with different pore sizes at a flow rate of 40 L/h.
resistance. With the increase of the heat flux, the evaporation of the droplets leads to the thinning of the liquid film, the hindrance is weakened and the thermal resistance is reduced, and the heat transfer coefficient is increased. Therefore, the heat transfer coefficient trend of No. 2 nozzle is different from No. 1 nozzle.
alumina is 0.08%, the highest velocity of 8 m/s is achieved. As the nano-alumina fraction continues to increase, the droplet velocity decreases. When the mass fraction of the nano-alumina reaches 0.2%, the maximum flow rate of the spray droplets is reduced to 7 m/s. The variations of the heat transfer coefficient with the input heat flux of pure water and five different mass fractions of nanofluid are shown in Fig. 15. It can be seen from the figure that the heat transfer coefficient increases as the fraction of the nano-alumina increases before the mass fraction of 0.08%. When pure water is used as the coolant, the critical state is achieved at the input power of 150 W/cm2, and then a downward trend occurs because the cooling capacity of pure water deteriorates with the increase of the input power. As seen from Fig.14, the droplet velocity also increases as the fraction of the nano-alumina increases before the mass fraction of 0.08%. When the fraction reaches 0.08%, the droplet velocity and the surface heat transfer coefficient simultaneously reach a maximum value. This means the nanoparticles can flow with the liquid film with
3.4. Effect of different fractions of Nano-Alumina additive on heat transfer characteristics and heat transfer performance of flow field The PIV system was used to capture the flow field of pure water and different mass fractions of nano-alumina solution (0.02%, 0.04%, 0.08%, 0.12%, 0.20%, selected on the reference to Bellerová, Tseng, Pohanka, and Raudensky (2012) and Ravikumar et al. 2015) with a diameter of 0.8 mm at a flow rate of 20 L/h, as shown in Fig. 14. It can be seen from the figure that as the fraction of nano-alumina increases, the velocity of the spray droplets increases from the mass fraction of 0.02% to the mass fraction of 0.08%. When the fraction of the nano8
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Fig. 12. Flow field distribution of different series nozzles with a pore of 2.0 mm at a flow rate of 40 L/h.
nozzle structures and the nano fluid fractions to improve the heat transfer capacity. Due to the limitation of the experimental bench, the adjustable range of flow rate is limited. In our subsequent research, the adjustable range of flow rate for the experimental bench will be further expanded. Sufficient experimental results will be used to obtain better conclusions. Conclusions are as follows:
• The angle of the spray cone opening has a non-negligible effect on • Fig. 13. Comparison of heat transfer coefficients for two different series of nozzles with pore size of 2.0 mm.
•
high droplet velocity, which will enhance the convection heat transfer between the liquid film and the heating surface. And then from a fraction of 0.08% to 0.12%, the droplet velocity decreases, as well as the surface heat transfer coefficient. When the fraction increases to 0.2%, the droplet velocity decreases, resulting in a decrease in the flow disturbance on the heated surface liquid film. The impaired flow disturbance on the surface will directly cause the nanoparticles stacking on the surface instead of flowing away by the liquid film, which will enhance the thermal resistance on the heating surface. As a result, the heat transfer performance of the spray cooling deteriorates with its value smaller than that of pure water. For this experiment, the optimum mass fraction of nano-alumina is 0.08%.
•
the heat transfer effect of the spray cooling. In some cases, it is ensuring that the droplets not spraying beyond the surface more preferred than enhancing the droplet velocity to improve the heat transfer effect. As the diameter of the nozzle increases, the output velocity of the droplet and the angle of the spray vertebral both decrease, the heat transfer effect can be improved. The better the uniformity of the droplets velocity distribution covering the surface of the simulated heat source, the better the heat transfer of the surface. Adding a certain fraction of nano-additives to water will help to enhance both the velocity and the heat transfer effect of spray cooling. When the fraction exceeds the optimum value, the heat transfer will be impaired due to the enhancing of thermal resistance.
If spray cooling is applied to chip cooling in data center, the high inlet pressure is not preferred for generating due to the high probability of working fluid leakage. Therefore the spray flow rate is limited. In order to enhance the heat transfer ability, the nozzle structure and other parameters can be improved to achieve effective droplet size and uniform distribution at relatively moderate pressure for optimal heat transfer. Studies in this paper is still limited. In further research, more operating conditions concerning the nozzles and the cooling medium should be considered. Moreover, in practical application, the system volume should be optimized to satisfy the room inside the rack of the data center.
4. Conclusions In this paper, by establishing the spray cooling test bench and PIV system, the velocity distribution of the droplets from different types of nozzles were photographed, and the heat transfer performance corresponding to the velocity distributions were obtained. On the basis, the relationship between the velocity distribution of the droplets and the spray cooling heat transfer coefficient was studied. The innovation of this paper is the observation of the spray atomization flow distribution by the PIV visualiation system and its combination with the heat transfer analysis, which provides a reference for optimizing the atomization parameters including the flow rates, the
Acknowledgments This work is supported by the National Natural Science Foundation of China (Grant No. 51806096), Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. SJCX 0336), Natural Science Foundation of the Jiangsu Higher Education institutions of China (Grant No. 18KJB560007) and the Research Fund of Key 9
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Fig. 14. Flow field distribution of nano-alumina additives with different mass fractions.
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Hsieh, C., & Yao, S. (2006). Evaporative heat transfer characteristics of a water spray on micro-structured silicon surfaces. International Journal of Heat and Mass Transfer, 49, 962–974. Mudawar, I., & Estes, K. (1996). Optimizing and predicting CHF in spray cooling of a square surface. Journal of Heat Transfer, 118, 672–679. Cheng, W.-L., Liu, Q.-N., Zhao, R., & Fan, H.-l. (2010). Experimental investigation of parameters effect on heat transfer of spray cooling. Heat and Mass Transfer, 46, 911–921. Silk, E. A., Kim, J., & Kiger, K. (2006). Spray cooling of enhanced surfaces: Impact of structured surface geometry and spray axis inclination. International Journal of Heat and Mass Transfer, 49, 4910–4920. Bostanci, H., Rini, D. P., Kizito, J. P., Singh, V., Seal, S., & Chow, L. C. (2012). High heat flux spray cooling with ammonia: Investigation of enhanced surfaces for CHF. International Journal of Heat and Mass Transfer, 55, 3849–3856. Bostanci, H., Altalidi, S., & Nasrazadani, S. (2018). Two-phase spray cooling with HFC134a and HFO-1234yf on practical enhanced surfaces. Applied Thermal Engineering, 131, 150–158. Xu, H., Si, C., Shao, S., & Tian, C. (2014). Experimental investigation on heat transfer of spray cooling with isobutane (R600a). International Journal of Thermal Sciences, 86, 21–27. Hou, Y., Tao, Y., & Huai, X. (2014). The effects of micro-structured surfaces on multinozzle spray cooling. Applied Thermal Engineering, 62, 613–621. Xie, J., Tan, Y., Duan, F., Ranjith, K., Wong, T., Toh, K., et al. (2013). Study of heat transfer enhancement for structured surfaces in spray cooling. Applied Thermal Engineering, 59, 464–472. Martínez-Galván, E., Antón, R., Ramos, J. C., & Khodabandeh, R. (2013). Influence of surface roughness on a spray cooling system with R134a. Part I: Heat transfer measurements. Experimental Thermal and Fluid Science, 46, 183–190. Ravikumar, S. V., Jha, J. M., Sarkar, I., Pal, S. K., & Chakraborty, S. (2014). Enhancement of heat transfer rate in air-atomized spray cooling of a hot steel plate by using an aqueous solution of non-ionic surfactant and ethanol. Applied Thermal Engineering, 64, 64–75. Bhatt, N., Raj, R., Varshney, P., Pati, A., Chouhan, D., Kumar, A., et al. (2017). Enhancement of heat transfer rate of high mass flux spray cooling by ethanol-water and ethanol-tween20-water solution at very high initial surface temperature. International Journal of Heat and Mass Transfer, 110, 330–347. Cheng, W., Xie, B., Han, F., & Chen, H. (2013). An experimental investigation of heat transfer enhancement by addition of high-alcohol surfactant (HAS) and dissolving salt additive (DSA) in spray cooling. Experimental Thermal and Fluid Science, 45, 198–202. Kim, S. J., Bang, I. C., Buongiorno, J., & Hu, L. (2007). Surface wettability change during pool boiling of nanofluids and its effect on critical heat flux. International Journal of Heat and Mass Transfer, 50, 4105–4116. Utomo, A. T., Poth, H., Robbins, P. T., & Pacek, A. W. (2012). Experimental and theoretical studies of thermal conductivity, viscosity and heat transfer coefficient of titania and alumina nanofluids. International Journal of Heat and Mass Transfer, 55, 7772–7781. Nguyen, C. T., Roy, G., Gauthier, C., & Galanis, N. (2007). Heat transfer enhancement using Al2O3–water nanofluid for an electronic liquid cooling system. Applied Thermal Engineering, 27, 1501–1506. Vafaei, S., & Borca-Tasciuc, T. (2014). Role of nanoparticles on nanofluid boiling phenomenon: Nanoparticle deposition. Chemical Engineering Research and Design, 92, 842–856. Schrijer, F., Scarano, F., van Oudheusden, B., & Bannink, W. (2005). Application of PIV in a hypersonic double-ramp flow. AIAA/CIRA 13th International Space Planes and Hypersonics Systems and Technologies Conference, 3331. Molezzi, M., & Dutton, J. (1993). Application of particle image velocimetry in high-speed separated flows. AIAA Journal, 31, 438–446. Wang, Y., Zhou, N., Yang, Z., & Jiang, Y. (2016). Experimental investigation of aircraft spray cooling system with different heating surfaces and different additives. Applied Thermal Engineering, 103, 510–521. Wang, Y., Jiang, Y., Chen, W., & Zhou, B. (2017). Heat transfer characteristics of spray cooling beyond critical heat flux under severe heat dissipation condition. Applied Thermal Engineering, 123, 1356–1364. Bellerová, H., Tseng, A. A., Pohanka, M., & Raudensky, M. (2012). Spray cooling by solid jet nozzles using alumina/water nanofluids. International Journal of Thermal Sciences, 62, 127–137. Ravikumar, S. V., Haldar, K., Jha, J. M., Chakraborty, S., Sarkar, I., Pal, S. K., et al. (2015). Heat transfer enhancement using air-atomized spray cooling with water–Al2O3 nanofluid. International Journal of Thermal Sciences, 96, 85–93.
Fig. 15. Comparison of heat transfer coefficients for different fractions of nanoalumina additives.
Laboratory of Aircraft Environment Control and Life Support, MIIT, Nanjing University of Aeronautics and Astronautics(Grant No. KLAECLS-E-201902). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.scs.2019.101799. References Kant, K. (2009). Data center evolution: A tutorial on state of the art, issues, and challenges. Computer Networks, 53, 2939–2965. Marcinichen, J. B., Olivier, J. A., & Thome, J. R. (2012). On-chip two-phase cooling of datacenters: Cooling system and energy recovery evaluation. Applied Thermal Engineering, 41, 36–51. Zhang, H., Shao, S., Xu, H., Zou, H., & Tian, C. (2014). Free cooling of data centers: A review. Renewable and Sustainable Energy Reviews, 35, 171–182. Oró, E., Taddeo, P., & Salom, J. (2019). Waste heat recovery from urban air cooled data centres to increase energy efficiency of district heating networks. Sustainable Cities and Society, 45, 522–542. Cho, K., Chang, H., Jung, Y., & Yoon, Y. (2017). Economic analysis of data center cooling strategies. Sustainable Cities and Society, 31, 234–243. Saini, M., & Webb, R. L. (2002). Heat rejection limits of air cooled plane fin heat sinks for computer cooling, ITherm. Eighth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (pp. 1–8). Marcinichen, J. B., Thome, J. R., & Michel, B. (2010). Cooling of microprocessors with micro-evaporation: A novel two-phase cooling cycle. International Journal of Refrigeration, 33, 1264–1276. Oró, E., Allepuz, R., Martorell, I., & Salom, J. (2018). Design and economic analysis of liquid cooled data centres for waste heat recovery: A case study for an indoor swimming pool. Sustainable Cities and Society, 36, 185–203. Kandlikar, S. G., & Bapat, A. V. (2007). Evaluation of jet impingement, spray and microchannel chip cooling options for high heat flux removal. Heat Transfer Engineering, 28, 911–923. Chen, R.-H., Chow, L. C., & Navedo, J. E. (2002). Effects of spray characteristics on critical heat flux in subcooled water spray cooling. International Journal of Heat and Mass Transfer, 45, 4033–4043. Sozbir, N., Chang, Y., & Yao, S. (2003). Heat transfer of impacting water mist on high temperature metal surfaces. Journal of Heat Transfer, 125, 70–74. Oliphant, K., Webb, B., & McQuay, M. (1998). An experimental comparison of liquid jet array and spray impingement cooling in the non-boiling regime. Experimental Thermal and Fluid Science, 18, 1–10. Estes, K. A., & Mudawar, I. (1995). Correlation of Sauter mean diameter and critical heat flux for spray cooling of small surfaces. International Journal of Heat and Mass Transfer, 38, 2985–2996.
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Analysis on the influences of atomization characteristics on heat transfer characteristics of spray cooling
T
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Jun Bao, Yu Wang , Xinjie Xu, Xiaoyi Niu, Jinxiang Liu, Lanlan Qiu College of Urban Construction, Nanjing Tech University, Nanjing 210009, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Spray cooling Spray atomization PIV Flow pattern distribution Heat transfer coefficient Nano-alumina additive
The development of big data leads to the increasing heat dissipation of data center chips. As an efficient pattern to remove high heat flux, spray cooling has huge potential for data center cooling. Spray cooling system was established combined with PIV (Particle Image Velocimetry) system. The PIV was used to measure the flow pattern distribution of different nozzle sprays, while the surface heat flux and heat transfer coefficient were obtained by the thermocouples. The results show that as the spray diameter decreases, the outlet pressure and outlet velocity of the droplet increase, and the spray cone angle increases, causing only a small amount of droplets actually participate in the heat exchange, resulting in a higher velocity and a smaller heat transfer coefficient. It is also inferred that better uniformity of droplets velocity is beneficial for the heat transfer performance. Moreover, to further enhance the heat transfer performance, nano-alumina solution with five different fractions was applied to the experimental system. It is found that the heat transfer coefficient of the surface reaches an optimum value with a maximum velocity obtained by the PIV when the mass fraction of the solution is 0.08%.
1. Introduction With the sharp increase of the data amount in Internet, the demand for data centers’ processing capacity is getting higher. The augment of server racks power consumption and the improvement of chip integration lead to higher requirements for heat dissipation ability in data center. The power density of each rack achieved 7 kW in traditional data centers (Kant, 2009), while the cooling capacities could be better between 10–15 kW per rack in the new generation data centers (Marcinichen, Olivier, & Thome, 2012). Air cooling is the most widely used cooling method to remove heat which caused by servers in data centers. In a conventional data center, about 40% of the total used electricity is consumed by cooling system (Zhang, Shao, Xu, Zou, & Tian, 2014). Therefore, how to improve the energy efficiency of the data room and reduce energy waste is great importance. Eduard Oró et al. Or, Taddeo, and Salom (2019) evaluated the energy and economic viability of a heat-recycling program in an air-cooled data center, which showed the infeasibility of a heat recovery scheme based on a combination of a high-temperature heat pump and a commercial chiller. Kyuman Cho et al. Cho, Chang, Jung, and Yoon (2017) analyzed the economic performance of a cooling strategy developed by a combination of seven data center cooling systems and the results showed that in comparison ⁎
to the conventional cooling system, the air-side economizer and supplementary cooling by a mechanical system saved 26.84% of economic expenditure. Researchers suggested that the maximum heat dissipation capacity of air cooling is about 37 W/ cm2 (Saini & Webb, 2002) and it is hard to meet the heat generation rate of processors which is about 65 W/ cm2 (Marcinichen, Thome, & Michel, 2010). Research shows that liquidcooled data centers can reduce overall data center consumption by 30% (Oró, Allepuz, Martorell, & Salom, 2018). In order to ensure the reliability and stability of chips, new efficient heat removal technologies need to be adopted urgently. As a new promising cooling method for data center, spray cooling has attracted more and more attention by researchers. It realizes the high heat flux removal while maintaining the uniform surface temperature of chips and provides more uniform cooling than liquid jet impingement (Kandlikar & Bapat, 2007). Plenty of studies concerning the factors affecting spray cooling heat transfer characteristics have been proposed including the coolant flow flux, types of working substance, orifice-to-surface distance and so on. Experiments were performed by Chen, Chow, and Navedo (2002) and studied the factors affecting critical heat flux in which the mean droplet velocity has the most significant effect on CHF and the second important factor is the droplet flux. Sozbir, Chang, and Yao (2003) studied the atomization
Corresponding author. E-mail address: [email protected] (Y. Wang).
https://doi.org/10.1016/j.scs.2019.101799 Received 28 March 2019; Received in revised form 22 August 2019; Accepted 22 August 2019 Available online 26 August 2019 2210-6707/ © 2019 Elsevier Ltd. All rights reserved.
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Nomenclature D g H q Re ti T1 T2 T3 T4 Ti
Tj Tin Tw
equivalent diameter (cm) mass flux (kg/(s.m2)) surface heat transfer coefficient, W/m2.K heat flux density at the heat source surface, W/m2 Reynold number thermocouple number i temperature measured by thermocouple t1, °C temperature measured by thermocouple t2, ° temperature measured by thermocouple t3, °C temperature measured by thermocouple t3, °C temperature measured by thermocouple ti, °C
temperature measured by thermocouple tj, °C substance nozzle inlet temperature, °C temperature of the heat source surface, °C
Greek letter Δδ δ1 λ μ
heat transfer coefficient under different inlet flow rates in the membrane boiling zone by air atomizing nozzle and found that the heat transfer coefficient is linear with the inlet flow of water. Chen et al. (2002) and Oliphant, Webb, and McQuay (1998) both concluded that surface heat transfer coefficient increases with the mass flux rise of the medium through investigations. Experiments about different type working substance which includes FC-72, FC-87, and water on a small area of heat source were conducted by Estes & Mudawar (1995) and they found that droplets with a larger diameter and faster velocity could impede its evaporation. Hsieh and Yao (2006) performed a single nozzle spray cooling experiment with 25 °C pure water and 14 °C R134a as the working medium. The results show that the degree of subcooling has little effect on the heat transfer performance of R134a spray cooling, and the cooling effect of R134a is much lower than that of water. (Mudawar and Estes (1996) found that the flow of working fluid reaching the surface of the heat source could be changed indirectly by altering the orifice-to-surface distance and the CHF could reach peak when the atomization area of the droplet and the heat dissipation surface were just inscribed. Cheng, Liu, Zhao, and Fan (2010) pointed out that the nozzle height is optimal when the working fluid utilization rate is the highest, but not when the spray completely covers the heated surface. From the aspect of cooling performance enhancing, enhanced surfaces (Bostanci, Altalidi, & Nasrazadani, 2018; Bostanci et al., 2012; Silk, Kim, & Kiger, 2006), and medium with stronger heat transfer parameters (Hsieh & Yao, 2006; Xu, Si, Shao, & Tian, 2014) are the most commonly used techniques. Experiments (Hou, Tao, & Huai, 2014) were conducted on heat transfer characteristics and mechanisms of spray cooling in which micro-structured surfaces include the cubic fins and the straight pin fins served as heat exchange surfaces. It was found that the heat transfer performance of the straight pin fins is optimal in the single-phase region, and the heat transfer performance of the cubic fins is better in the two-phase region. A dimensionless number (DM) was created to characterize the heat transfer performance of different microstructures in single-phase heat transfer. The heat transfer effect of the surface in spray cooling was studied experimentally by Xie et al. (2013). Experiments show that the arrangement of fins plays a decisive role in the cooling performance of the macro-structured surface. With same surface geometries, the surface heat transfer enhancement effect of the multi-scale structure with microstructure is superior to macro-structured surface. Experiments on two heaters with different surface roughness were performed by Eduardo (MartínezGalván, Antón, Ramos, & Khodabandeh, 2013). It was found that for rough surfaces, the value of CHF increases with volume flow rate and for smooth surfaces, the value of CHF is independent of volume flow. The mixture of ethanol and water were used for spray cooling experiments by Ravikumar, Jha, Sarkar, Pal, and Chakraborty (2014). The cooling enhancement effect is optimal with the ethanol fraction of 500 ppm. In the ethanol-water-tween 20 mixture spray experiment proposed by Bhatt et al. (2017), the achieved CHF (2.1 MW/m2) is 1.6
distance between two adjacent thermocouples, mm distance from simulated heat source surface to the thermocouple T1, mm thermal conductivity of the heat source material copper, W/m.K dynamic viscosity (mPa∙S)
times that of pure water. The maximum heat transfer coefficient is obtained when the fraction of ethanol is 500 ppm. The heat transfer enhancement by the addition of high-alcohol surfactant and dissolving salt additive were studied by Cheng, Xie, Han, and Chen (2013). The optimum fractions of NaCl, Na2SO4, 1-Octanol, and 2-ethyl hexanol additives were demonstrated to be 1.72%, 2.76%, 0.02%, and 0.015%, respectively. The pool boiling characteristics of alumina, zirconia, and silica as nanoparticles of nanofluid were experimentally studied by Kim, Bang, Buongiorno, and Hu (2007). A significant increase in critical heat flux (CHF) was achieved at moderate nanoparticle fractions (< 0. 1 % by volume). Utomo, Poth, Robbins, and Pacek (2012), Nguyen, Roy, Gauthier, and Galanis (2007) and Vafaei & Borca-Tasciuc, 2014) also obtained research results about spray cooling with nano-additives. However, little research was proposed on the heat transfer characteristics of spray cooling through visualization, especially from the view of nozzle atomization. In this investigation, a spray cooling system has been established in combination with PIV system aiming to achieve visualization for investigating the relationship between atomization effects of nozzles with different pore sizes and the heat transfer performance. Besides, the heat transfer characteristics and the nozzle atomization of the nanofluid prepared by adding nano-alumina particles were also studied by combining the PIV system. The results of this study will not only provide a reference for nozzle selection, nanofluid fraction configuration, but also for flow and heat transfer characteristics optimization in spray cooling system design. 2. Equipment and methods 2.1. Bench construction The spray cooling system experimental bench established in this study mainly consists of a spray liquid supply system, a simulated heat source heating system, a data acquisition system, and a PIV (Particle Image Velocimetry) system. The nozzles selected in the experiment are 304 stainless steel solid cone nozzles, and the nozzle pore size is 0.8 mm, 1.2 mm, 1.5 mm, 2.0 mm. The experimental medium is water and nanofluid at constant room temperature. The surface area of the simulated heat source is a circular shape with a diameter of 24 mm and the maximum heat that the simulated heat source can achieve is about 1800 W. The distance from the nozzle to the surface of the simulated heat source is 100 mm. Other parameters are listed in Table 1. The photo of the spray cooling system and the spray system schematic are Table 1 Spray cooling experimental conditions.
2
Orifice-to-surface distance
10 mm
Nozzle inlet temperature Working fluid flow Ambient temperature
6-12 ℃ 20-40 L/h 3-15 ℃
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following formula.
shown in Fig. 1. The micro-high pressure pump is used to supply the liquid to the spray system, and the flow rate is adjusted by the flow regulating valve. The flow rate can be accessed by the flow meter LZ500 of Suzhou xianchi Co. which has a range of 0–200 L/h and maximum uncertainty of ± 5 L/h. The cooling medium could be atomized by the pressure nozzle into droplets and sprayed onto the surface of the heating block. A copper block was applied to simulate the heating part of the server, and the electric heating rod is installed at the lower end of the copper block. A power regulator is used to regulate the heating power which is transferred upward through the copper block to the surface to simulate different heat flux densities. Two different series of nozzles were selected for the experiments, the structures of which are shown in Fig. 2. As shown in Fig.2, the structure of No.2 nozzle is less complex than that of No.1 nozzle, resulting in a lower flow resistance. Comparison experiments were carried out at a flow rate of 40 L/h using a No. 1 series nozzle and a No. 2 series nozzle with a pore size of 2.0 mm. All rest experiments were carried out by using No. 1 series nozzles with different pore size.
Tw = T1 −
(Ti − Tj) δ1 Δδ
Where Tw is the temperature of the heat source surface, δ1 is the distance from the simulated heat source surface to the thermocouple T1. From the fitting of the temperature variation gradient, the relationship between T1 and the surface temperature can be obtained. The surface heat transfer coefficient can be calculated as below.
H=
q (Tw − Tin )
2.4. Experimental procedure The experiments conducted in this paper were divided into two parts, as shown in Fig. 4. The first part of the experiment is the heat transfer performance experiment. Pure water and different fractions of nano-alumina solution were used as the spray medium. The spray cooling effect under different working conditions could be obtained by altering the nozzle type, heating power and flow rate of the working
As an effective method to measure flow fields, many researchers have made many contributions to the application of this technology for research (Molezzi & Dutton, 1993; Schrijer, Scarano, van Oudheusden, & Bannink, 2005). A 2D PIV system SM3-5M200 of Beijing lifangtiandi Co. was applied in this research. PIV system consists of an illumination laser, a sync controller, an image acquisition board which was built in a computer in advance, a high-speed digital camera, and a computer which was used for recording and calculation. The model types of the specific equipment used in this research are shown in Table 2. The principle of the PIV system is to calculate the measured fluid velocity vector from the displacement of a small region in the flow field at a known time interval. Appropriate tracer particles have been sprinkled in the fluid in the area to be tested, and a laser pulse generated by a two-pulse laser with a time interval of Δ t forms a laser sheet to illuminate the flow field region to be studied. The flow field could be deduced by using a digital camera to obtain a flow field image of the two frames to be tested. Then the two photos of the flow field information would be transmitted to the data processor in which the velocity of each point or region by using cross-correlation analysis algorithm could be calculated to form the original vector. The schematic diagram of the experimental system is shown in Fig. 3. 2.3. Heat flux measurement and data acquisition instrument In order to calculate the surface heat transfer coefficient of the spray cooling simulated heat source, four K-type thermocouples were arranged in the vertical direction from the surface of the simulated heat source to the bottom, and the distance to the hot surface was t1 T1 :17 mm、t2 T2 : 25 mm、t3 T3 :33 mm、t4 T4 :41 mm respectively. The temperature is obtained by an Agilent 34972A data acquisition instrument. The maximum uncertainty of a K-type thermocouple is ± 0.8 ℃. According to one-dimensional Fourier heat conduction law, the radial temperature distribution and heat flux of the simulated heat source surface can be derived.
Ti − Tj Δδ
q= λ
Ti − Tj Δδ
(3)
Where H is the surface heat transfer coefficient, Tin is the spray substance nozzle inlet temperature. The nozzle inlet temperature is obtained by PT100 platinum resistor, the maximum uncertainty is ± 0.15 ℃.
2.2. PIV system introduction
q=λ
(2)
(1)
Where q is heat flux density at the heat source surface, λ is the thermal conductivity of the heat source material copper, Ti 、 Tj is the temperature measured by thermocouple ti Ti 、tj(1 < i < j < 4) Tj, Δδ is the distance between two adjacent thermocouples. According to our previous work, the uncertainty of heat flux is ± 4.9 % (Wang, Zhou, Yang, & Jiang, 2016). The temperature of the heat source surface can be calculated by the
Fig. 1. Spray cooling system. (a) No. 1 series nozzle (b) No. 2 series nozzle 3
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Fig. 2. Two different series of nozzle structures.
laser film thickness to about 1 mm and ensure that the light can illuminate the study area; (2) Place the camera in proper position and adjust the camera to a proper height; (3) Fix the charge coupled device (CCD) camera on the camera frame; connect the power cable of the CCD and the data cable which connect the CCD and the image board; (4) Take a photo of the ruler at the piece of light and calibrate the image of the ruler to determine the magnification of the system image; (5) Run the spray system, take the photo of the flow field, and ensure the particle distribution is uniform and the number is large; (6) Adjust system parameters until a satisfactory particle image is acquired; (7) Save the image sequence to perform subsequent processing including analyzing the velocity distribution of the flow field；(8) Import the velocity data collected by the PIV system into Tecplot and convert it into the velocity contour.
Table 2 PIV system equipment model. Device name
Model type
Illumination laser Sync controller Digital camera
Vlite-200 SM-Micropulse725 CLB-B2520M-SC000
2.5. Data selection In the experiment, measured data was used for analysis when steady state was achieved. For instance, the temperature variation rates of the four thermocouples for a nozzle with the pore size of 0.8 mm, flow rate of 20 L/h and input power of 50 W/cm2 are shown in Fig. 5. The heat transfer is considered to be in steady state when the temperature variation rate of each thermocouple is less than 1 °C in 5 min. 3. Results and discussions 3.1. Effect of the flow rate change on atomization state and heat transfer performance
Fig. 3. Operating principle diagram of the PIV system. (a) PIV system experimental procedure (b) Spray cooling experimental procedure
The heat transfer coefficient of the simulated heat source at the flow rate of 20 L/h and 30 L/h for the nozzle with the pore size of 0.8 mm was compared. It can be seen from Fig. 6 that the heat transfer coefficient increases with the increase of input heating power. However, the heat transfer coefficient tends to decrease when the heating power of 200 W/ cm2 is achieved with the flow rate of 20 L/h. This is because, with the development of heat flux, the droplets become vapor at the time they fall on the heating surface. The substance droplets are blocked by the vapor, which impairs the heat transfer. With the increase of droplet velocity, the droplets have the ability to overcome the vapor. Therefore with the flow rate of 30 L/h the heat transfer is still enhanced when the heat flux of 200 W/ cm2 is achieved. The velocity distributions of spray from a nozzle with a pore size of 0.8 mm at flow rates of 20 L/h and 30 L/h were obtained by the PIV system, as shown in Fig. 7. It can be seen from the two figures that the spray droplet are symmetrically distributed. The maximum velocity of the droplets appears at the axis of the cone and the velocity gradually decreases with the extend of the axis. Since the flow rate in Fig. 7(b) is 30 L/h which is larger than the flow rate in Fig. 7(a), the spray range in Fig. 7(b) is larger than that of Fig. 7(a). It can be seen from Fig. 7 that the spray coverage range is -30 mm to 30 mm when the flow rate is 20 L/h, and the value is -40 mm to 40 mm when the flow rate is 30 L/h,
fluid. The second part of the experiment is the application of PIV system to take visual graphics of the spray flow field. The procedures of the heat transfer experiment are as follows: (1) Adjust the height of the adjustable nozzle to the heating surface to a preset position by rotating the thread above the spray chamber; (2) Turn on the power switch of the solution pump and adjust the flow meter to make water the flow rate reaches a setting value; (3) Adjust the voltage of the regulated power supply for heating the heating rods to a setting value; (4) Turn on the computer and data acquisition instrument to record the temperature of the thermocouples in the simulated heat source; (5) When the temperature variation rate of each thermocouple is less than 1 °C within 5 min, the heat transfer is considered to reach a steady state; (6) Adjust the voltage value and proceed to the next set of experiments; (7) When the experiment of one nozzle is completed, turn off the power of the heating rod. After the simulated heating surface is cooled to environment temperature, replace the nozzles and repeat the above steps (3)–(6); (8) Different fractions of nano-alumina solution were prepared as working fluids, then repeat steps (3)–(6). The experimental procedures with the PIV system are listed as follows: (1) Adjust the laser light to the measurement position, set the 4
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Fig. 4. Experimental flow chart.
Fig. 5. Transient temperature variations under one case. Fig. 6. Comparison of heat transfer coefficients for a nozzle with a pore size of 0.8 and flow rates of 20 L/h and 30 L/h.
respectively. By comparing the surface heat transfer coefficients at the two flow rates in Fig. 6, it is found that the heat transfer coefficient at the flow rate of 30 L/h is smaller than the heat transfer coefficient at the flow rate of 20 L/h which is contrary to previous PIV experimental studies. As shown in Fig. 8, by observing the droplet distribution in the spray chamber, and the comparison of the velocity distributions at the two flow rates in Fig. 7, it is found that when the flow rate is 20 L/h, the nozzle cone spray with the pore size of 0.8 mm cannot reach the setting operation angel. Therefore the droplets can concentrate on the surface of the heating block and dissipate heat sufficiently. When the flow rate is 30 L/h, the cone spray angle reaches the maximum value, and the droplets ejected from the nozzle are scattered over the heat dissipating surface, which means some droplets do not participate in the heat exchange with the heating surface. The heat transfer coefficient is influenced by the dimensionless parameter Re. The Reynolds number Re is the ratio of inertial force to viscous forces with in a fluid, which indicates the flow state of the liquid droplets and the liquid film (Wang,
Jiang, Chen, & Zhou, 2017).
Re =
gD μ
(4)
With the flow rate of 30 L/h, as seen from Fig.7, the droplet number participated in the heat transfer is smaller than that with the flow rate of 20 L/h. Therefore, in this case less cooling medium is flowing through the heating surface, causing a lower Reynolds number, which means an insignificant surface heat transfer capability. 3.2. Effect of nozzle pore size variation on atomization state and heat transfer performance The velocity distribution of the same series of nozzles with the pore size of 1.2 mm, 1.5 mm, 2.0 mm at a flow rate of 40 L/h and a spray 5
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Fig. 7. Flow field distribution with a nozzle pore of 0.8 mm and different flow rate.
of 40 L/h can be obtained. The heat transfer coefficient of the heating block surface increases with the augment of the heating power. When the flow rate is constant, the heat exchange effect of the nozzle with larger diameter is better. Especially the droplets ejected from the nozzle with a diameter of 1.2 mm are smaller than the droplets ejected from the nozzles of 1.5 mm and 2.0 mm, and are more easily vaporized at an input power of 200 W/cm2 to form vapor layer on the heating surface. A formed vapor layer prevents subsequent droplets from contacting and transferring heat with the heating surface. By comparing the velocity maps of the three nozzles combined with the droplet distribution state which are shown in Fig. 11, it is found that although the droplets ejected by the small-caliber nozzle are large in initial velocity, the droplet distribution is not as uniform as that with large-diameter ones, and the edge velocity is weakened causing the surface not completely covered. The droplet velocity of the large holes is small, but the velocity distribution is more uniform and can evenly cover the entire surface. Therefore, compared with the velocity values, the velocity uniformity has a major effect on heat transfer.
height of 10 cm are shown in Fig. 9 respectively. It can be observed from Fig. 9 (a) that droplet velocity with the pore size of 1.2 mm at the spray axis can reach 7 m/s, and most of the droplets with high velocity are concentrated at the axis of the cone. It can be seen from Fig. 9 (b) that speed of droplets ejected by the nozzle with the pore size of 1.5 mm can reach 4.2 m/s, and part of the droplets which has a faster velocity deviates from the axis of the cone, resulting the droplet to not uniformly cover the surface of the heating block. What can be found in Fig. 9 (c) is that the fastest droplets ejected from the nozzle with the pore size of 2.0 mm could reach 2.8 m/s, and the faster droplets could well cover the surface of the heating block. Comparing the three velocity distribution images above, it can be found that as the diameter of the nozzle increases, the droplet velocity of the nozzle ejection decreases. The reason is that when the flow rate is constant, the pressure difference between the inlet and outlet of the nozzle decreases as the diameter of the nozzle increases. As the pressure difference decreases, the droplet velocity also decreases, and the degree of fluid fragmentation becomes smaller so that the initial droplet velocity is relatively lower. From Fig. 10 the relationship between heat transfer coefficients of droplets ejected from three nozzles with different calibers at a flow rate
Fig. 8. Droplet distribution in the spray chamber at different flow rate. 6
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Fig. 9. Flow field distribution with different pore sizes at a flow rate of 40 L/h.
in the experiment. The velocity distributions of two different series of nozzles with a pore size of 2.0 mm (as shown in Fig.2) are shown in Fig. 12, and a comparison of heat transfer coefficients is shown in Fig. 13. Comparing the speed profiles in Fig. 12, combined with the line graph of the heat transfer coefficient generated by the droplets ejected from the two nozzles, it is found that the velocity uniformity of the droplets ejected by the No. 2 nozzle on the heating surface is not as good as the uniformity of the droplets ejected from the No. 1, resulting in uneven heat distribution of the simulated heat source and affecting the heat transfer effect. The No. 2 nozzle has a droplet velocity up to 7.5 m/s. When the droplets hit the surface of the heat source, the droplets residence time is too short to exchange heat with the heating surface and the former droplets are replaced by the subsequent droplets. The droplet velocity distribution on the heat source surface of the No. 1 nozzle is uniform and the speed is not too large, and the droplets can exchange heat with the surface fully. These results also indicate that compared with high droplet velocity, the uniform velocity distribution plays a more significant role in enhancing the spray cooling heat transfer ability. When the heat flux is small, the evaporation of droplets is less than the supplement of droplets. Due to the uneven distribution of droplet velocity ejected from nozzle No. 2, the droplet at the edge is pushed away by the fluid at the center without exchanging heat. Therefore, the a liquid film is formed on the surface of a relatively high temperature, which hinders heat exchange, thereby increasing the thermal
Fig. 10. Comparison of heat transfer coefficients for nozzles with a pore size of 1.2 mm, 1.5 mm, 2.0 mm and flow rate of 40 L/h.
3.3. Comparison of velocity distribution and heat transfer characteristics of two different series of nozzles with a diameter of 2.0 mm In order to investigate the influence of droplet velocity uniformity, two different series of nozzles with the same diameter were conducted 7
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Fig. 11. Droplet distribution in the spray chamber of nozzles with different pore sizes at a flow rate of 40 L/h.
resistance. With the increase of the heat flux, the evaporation of the droplets leads to the thinning of the liquid film, the hindrance is weakened and the thermal resistance is reduced, and the heat transfer coefficient is increased. Therefore, the heat transfer coefficient trend of No. 2 nozzle is different from No. 1 nozzle.
alumina is 0.08%, the highest velocity of 8 m/s is achieved. As the nano-alumina fraction continues to increase, the droplet velocity decreases. When the mass fraction of the nano-alumina reaches 0.2%, the maximum flow rate of the spray droplets is reduced to 7 m/s. The variations of the heat transfer coefficient with the input heat flux of pure water and five different mass fractions of nanofluid are shown in Fig. 15. It can be seen from the figure that the heat transfer coefficient increases as the fraction of the nano-alumina increases before the mass fraction of 0.08%. When pure water is used as the coolant, the critical state is achieved at the input power of 150 W/cm2, and then a downward trend occurs because the cooling capacity of pure water deteriorates with the increase of the input power. As seen from Fig.14, the droplet velocity also increases as the fraction of the nano-alumina increases before the mass fraction of 0.08%. When the fraction reaches 0.08%, the droplet velocity and the surface heat transfer coefficient simultaneously reach a maximum value. This means the nanoparticles can flow with the liquid film with
3.4. Effect of different fractions of Nano-Alumina additive on heat transfer characteristics and heat transfer performance of flow field The PIV system was used to capture the flow field of pure water and different mass fractions of nano-alumina solution (0.02%, 0.04%, 0.08%, 0.12%, 0.20%, selected on the reference to Bellerová, Tseng, Pohanka, and Raudensky (2012) and Ravikumar et al. 2015) with a diameter of 0.8 mm at a flow rate of 20 L/h, as shown in Fig. 14. It can be seen from the figure that as the fraction of nano-alumina increases, the velocity of the spray droplets increases from the mass fraction of 0.02% to the mass fraction of 0.08%. When the fraction of the nano8
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Fig. 12. Flow field distribution of different series nozzles with a pore of 2.0 mm at a flow rate of 40 L/h.
nozzle structures and the nano fluid fractions to improve the heat transfer capacity. Due to the limitation of the experimental bench, the adjustable range of flow rate is limited. In our subsequent research, the adjustable range of flow rate for the experimental bench will be further expanded. Sufficient experimental results will be used to obtain better conclusions. Conclusions are as follows:
• The angle of the spray cone opening has a non-negligible effect on • Fig. 13. Comparison of heat transfer coefficients for two different series of nozzles with pore size of 2.0 mm.
•
high droplet velocity, which will enhance the convection heat transfer between the liquid film and the heating surface. And then from a fraction of 0.08% to 0.12%, the droplet velocity decreases, as well as the surface heat transfer coefficient. When the fraction increases to 0.2%, the droplet velocity decreases, resulting in a decrease in the flow disturbance on the heated surface liquid film. The impaired flow disturbance on the surface will directly cause the nanoparticles stacking on the surface instead of flowing away by the liquid film, which will enhance the thermal resistance on the heating surface. As a result, the heat transfer performance of the spray cooling deteriorates with its value smaller than that of pure water. For this experiment, the optimum mass fraction of nano-alumina is 0.08%.
•
the heat transfer effect of the spray cooling. In some cases, it is ensuring that the droplets not spraying beyond the surface more preferred than enhancing the droplet velocity to improve the heat transfer effect. As the diameter of the nozzle increases, the output velocity of the droplet and the angle of the spray vertebral both decrease, the heat transfer effect can be improved. The better the uniformity of the droplets velocity distribution covering the surface of the simulated heat source, the better the heat transfer of the surface. Adding a certain fraction of nano-additives to water will help to enhance both the velocity and the heat transfer effect of spray cooling. When the fraction exceeds the optimum value, the heat transfer will be impaired due to the enhancing of thermal resistance.
If spray cooling is applied to chip cooling in data center, the high inlet pressure is not preferred for generating due to the high probability of working fluid leakage. Therefore the spray flow rate is limited. In order to enhance the heat transfer ability, the nozzle structure and other parameters can be improved to achieve effective droplet size and uniform distribution at relatively moderate pressure for optimal heat transfer. Studies in this paper is still limited. In further research, more operating conditions concerning the nozzles and the cooling medium should be considered. Moreover, in practical application, the system volume should be optimized to satisfy the room inside the rack of the data center.
4. Conclusions In this paper, by establishing the spray cooling test bench and PIV system, the velocity distribution of the droplets from different types of nozzles were photographed, and the heat transfer performance corresponding to the velocity distributions were obtained. On the basis, the relationship between the velocity distribution of the droplets and the spray cooling heat transfer coefficient was studied. The innovation of this paper is the observation of the spray atomization flow distribution by the PIV visualiation system and its combination with the heat transfer analysis, which provides a reference for optimizing the atomization parameters including the flow rates, the
Acknowledgments This work is supported by the National Natural Science Foundation of China (Grant No. 51806096), Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. SJCX 0336), Natural Science Foundation of the Jiangsu Higher Education institutions of China (Grant No. 18KJB560007) and the Research Fund of Key 9
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Fig. 14. Flow field distribution of nano-alumina additives with different mass fractions.
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Hsieh, C., & Yao, S. (2006). Evaporative heat transfer characteristics of a water spray on micro-structured silicon surfaces. International Journal of Heat and Mass Transfer, 49, 962–974. Mudawar, I., & Estes, K. (1996). Optimizing and predicting CHF in spray cooling of a square surface. Journal of Heat Transfer, 118, 672–679. Cheng, W.-L., Liu, Q.-N., Zhao, R., & Fan, H.-l. (2010). Experimental investigation of parameters effect on heat transfer of spray cooling. Heat and Mass Transfer, 46, 911–921. Silk, E. A., Kim, J., & Kiger, K. (2006). Spray cooling of enhanced surfaces: Impact of structured surface geometry and spray axis inclination. International Journal of Heat and Mass Transfer, 49, 4910–4920. Bostanci, H., Rini, D. P., Kizito, J. P., Singh, V., Seal, S., & Chow, L. C. (2012). High heat flux spray cooling with ammonia: Investigation of enhanced surfaces for CHF. International Journal of Heat and Mass Transfer, 55, 3849–3856. Bostanci, H., Altalidi, S., & Nasrazadani, S. (2018). Two-phase spray cooling with HFC134a and HFO-1234yf on practical enhanced surfaces. Applied Thermal Engineering, 131, 150–158. Xu, H., Si, C., Shao, S., & Tian, C. (2014). Experimental investigation on heat transfer of spray cooling with isobutane (R600a). International Journal of Thermal Sciences, 86, 21–27. Hou, Y., Tao, Y., & Huai, X. (2014). The effects of micro-structured surfaces on multinozzle spray cooling. Applied Thermal Engineering, 62, 613–621. Xie, J., Tan, Y., Duan, F., Ranjith, K., Wong, T., Toh, K., et al. (2013). Study of heat transfer enhancement for structured surfaces in spray cooling. Applied Thermal Engineering, 59, 464–472. Martínez-Galván, E., Antón, R., Ramos, J. C., & Khodabandeh, R. (2013). Influence of surface roughness on a spray cooling system with R134a. Part I: Heat transfer measurements. Experimental Thermal and Fluid Science, 46, 183–190. Ravikumar, S. V., Jha, J. M., Sarkar, I., Pal, S. K., & Chakraborty, S. (2014). Enhancement of heat transfer rate in air-atomized spray cooling of a hot steel plate by using an aqueous solution of non-ionic surfactant and ethanol. Applied Thermal Engineering, 64, 64–75. Bhatt, N., Raj, R., Varshney, P., Pati, A., Chouhan, D., Kumar, A., et al. (2017). Enhancement of heat transfer rate of high mass flux spray cooling by ethanol-water and ethanol-tween20-water solution at very high initial surface temperature. International Journal of Heat and Mass Transfer, 110, 330–347. Cheng, W., Xie, B., Han, F., & Chen, H. (2013). An experimental investigation of heat transfer enhancement by addition of high-alcohol surfactant (HAS) and dissolving salt additive (DSA) in spray cooling. Experimental Thermal and Fluid Science, 45, 198–202. Kim, S. J., Bang, I. C., Buongiorno, J., & Hu, L. (2007). Surface wettability change during pool boiling of nanofluids and its effect on critical heat flux. International Journal of Heat and Mass Transfer, 50, 4105–4116. Utomo, A. T., Poth, H., Robbins, P. T., & Pacek, A. W. (2012). Experimental and theoretical studies of thermal conductivity, viscosity and heat transfer coefficient of titania and alumina nanofluids. International Journal of Heat and Mass Transfer, 55, 7772–7781. Nguyen, C. T., Roy, G., Gauthier, C., & Galanis, N. (2007). Heat transfer enhancement using Al2O3–water nanofluid for an electronic liquid cooling system. Applied Thermal Engineering, 27, 1501–1506. Vafaei, S., & Borca-Tasciuc, T. (2014). Role of nanoparticles on nanofluid boiling phenomenon: Nanoparticle deposition. Chemical Engineering Research and Design, 92, 842–856. Schrijer, F., Scarano, F., van Oudheusden, B., & Bannink, W. (2005). Application of PIV in a hypersonic double-ramp flow. AIAA/CIRA 13th International Space Planes and Hypersonics Systems and Technologies Conference, 3331. Molezzi, M., & Dutton, J. (1993). Application of particle image velocimetry in high-speed separated flows. AIAA Journal, 31, 438–446. Wang, Y., Zhou, N., Yang, Z., & Jiang, Y. (2016). Experimental investigation of aircraft spray cooling system with different heating surfaces and different additives. Applied Thermal Engineering, 103, 510–521. Wang, Y., Jiang, Y., Chen, W., & Zhou, B. (2017). Heat transfer characteristics of spray cooling beyond critical heat flux under severe heat dissipation condition. Applied Thermal Engineering, 123, 1356–1364. Bellerová, H., Tseng, A. A., Pohanka, M., & Raudensky, M. (2012). Spray cooling by solid jet nozzles using alumina/water nanofluids. International Journal of Thermal Sciences, 62, 127–137. Ravikumar, S. V., Haldar, K., Jha, J. M., Chakraborty, S., Sarkar, I., Pal, S. K., et al. (2015). Heat transfer enhancement using air-atomized spray cooling with water–Al2O3 nanofluid. International Journal of Thermal Sciences, 96, 85–93.
Fig. 15. Comparison of heat transfer coefficients for different fractions of nanoalumina additives.
Laboratory of Aircraft Environment Control and Life Support, MIIT, Nanjing University of Aeronautics and Astronautics(Grant No. KLAECLS-E-201902). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.scs.2019.101799. References Kant, K. (2009). Data center evolution: A tutorial on state of the art, issues, and challenges. Computer Networks, 53, 2939–2965. Marcinichen, J. B., Olivier, J. A., & Thome, J. R. (2012). On-chip two-phase cooling of datacenters: Cooling system and energy recovery evaluation. Applied Thermal Engineering, 41, 36–51. Zhang, H., Shao, S., Xu, H., Zou, H., & Tian, C. (2014). Free cooling of data centers: A review. Renewable and Sustainable Energy Reviews, 35, 171–182. Oró, E., Taddeo, P., & Salom, J. (2019). Waste heat recovery from urban air cooled data centres to increase energy efficiency of district heating networks. Sustainable Cities and Society, 45, 522–542. Cho, K., Chang, H., Jung, Y., & Yoon, Y. (2017). Economic analysis of data center cooling strategies. Sustainable Cities and Society, 31, 234–243. Saini, M., & Webb, R. L. (2002). Heat rejection limits of air cooled plane fin heat sinks for computer cooling, ITherm. Eighth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (pp. 1–8). Marcinichen, J. B., Thome, J. R., & Michel, B. (2010). Cooling of microprocessors with micro-evaporation: A novel two-phase cooling cycle. International Journal of Refrigeration, 33, 1264–1276. Oró, E., Allepuz, R., Martorell, I., & Salom, J. (2018). Design and economic analysis of liquid cooled data centres for waste heat recovery: A case study for an indoor swimming pool. Sustainable Cities and Society, 36, 185–203. Kandlikar, S. G., & Bapat, A. V. (2007). Evaluation of jet impingement, spray and microchannel chip cooling options for high heat flux removal. Heat Transfer Engineering, 28, 911–923. Chen, R.-H., Chow, L. C., & Navedo, J. E. (2002). Effects of spray characteristics on critical heat flux in subcooled water spray cooling. International Journal of Heat and Mass Transfer, 45, 4033–4043. Sozbir, N., Chang, Y., & Yao, S. (2003). Heat transfer of impacting water mist on high temperature metal surfaces. Journal of Heat Transfer, 125, 70–74. Oliphant, K., Webb, B., & McQuay, M. (1998). An experimental comparison of liquid jet array and spray impingement cooling in the non-boiling regime. Experimental Thermal and Fluid Science, 18, 1–10. Estes, K. A., & Mudawar, I. (1995). Correlation of Sauter mean diameter and critical heat flux for spray cooling of small surfaces. International Journal of Heat and Mass Transfer, 38, 2985–2996.
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