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nanolubricant mixture with surfactant
i n t e r n a t i o n a l j o u r n a l o f r e f r i g e r a t i o n 3 6 ( 2 0 1 3 ) 1 0 4 5 e1 0 5 5
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Nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant Haitao Hu a, Hao Peng b, Guoliang Ding a,* a b
Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China Carrier Air-Conditioning & Refrigeration R&D Management (Shanghai) Co., Ltd., 3239 Shenjiang Road, Shanghai 201206, China
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abstract
Article history:
The objective of this paper is to investigate the nucleate pool boiling heat transfer char-
Received 25 October 2012
acteristics of refrigerant/nanolubricant mixture with surfactant. In the experiments, three
Received in revised form
types of surfactants including SDS, CTAB and Span-80 were used. Nanolubricant was
14 December 2012
formed from Cu nanoparticles and oil VG68. The results show that, the ratio of heat
Accepted 16 December 2012
transfer coefficient of refrigerant/nanolubricant mixture with surfactant to that without
Available online 23 December 2012
surfactant (defined as surfactant impact factor, SIF ) are within 0.85e1.58, 0.73e1.31, and
Keywords:
increase of surfactant concentration and then decrease, and increase with the decrease of
Additive
surfactant molecular weight, nanolubricant concentration and heat flux. A nucleate pool
Nucleate boiling
boiling heat transfer correlation for refrigerant/nanolubricant mixture was proposed, and it
Lubricant
agrees well with the experimental data of refrigerant/nanolubricant mixture with surfac-
Particle
tant and that without surfactant.
0.68e1.24 for SDS, CTAB and Span-80, respectively. The values of SIF increase with the
ª 2012 Elsevier Ltd and IIR. All rights reserved.
Refrigerant
Caracte´ristiques du transfert de chaleur lors de l’e´bullition libre nucle´e´e d’un me´lange frigorige`ne / nanolubrifiant contenant un agent tensio-actif Mots cle´s : additif ; e´bullition nucle´e´e ; lubrifiant ; particule ; frigorige`ne
1.
Introduction
Nanolubricants (i.e., the mixture of nanoparticles and lubricating oil) can be used to improve the energy efficiency of refrigerant system (Wang et al., 2003, 2007; Bi et al., 2008). In the refrigeration system using nanolubricant, the working fluid is refrigerant/nanolubricant mixture. The existence of
lubricating oil is beneficial to the stability of the nanoparticles in the refrigeration cycle (Kedzierski, 2011). However, the nanoparticles in the refrigerant/nanolubricant mixture may aggregate and settle down when the refrigeration system is shutdown for long time. In order to ensure the long-term stability of the refrigerant/nanolubricant mixture in the refrigeration cycle, the aggregation and sedimentation of
* Corresponding author. Tel.: þ86 21 34206378; fax: þ86 21 34206814. E-mail address: [email protected] (G. Ding). 0140-7007/$ e see front matter ª 2012 Elsevier Ltd and IIR. All rights reserved. http://dx.doi.org/10.1016/j.ijrefrig.2012.12.015
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Nomenclature a1, a2 C Cp d d0 h
coefficients in Eq. (7) surfactant concentration isobaric specific heat/J kg1 K1 nanoparticles diameter/nm benchmark nanoparticle size/nm nucleate pool boiling heat transfer coefficient/ W m2 K1 hfg latent heat of vaporization/J kg1 M molecular weight m mass/kg m1, m2, m3 coefficients in Eq. (12) n coefficients in Eq. (12) q heat flux/W m2 SIF surfactant impact factor T temperature/oC nanolubricant concentration xn,o nanoparticles concentration in the mixture yn
nanoparticles should be prevented. Adding the surfactant is a widely used method for preventing the aggregation and sedimentation of nanoparticles in the nanofluid (Hwang et al., 2006; Choi et al., 2008). The addition of surfactant will change the thermophysical properties and then affect the boiling heat transfer characteristics (Wen and Wang, 2002; Chopkar et al., 2008; Kathiravan et al., 2009; Peng et al., 2011a). In order to well design and optimize the heat exchangers in refrigeration systems using refrigerant/nanolubricant, the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant should be investigated to evaluate the effect of surfactant on boiling heat transfer characteristics. The existing researches on the nucleate pool boiling heat transfer characteristics are mainly focused on the refrigerant/ nanolubricant without surfactant (Kedzierski and Gong, 2009; Kedzierski, 2009, 2011; Peng et al., 2010; 2011b). The research results show that, the nanoparticles cause a heat transfer enhancement compared with the heat transfer of refrigerant/ oil mixture (Kedzierski and Gong, 2009; Peng et al., 2010). The influence factors for the heat transfer enhancement of refrigerant/nanolubricant include nanolubricant concentration, nanoparticle concentration, nanoparticle type, nanoparticle size and heat flux (Kedzierski and Gong, 2009; Kedzierski, 2009, 2011; Peng et al., 2010; 2011b). However, the influence of surfactant is not concerned in these researches, and should be investigated. For the prediction correlations of the nucleate pool boiling heat transfer characteristics, the existing researches are mainly focused on the refrigerant/nanolubricant mixture without surfactant (Peng et al., 2010; 2011b; Kedzierski, 2011). A semi-empirical model was developed to predict the boiling enhancement based on the interaction of the nanoparticles with the bubbles (Kedzierski, 2011). Peng et al. (2011b) proposed an improved correlation based on the correlation of Peng et al. (2010), and it can reflect the effect of nanolubricant concentration, host fluid types, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. However, the influence of surfactant is not considered in these correlations.
Greek symbols l thermal conductivity/W m1 K1 m dynamic viscosity/Pa s r density/kg m3 s surface tension/N m1 un nanoparticles concentration in the nanolubricant Subscripts c copper f saturated liquid g saturated vapor n nanoparticles o lubricating oil r refrigerant s surfactant sat saturation w test surface
The purpose of this study is to experimentally investigate the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant, and to develop a correlation for refrigerant/nanolubricant reflecting the influences of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux.
2.
Experimental facility and test conditions
2.1. Preparation and characterization of refrigerant/ nanolubricant mixture with surfactant R113 is chosen as the host refrigerant in the present study, just as Peng et al. (2010) did; and Cu nanoparticles and lubricating oil VG68 are also applied in preparing the refrigerant/nanolubricant mixture. Although R113 is not used any more in the refrigeration and air conditioning industry, we use it in the lab instead of common refrigerants (e.g. R134a and R410A) for the follow reasons: 1) R113 is in liquid state at atmospheric pressure and room temperature, making it is more suitable to produce characteristic-stable refrigerant/nanolubricant mixture for experiments; 2) the difference between R113 and common refrigerants are much less than refrigerants and other common type fluids such as water and oil. The properties of refrigerant R113 are given in Table 1.
Table 1 e Properties of refrigerant R113. Property Chemical formula Molecular mass Normal boiling point Critical temperature Critical pressure
Unit e g mol1 oC oC MPa
Value or format Cl2FCeCClF2 187.37 47.6 214.1 3.39
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Table 2 e Properties of Cu nanoparticles. Property Atomic mass Average particle diameter Density Thermal conductivity Isobaric specific heat
Unit 1
g mol nm kg m3 W m1 K1 J kg1 K1
Value 63.54 20 8920 398 385
Cu nanolubricant is formed by Cu nanoparticles with the average diameter of 20 nm and lubricating oil VG68. Cu nanoparticles are produced by hydrogen direct current arc plasma evaporation method. The properties of Cu nanoparticles are given in Table 2, and the TEM (transmission electron microscope) photographs of Cu nanoparticles are shown in Fig. 1. The lubricating oil VG68 is ester oil with a density of 0.964 g cm3 at 15 C and kinematic viscosities of 66.79 and 8.23 mm2 s1 at 40 C and 100 C, respectively, as reported by the manufacturer. In the present study, one anionic surfactant (SDS), one cationic surfactant (CTAB) and one nonionic surfactant (Span80) are used. The physical and chemical properties of these three surfactants are listed in Table 3. R113/Cu nanolubricant mixture with surfactant is prepared by the following steps: 1) weighing the required mass of Cu nanoparticles and surfactants by a digital electronic balance with a measurement range of 10 mge210 g and a maximum error of 0.1 mg; 2) putting the Cu nanoparticles into the weighed lubricating oil VG68 to form a Cu nanolubricant; 3) putting the Cu nanolubricant into the weighed R113 to form a R113/Cu nanolubricant; 4) putting the surfactants into the R113/Cu nanolubricant to form the R113/Cu nanolubricant mixture with surfactant; 5) vibrating the R113/Cu nanolubricant mixture with surfactant by an ultrasonic processor for 1 h to disperse the nanoparticles evenly. Experimental observation shows that the stable dispersion of Cu nanoparticles in the R113/Cu nanolubricant mixture with surfactant can be kept for more than 24 h. The duration of the experiment for each sample of R113/Cu nanolubricant mixture with surfactant is less than 4 h which is shorter than 24 h,
Table 3 e Properties of the surfactants used in the experiments. Surfactant name
SDS
CTAB
Span-80
Chemical formula Ionic nature Form
C12H25SO4Na Anionic White powder
C19H42NBr Cationic White powder
Molecular weight HLB value
288.3 40
364.5 15.8
C24H44O6 Nonionic Pale yellow oily liquid 428.6 4.3
so the prepared R113/Cu nanolubricant mixture with surfactant can maintain good uniformity in the experiment. In order to quantitatively describe the composition of refrigerant/nanolubricant mixture with surfactant, the following concentrations are defined. 1) Surfactant concentration (C ), which is the ratio of the mass of surfactant to the mass of refrigerant/nanolubricant mixture with surfactant, presented as Eq. (1): C¼
ms mn;o þ mr þ ms
(1)
where, ms, mn,o and mr are the mass of surfactant, nanolubricant and refrigerant, respectively. 2) Nanolubricant concentration (xn,o), which is the ratio of the mass of nanolubricant to the mass of refrigerant/nanolubricant mixture with surfactant, presented as Eq. (2): xn;o ¼
mn;o mn;o þ mr þ ms
(2)
3) Nanoparticles concentration in nanolubricant (un), which is the ratio of the mass of nanoparticles to the mass of nanolubricant, presented as Eq. (3): un ¼
mn mn þ mo
(3)
where, mn and mo are the mass of nanoparticles and lubricating oil, respectively. 4) Nanoparticles concentration in the refrigerant/nanolubricant mixture ( yn), which is the ratio of the mass of nanoparticles to the mass of refrigerant/nanolubricant mixture, presented as Eq. (4): yn ¼
mn mn;o þ mr
(4)
In the experiments for each type of surfactant, C is from 200 to 10,000 ppm, xn,o is from 1 to 5 wt%, un is 20 wt%, and yn is from 0.2% to 1%.
2.2.
Fig. 1 e TEM photographs of Cu nanoparticles.
Experimental facility and test conditions
The experimental facility used for testing the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant is composed of a test
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Fig. 2 e Schematic diagram of experimental facility.
section, a boiling apparatus and a condensation loop, as schematically shown in Fig. 2. The test section is fabricated by a copper block. The top horizontal surface of the copper block is circular with a diameter of 20.0 mm, and flat with an average roughness (Ra) of 1.6 mm. This surface is used as the test surface for pool boiling heat transfer experiments. Five calibrated K-type thermocouples with a precision of 0.1 C are inserted into five 1.0 mm diameter holes in the top part of the copper block in order to obtain the temperature gradient of the test surface accurately, and then to determine the heat flux and the test surface temperature. The liquid temperature is measured by a calibrated K-type thermocouple with a precision of 0.1 C, and the pressure inside the boiling chamber is measured by a pressure transducer with a precision of 0.1 kPa. The heat flux through the test surface is controlled
by adjusting the heating power of the cartridge heater. The saturation pressure is controlled by two methods: 1) adjusting the heating power of the electrical heating wire; 2) adjusting the mass flow rate of the cool water by controlling the opening of the valve in the condensation loop. The principle and operation procedure of the experimental facility were introduced in detail in Peng et al. (2010). Test conditions are tabulated in Table 4. Total 456 experimental data are recorded, including 432 experimental data of R113/Cu nanolubricant mixtures with three different types of surfactants (i.e., SDS, CTAB and Span-80) and 24 experimental data of R113/Cu nanolubricant mixtures without surfactant as baseline. All signals of temperature and pressure are collected by a data acquisition system and transmitted to a computer after the system reaches a steady state.
Table 4 e Test conditions. Test fluid
R113/Cu/VG68/SDS, R113/Cu/VG68/CTAB, R113/Cu/VG68/Span-80
Heat flux (kW m2)
Saturation pressure (kPa)
10, 20, 30, 40, 50, 60, 70, 80
101.3
Nanolubricant Nanoparticles concentration in concentration xn,o (wt %) nanolubricant (un) 20
1, 3, 5
Surfactant concentration C (ppm)
No. of experimental data
0, 200, 500, 1000, 2000, 5000, 10,000
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2.3.
Data reduction and uncertainties
The nucleate pool boiling heat transfer coefficient, h, is calculated as: h ¼ q=ðTw Tsat Þ
(5)
where, q is the heat flux, Tw is the test surface temperature, and Tsat is the saturated liquid temperature. For pure R113, the saturated liquid temperature, Tsat, is 47.6 C at the saturated pressure of 101.3 kPa. For refrigerant/ nanolubricant mixture with surfactants, the saturated liquid temperature, Tsat, changes with the variations of the composition, and is measured by the K-Type thermocouple. The measured value of the saturated liquid temperature can reflect its change with the variations of the compositions of refrigerant/nanolubricant mixture with surfactant. The heat flux, q, is calculated by Eqs. (6) and (7) based on the one-dimensional heat conduction equation: dT dz w
(6)
T ¼ a1 þ a2 z
(7)
q ¼ lc
where, lc is the copper thermal conductivity, z is the coordinate perpendicular to the test surface, a1 and a2 are constants correlated based on the measured five temperatures on the copper block. The test surface temperature, Tw, is calculated as: Tw ¼ ða1 þ a2 zÞjz¼0 ¼ a1
(8)
The relative uncertainties of heat flux and nucleate pool boiling heat transfer coefficient are estimated to be smaller than 8.9% and 9.2%, respectively. Tests under several conditions were repeated for three times, and the differences among the three testing results under each condition are less than 5%.
3.
Experimental results and discussion
3.1. Nucleate pool boiling heat transfer coefficients of refrigerant/nanolubricant mixture with surfactant The nucleate pool boiling heat transfer coefficients of R113/Cu nanolubricant mixtures with three types of surfactants (i.e., SDS, CTAB and Span-80) are shown in Fig. 3 (a)e(c), respectively. For each type of surfactant, experimental conditions cover three nanolubricant concentrations (xn,o), i.e., 1 wt%, 3 wt% and 5 wt %. Fig. 3 (a) shows the experimental data of the mixture with anionic surfactant (SDS). It can be seen that at nanolubricant concentration (xn,o) of 1 wt%, the presence of SDS enhances the nucleate pool boiling heat transfer characteristics for all SDS concentrations, and the maximum enhancement occurs at the SDS concentration (CSDS) of 2000 ppm. At xn,o of 3 wt% and 5 wt%, the presence of SDS enhances the nucleate pool boiling heat transfer under the experimental conditions except at CSDS of 10,000 ppm, and the maximum enhancements occur at CSDS of 5000 ppm. Fig. 3 (b) shows the experimental data of the mixture with cationic surfactant (CTAB). It can be seen that at each
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nanolubricant concentration (xn,o), the presence of CTAB enhances the nucleate pool boiling heat transfer characteristics under the experimental conditions except at the CTAB concentration (CCTAB) of 10,000 ppm. The maximum enhancements occur at CCTAB of 500 ppm, 1000 ppm and 2000 ppm when the values of xn,o are 1 wt%, 3 wt% and 5 wt%, respectively. Fig. 3 (c) shows the experimental data of the mixture with nonionic surfactant (Span-80). It can be seen that at each nanolubricant concentration (xn,o), the presence of Span-80 enhances the nucleate pool boiling heat transfer characteristics under the experimental conditions except at the Span-80 concentration (CSpan-80) of 10,000 ppm. The maximum enhancements occur at CSpan-80 of 1000 ppm, 2000 ppm and 5000 ppm when the values of xn,o are 1 wt%, 3 wt% and 5 wt%, respectively. From the experimental results, it can be concluded that the surfactant concentration, surfactant type, nanolubricant concentration and heat flux have influences on the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture. The influences will be quantitatively analyzed in the following sections.
3.2. Influence of surfactant concentration on the nucleate pool boiling heat transfer characteristics Surfactant impact factor, SIF, is defined to quantify and analyze the surfactant influence on the nucleate pool boiling heat transfer characteristics of refrigerant-nanolubricant mixture with surfactant, presented as Eq. (9): SIF ¼ hr;n;o;s =hr;n;o
(9)
where, hr,n,o,s and hr,n,o are the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant and that of refrigerant/nanolubricant mixture without surfactant, respectively. Fig. 4 (a)e(c) show the influences of surfactant concentration on the nucleate pool boiling heat transfer characteristics for SDS, CTAB and Span-80, respectively. It can be seen that SIF for SDS, CTAB and Span-80 are in the ranges of 0.85e1.58, 0.73e1.31 and 0.68e1.24, respectively. The values of SIF are higher than 1.0 when the surfactant concentration is smaller than or equal to 5000 ppm. With the increase of surfactant concentration, SIF initially increases and reaches the maximum value, and then decreases with further increase of surfactant concentration. At high surfactant concentration (e.g., 10,000 ppm), the values of SIF are lower than 1.0. This phenomenon is caused by the conjunct role of enhancement factors and deterioration factors. The enhancement factors include: 1) the surfactant decreases the mixture surface tension (Wu et al., 1995), and then decreases the bubble departure diameter and increases the bubble departure frequency; 2) the surfactant increases the active nucleation sites (Kedzieski, 1999); 3) the surfactant may aggregate and serve as boiling nuclei (Zhang, 2004), causing the secondary nucleation on the bubble. The deterioration factors include: 1) the surfactant increases the viscosity, and then suppresses the micro-convection near heating surface (Zhang, 2004); 2) the surfactant weakens the interaction between nanoparticles and heating surface. At low surfactant concentration, the enhancement factors dominate; while at high surfactant concentration, the deterioration factors dominate.
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Fig. 3 e Nucleate pool boiling heat transfer coefficients of R113/Cu nanolubricant mixtures with three types of surfactants: (a) SDS; (b) CTAB; (c) Span-80.
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Fig. 4 e Surfactant impact factor (SIF ) for three types of surfactants: (a) SDS; (b) CTAB; (c) Span-80.
Therefore, SIF increases with the increase of surfactant concentration, and then decreases. It can also be seen from Fig. 4 that, the optimal surfactant concentrations corresponding to the maximal SIF are different for different surfactant types and lubricant concentrations.
For surfactant SDS, the optimal surfactant concentrations are 2000 ppm, 5000 ppm and 5000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. For surfactant CTAB, the optimal surfactant concentrations are 500 ppm, 1000 ppm and 2000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. For surfactant
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Span 80, the optimal surfactant concentrations are 1000 ppm, 2000 ppm and 5000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. The possible reason for this phenomenon is as follows. With the increase of nanolubricant concentration, the surfactant aggregation is suppressed, and then more surfactant is needed to form the large surfactant particles serving as boiling nuclei. Therefore, the optimal surfactant concentration increases with the increase of nanolubricant concentration. For the refrigerant-based nanofluid (xn,o ¼ 0), the aggregation of the surfactant is not influenced by the change of nanolubricant concentration, so the optimal surfactant concentration is a constant value for a fixed type of surfactant (Peng et al., 2011a).
3.3. Influence of surfactant type on the nucleate pool boiling heat transfer characteristics Fig. 5 shows the influence of surfactant type on the nucleate pool boiling heat transfer characteristics. It can be seen that the values of SIF are in the order of SDS > CTAB > Span-80 at one certain surfactant concentration (C ) and nanolubricant concentration (xn,o), which is opposite to the order of the molecular weight values for SDS (M ¼ 288.3), CTAB (M ¼ 364.5) and Span-80 (M ¼ 428.6). The possible reason for this phenomenon is as follows. With the decrease of molecular weight, the diffusion velocities of surfactant molecules increase, and the accumulation of surfactant on the growing bubble surface is intensified, resulting in more obvious influences of surfactant on the surface tension and the heat transfer characteristics. Therefore, SIF increases with the decrease of molecular weight value.
3.4. Influence of nanolubricant concentration on the nucleate pool boiling heat transfer characteristics Fig. 6 shows the influence of nanolubricant concentration on the nucleate pool boiling heat transfer characteristics. It can be seen that SIF increases with the decrease of nanolubricant concentration (xn,o). On the condition of C ¼ 500 ppm, the value of SIF for SDS increases maximally by 22.2% with the decrease of xn,o from 5 wt% to 1 wt%. The possible reasons for this
Fig. 5 e Influence of surfactant type on SIF.
Fig. 6 e Influence of nanolubricant on SIF.
phenomenon are as follows. The decrease of nanolubricant concentration leads to the decrease of the mixture viscosity and the increase of the diffusion velocities of surfactant molecules, resulting in more surfactant molecules accumulating on the growing bubble surface and surface tension decreasing rapidly. With the decrease of surface tension, the enhancement of nucleate pool boiling becomes larger, and then SIF increases with the decrease of nanolubricant concentration. Fig. 7 shows the comparison of SIF for refrigerant/nanolubricant mixture with that for refrigerant-based nanofluid (Peng et al., 2011a). The comparison results show that, the values of SIF for refrigerant/nanolubricant mixture and refrigerant-based nanofluid are in the ranges of 1.01e1.11, and 1.07e1.19, respectively. The values of SIF for refrigerant/ nanolubricant mixture are smaller than those for refrigerantbased nanofluids (xn,o ¼ 0). It is in accordance with the regularity that SIF increases with the decrease of nanolubricant concentration (xn,o).
Fig. 7 e Comparison of SIF for refrigerant/nanolubricant mixture with that for refrigerant-based nanofluid.
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3.5. Influence of heat flux on the nucleate pool boiling heat transfer characteristics From Fig. 7, it can also be seen that the value of SIF increases with the decrease of heat flux (q). With the decrease of q from 80 kW m2 to 10 kW m2, the values of SIF for SDS, CTAB and Span-80 increases by 7.4%, 5.5% and 4.3%, respectively. The possible reason for the increase of SIF with the decrease of heat flux is as follows. At high heat flux, the bubble departure
hr;n;o ¼
are suitable for both the refrigerant/nanolubricant mixture with surfactant and that without surfactant. The new correlation is proposed at the form of the product of the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture without surfactant (hr,n,o) and the surfactant impact factor (SIF ), as shown in Eq. (10). hr;n;o;s ¼ SIF,hr;n;o
(10)
q "
1:3068 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi#0:33 Cp;r;n;o;f mr;n;o;f hfg dn q sr;n;o
0:0093 þ 0:00356 0:0048un þ 0:0025xn;o Cp;r;n;o;f d0 lr;n;o;f mr;n;o;f hfg g r r r;n;o;f
frequency increases, weakening the accumulation of surfactant on the growing bubble surface, thus the influence of surfactant on the surface tension becomes weaker and SIF increases with the decrease of heat flux.
4. A nucleate pool boiling heat transfer correlation for refrigerant/nanolubricant mixture According to the above analysis and the existing research results (Kedzierski and Gong, 2009; Kedzierski, 2011, 2009; Peng et al., 2010; 2011b), the conclusion can be deduced that, the influencing factors for nucleate pool boiling heat transfer characteristics of refrigerant/lubricant mixture with surfactant include surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. Therefore, in order to develop a correlation of the nucleate pool boiling heat transfer coefficient for refrigerant/nanolubricant mixture, the above influencing factors should be reflected in the correlation. Peng et al. (2011b) correlation is one existing nucleate pool boiling heat transfer coefficient correlation for refrigerant/ nanolubricant mixture, and it reflects the effect of nanolubricant concentration, host fluid types, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. One effective method for developing a general correlation is to introduce the surfactant impact factor (SIF ) in Peng et al. (2011b) correlation. SIF should be expressed as the function of surfactant concentration, molecular weight of surfactant, nanolubricant concentration and heat flux. Furthermore, when the surfactant concentration is equal to zero, the value of SIF should be equal to 1, making sure that the correlations
( qexp ð1395C þ 14CÞ 2
hr;n;o;s ¼
(11)
r;g
where, Cp,r,n,o,f, mr,n,o,f, and lr,n,o,f are the isobaric specific heat, the dynamic viscosity and the thermal conductivity of liquid refrigerant/nanolubricant mixture, respectively; sr,n,o is the surface tension of refrigerant/nanolubricant mixture; rr,g and rr,n,o,f are the densities of vapor refrigerant and liquid refrigerant/nanolubricant mixture, respectively; hfg is the latent heat of vaporization; dn is the nanoparticle diameter; d0 is the benchmark nanoparticle size (the value is 100 nm); un is the nanoparticle concentration in the nanolubricant. The properties of refrigerant/nanolubricant mixture can be calculated with the models presented in Appendix. The key for development of the new correlation is to determine the SIF in Eq. (10). The SIF is expressed as Eq. (12). SIF ¼ exp m1 C2 þ m2 C
m3 ðqMxn;o Þn
(12)
The four coefficients m1, m2, m3 and n in Eq. (12) are fitted based on experimental data of R113/Cu nanolubricant mixtures with three different types of surfactants (i.e., SDS, CTAB and Span-80) in this study, covering the surfactant concentrations from 200 to 10,000 ppm, and the nanolubricant concentrations from 1 to 5 wt%. By nonlinear programming solution method, the four coefficients of m1, m2, m3 and n can be determined as 1395, 14, 2400 and 0.48, respectively. Therefore, Eq. (12) for calculating SIF becomes Eq. (13). ( SIF ¼ exp
1395C2 þ 14C
2400
)
ðqMxn;o Þ0:48
(13)
Based on Eqs. (10), (11) and (13), the new correlation for predicting the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant is expressed as Eq. (14).
2400
)
ðqMxn;o Þ0:48 "
1:3068 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi#0:33 Cp;r;n;o;f mr;n;o;f hfg dn q sr;n;o
0:0093 þ 0:00356 0:0048un þ 0:0025xn;o Cp;r;n;o;f d0 lr;n;o;f mr;n;o;f hfg g r r r;n;o;f
r;g
(14)
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for other kinds of refrigerant/nanolubricant mixtures with or without surfactants.
5.
Fig. 8 e Comparison of the predicted values of the new correlation with the experimental data of refrigerant/ nanolubricant mixture with surfactant and that without surfactant.
Fig. 8 shows the comparison of the predicted values of the new correlation with the experimental data of R113/Cu nanolubricant mixture with surfactant obtained in the present study and the experimental data of refrigerant/nanolubricant mixture without surfactant (Kedzierski and Gong, 2009; Peng et al., 2010; 2011b). It can be seen that the predicted values can agree with 91% of the experimental data of refrigerant/nanolubricant mixture with surfactant within a deviation of 25%; the predicted values can agree with 95% of the experimental data of R134a/nanolubricant mixture (Kedzierski and Gong, 2009) and R113/nanolubricant mixture (Peng et al., 2010, 2011b) within the deviation of 25%. The new correlation considers the influencing factors of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux, and is verified to have good predictions to refrigerant/nanolubricant mixture with surfactant and that without surfactant. The ranges of applicability for the new correlation are as follows: the surfactant types of SDS, CTAB and Span-80, surfactant concentrations from 0 to 10,000 ppm, nanolubricant concentrations from 1 wt% to 5 wt%, nanoparticle concentrations from 0.1 wt % to 1 wt%, nanoparticle sizes from 20 nm to 80 nm, heat fluxes from 10 to 120 kW m2. More verifications are needed in the future in order to ensure the accuracy of this correlation
Property Specific heat (J kg
Conclusions
(1) The presence of SDS, CTAB and Span-80 enhances the nucleate pool boiling heat transfer of R113/Cu nanolubricant on most conditions except at high surfactant concentrations. The ratio of nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant to that without surfactant, SIF, are in the ranges of 0.85e1.58, 0.73e1.31, and 0.68e1.24 for SDS, CTAB and Span-80, respectively. With the increase of surfactant concentration, SIF increases and reaches the maximum value, and then decreases. (2) The values of SIF are in the order of SDS > CTAB > Span-80 at one certain surfactant concentration and nanolubricant concentration, which is opposite to the order of the molecular weight values for SDS, CTAB and Span-80. (3) SIF increases with the decrease of nanolubricant concentration, and the optimal surfactant concentration corresponding to the maximal SIF increases with the increase of nanolubricant concentration. (4) For one certain surfactant concentration, nanolubricant concentration and surfactant type, SIF increases with the decrease of heat flux. (5) A correlation for predicting the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture is proposed, and it can reflect the influences of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. The new correlation agrees well with the experimental data of refrigerant/nanolubricant mixture with surfactant and that without surfactant.
Acknowledgments The authors gratefully acknowledge the support from the National Natural Science Foundation of China (Grant No. 50976065).
Appendix. Calculation of the properties of refrigerant/nanolubricant mixture
Model for calculating property 1
1
K )
Viscosity (Pa s)
Thermal conductivity (W m1 K1)
Cp,r,n,o,f ¼ (1 xn,o)Cp,r,f þ xn,oCp,n,o Cp,n,o ¼ (1 fn)Cp,o þ fnCp,n mr;n;o;f ¼ eðxn;o lnmn;o þð1xn;o Þlnmr;f Þ 1 mn;o ¼ mo ð1 fn Þ2:5 lr,n,o,f ¼ lr,f(1 xn,o) þ ln,oxn,o0.72xn,o(1 xn,o)(ln,o lr,f) ln þ 2lo 2fn ðlo ln Þ ln;o ¼ lo ln þ 2lo þ fn ðlo ln Þ
Author Jensen and Jackman (1984) Pak and Cho (1998) Kedzierski and Kaul (1993) Brinkman (1952) Baustian et al. (1988)
Hamilton and Crosser (1962)
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(continued ) Property Surface tension (N m1) Density (kg m3) Volume fraction of nanoparticles in the nanolubricant
Model for calculating property 0:5 sr;n;o ¼ sr þ ðsn;o sr Þxn;o !1 sn,o ¼ so xn;o 1 xn;o rr;n;o;f ¼ þ rn,o¼(1 fn) rn;o rr;f ro þ fnrn un ro fn ¼ un ro þ ð1 un Þrn
references
Baustian, J.J., Pate, M.B., Bergles, A.E., 1988. Measuring the concentration of a flowing oil-refrigerant mixture: instrument test facility and initial results. ASHRAE Trans. 94 (1), 167e177. Bi, S.S., Shi, L., Zhang, L.L., 2008. Application of nanoparticles in domestic refrigerators. Appl. Therm. Eng. 28, 1834e1843. Brinkman, H.C., 1952. The viscosity of concentrated suspensions and solution. J. Chem. Phys. 20, 571e581. Choi, C., Yoo, H.S., Oh, J.M., 2008. Preparation and heat transfer properties of nanoparticles-in- transformer oil dispersions as advanced energy-efficient coolants. Curr. Appl. Phys. 8, 710e712. Chopkar, M., Das, A.K., Manna, I., Das, P.K., 2008. Pool boiling heat transfer characteristics of ZrO2ewater nanofluids from a flat surface in a pool. Heat Mass. Transfer 44, 999e1004. Das, S.K., Putra, N., Roetzel, W., 2003. Pool boiling characteristics of nano-fluids. Int. J. Heat Mass. Transfer 46 (5), 851e862. Hamilton, R.L., Crosser, O.K., 1962. Thermal conductivity of heterogeneous two-component systems. Ind. Eng. Chem. Fundam. 1 (3), 187e191. Hwang, Y., Park, H.S., Lee, J.K., Jung, W.H., 2006. Thermal conductivity and lubrication characteristics of nanofluids. Curr. Appl. Phys. 6 (S1), e67ee71. Jensen, M.K., Jackman, D.L., 1984. Prediction of nucleate pool boiling heat transfer coefficients of refrigeranteoil mixtures. J. Heat Transfer 106, 184e190. Kathiravan, R., Kumar, R., Gupta, A., Chandra, R., 2009. Characterization and pool boiling heat transfer studies of nanofluids. J. Heat Transfer 131 (081902), 1e8. Kedzierski, M.A., 2011. Effect of Al2O3 nanolubricant on R134a pool boiling heat transfer. Int. J. Refrigeration 34, 498e508. Kedzierski, M.A., Gong, M., 2009. Effect of CuO nanolubricant on R134a pool boiling heat transfer. Int. J. Refrigeration 32 (5), 791e799. Kedzierski, M. A., 2009. Effect of Diamond Nanolubricant on R134a Pool Boiling Heat Transfer. In: Proc. of MNHMT09 2nd ASME Micro/Nanoscale Heat Mass Transfer Int. Conf., Shanghai, China, paper 18032.
Author Jensen and Jackman (1984) Das et al. (2003) Peng et al. (2011b) Peng et al. (2011b)
Kedzieski, M.A., 1999. Enhancement of R123 pool boiling by the addition of N-hexane. J. Enhanced Heat Transfer 6, 343e355. Kedzierski, M. A., Kaul, M. P., 1993. Horizontal nucleate flow boiling heat transfer coefficient measurements and visual observations for R12, R134a, and R134a/ester lubricant mixtures. In: Proc. of the 6th Int. Symp. on Transp. Phenom. in Therm. Eng. 1, 111e116. Pak, B.C., Cho, Y.I., 1998. Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particles. Exp. Heat Transfer 11 (2), 151e170. Peng, H., Ding, G.L., Hu, H.T., 2011a. Effect of surfactant additives on nucleate pool boiling heat transfer of refrigerant-based nanofluid. Exp. Therm Fluid Sci. 35, 960e970. Peng, H., Ding, G.L., Hu, H.T., Jiang, W.T., 2011b. Effect of nanoparticle size on nucleate pool boiling heat transfer of refrigerant/oil mixture with nanoparticles. Int. J. Heat Mass. Transfer 54, 1839e1850. Peng, H., Ding, G.L., Hu, H.T., Jiang, W.T., Zhuang, D.W., Wang, K.J., 2010. Nucleate pool boiling heat transfer characteristics of refrigerant/oil mixture with diamond nanoparticles. Int. J. Refrigeration 33 (2), 347e358. Wang, K.J., Shiromoto, K., Mizogami, T., 2007. Experiment study on the effect of nano-scale particle on the condensation process. In: Proc. of the 22nd Int. Congress of Refrigeration, August 20-26, Paper No. B1eB1005. Wang, R.X., Hao, B., Xie, G.Z., 2003. A refrigerating system using HFC134a and mineral lubricant appended with n-TiO2(R) as working fluids. In: Proc. of the 4th Int. Symp. on HAVC. Tsinghua University Press, Beijing, China, pp. 888e892. Wen, D.S., Wang, B.X., 2002. Effect of surface wettability on nucleate pool boiling heat transfer for surfactant solutions. Int. J. Heat Mass. Transfer 45, 1739e1747. Wu, W.T., Yang, Y.M., Maa, J.R., 1995. Enhancement of nucleate boiling heat transfer and depression of surface tension by surfactant additives. J. Heat Transfer 117, 526e529. Zhang, J.T., 2004. Experimental and computational study of nucleate pool boiling heat transfer in aqueous surfactant and polymer solutions. Ph.D. dissertation, University of Cincinnati.
Available online at www.sciencedirect.com
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journal homepage: www.elsevier.com/locate/ijrefrig
Nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant Haitao Hu a, Hao Peng b, Guoliang Ding a,* a b
Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China Carrier Air-Conditioning & Refrigeration R&D Management (Shanghai) Co., Ltd., 3239 Shenjiang Road, Shanghai 201206, China
article info
abstract
Article history:
The objective of this paper is to investigate the nucleate pool boiling heat transfer char-
Received 25 October 2012
acteristics of refrigerant/nanolubricant mixture with surfactant. In the experiments, three
Received in revised form
types of surfactants including SDS, CTAB and Span-80 were used. Nanolubricant was
14 December 2012
formed from Cu nanoparticles and oil VG68. The results show that, the ratio of heat
Accepted 16 December 2012
transfer coefficient of refrigerant/nanolubricant mixture with surfactant to that without
Available online 23 December 2012
surfactant (defined as surfactant impact factor, SIF ) are within 0.85e1.58, 0.73e1.31, and
Keywords:
increase of surfactant concentration and then decrease, and increase with the decrease of
Additive
surfactant molecular weight, nanolubricant concentration and heat flux. A nucleate pool
Nucleate boiling
boiling heat transfer correlation for refrigerant/nanolubricant mixture was proposed, and it
Lubricant
agrees well with the experimental data of refrigerant/nanolubricant mixture with surfac-
Particle
tant and that without surfactant.
0.68e1.24 for SDS, CTAB and Span-80, respectively. The values of SIF increase with the
ª 2012 Elsevier Ltd and IIR. All rights reserved.
Refrigerant
Caracte´ristiques du transfert de chaleur lors de l’e´bullition libre nucle´e´e d’un me´lange frigorige`ne / nanolubrifiant contenant un agent tensio-actif Mots cle´s : additif ; e´bullition nucle´e´e ; lubrifiant ; particule ; frigorige`ne
1.
Introduction
Nanolubricants (i.e., the mixture of nanoparticles and lubricating oil) can be used to improve the energy efficiency of refrigerant system (Wang et al., 2003, 2007; Bi et al., 2008). In the refrigeration system using nanolubricant, the working fluid is refrigerant/nanolubricant mixture. The existence of
lubricating oil is beneficial to the stability of the nanoparticles in the refrigeration cycle (Kedzierski, 2011). However, the nanoparticles in the refrigerant/nanolubricant mixture may aggregate and settle down when the refrigeration system is shutdown for long time. In order to ensure the long-term stability of the refrigerant/nanolubricant mixture in the refrigeration cycle, the aggregation and sedimentation of
* Corresponding author. Tel.: þ86 21 34206378; fax: þ86 21 34206814. E-mail address: [email protected] (G. Ding). 0140-7007/$ e see front matter ª 2012 Elsevier Ltd and IIR. All rights reserved. http://dx.doi.org/10.1016/j.ijrefrig.2012.12.015
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Nomenclature a1, a2 C Cp d d0 h
coefficients in Eq. (7) surfactant concentration isobaric specific heat/J kg1 K1 nanoparticles diameter/nm benchmark nanoparticle size/nm nucleate pool boiling heat transfer coefficient/ W m2 K1 hfg latent heat of vaporization/J kg1 M molecular weight m mass/kg m1, m2, m3 coefficients in Eq. (12) n coefficients in Eq. (12) q heat flux/W m2 SIF surfactant impact factor T temperature/oC nanolubricant concentration xn,o nanoparticles concentration in the mixture yn
nanoparticles should be prevented. Adding the surfactant is a widely used method for preventing the aggregation and sedimentation of nanoparticles in the nanofluid (Hwang et al., 2006; Choi et al., 2008). The addition of surfactant will change the thermophysical properties and then affect the boiling heat transfer characteristics (Wen and Wang, 2002; Chopkar et al., 2008; Kathiravan et al., 2009; Peng et al., 2011a). In order to well design and optimize the heat exchangers in refrigeration systems using refrigerant/nanolubricant, the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant should be investigated to evaluate the effect of surfactant on boiling heat transfer characteristics. The existing researches on the nucleate pool boiling heat transfer characteristics are mainly focused on the refrigerant/ nanolubricant without surfactant (Kedzierski and Gong, 2009; Kedzierski, 2009, 2011; Peng et al., 2010; 2011b). The research results show that, the nanoparticles cause a heat transfer enhancement compared with the heat transfer of refrigerant/ oil mixture (Kedzierski and Gong, 2009; Peng et al., 2010). The influence factors for the heat transfer enhancement of refrigerant/nanolubricant include nanolubricant concentration, nanoparticle concentration, nanoparticle type, nanoparticle size and heat flux (Kedzierski and Gong, 2009; Kedzierski, 2009, 2011; Peng et al., 2010; 2011b). However, the influence of surfactant is not concerned in these researches, and should be investigated. For the prediction correlations of the nucleate pool boiling heat transfer characteristics, the existing researches are mainly focused on the refrigerant/nanolubricant mixture without surfactant (Peng et al., 2010; 2011b; Kedzierski, 2011). A semi-empirical model was developed to predict the boiling enhancement based on the interaction of the nanoparticles with the bubbles (Kedzierski, 2011). Peng et al. (2011b) proposed an improved correlation based on the correlation of Peng et al. (2010), and it can reflect the effect of nanolubricant concentration, host fluid types, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. However, the influence of surfactant is not considered in these correlations.
Greek symbols l thermal conductivity/W m1 K1 m dynamic viscosity/Pa s r density/kg m3 s surface tension/N m1 un nanoparticles concentration in the nanolubricant Subscripts c copper f saturated liquid g saturated vapor n nanoparticles o lubricating oil r refrigerant s surfactant sat saturation w test surface
The purpose of this study is to experimentally investigate the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant, and to develop a correlation for refrigerant/nanolubricant reflecting the influences of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux.
2.
Experimental facility and test conditions
2.1. Preparation and characterization of refrigerant/ nanolubricant mixture with surfactant R113 is chosen as the host refrigerant in the present study, just as Peng et al. (2010) did; and Cu nanoparticles and lubricating oil VG68 are also applied in preparing the refrigerant/nanolubricant mixture. Although R113 is not used any more in the refrigeration and air conditioning industry, we use it in the lab instead of common refrigerants (e.g. R134a and R410A) for the follow reasons: 1) R113 is in liquid state at atmospheric pressure and room temperature, making it is more suitable to produce characteristic-stable refrigerant/nanolubricant mixture for experiments; 2) the difference between R113 and common refrigerants are much less than refrigerants and other common type fluids such as water and oil. The properties of refrigerant R113 are given in Table 1.
Table 1 e Properties of refrigerant R113. Property Chemical formula Molecular mass Normal boiling point Critical temperature Critical pressure
Unit e g mol1 oC oC MPa
Value or format Cl2FCeCClF2 187.37 47.6 214.1 3.39
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Table 2 e Properties of Cu nanoparticles. Property Atomic mass Average particle diameter Density Thermal conductivity Isobaric specific heat
Unit 1
g mol nm kg m3 W m1 K1 J kg1 K1
Value 63.54 20 8920 398 385
Cu nanolubricant is formed by Cu nanoparticles with the average diameter of 20 nm and lubricating oil VG68. Cu nanoparticles are produced by hydrogen direct current arc plasma evaporation method. The properties of Cu nanoparticles are given in Table 2, and the TEM (transmission electron microscope) photographs of Cu nanoparticles are shown in Fig. 1. The lubricating oil VG68 is ester oil with a density of 0.964 g cm3 at 15 C and kinematic viscosities of 66.79 and 8.23 mm2 s1 at 40 C and 100 C, respectively, as reported by the manufacturer. In the present study, one anionic surfactant (SDS), one cationic surfactant (CTAB) and one nonionic surfactant (Span80) are used. The physical and chemical properties of these three surfactants are listed in Table 3. R113/Cu nanolubricant mixture with surfactant is prepared by the following steps: 1) weighing the required mass of Cu nanoparticles and surfactants by a digital electronic balance with a measurement range of 10 mge210 g and a maximum error of 0.1 mg; 2) putting the Cu nanoparticles into the weighed lubricating oil VG68 to form a Cu nanolubricant; 3) putting the Cu nanolubricant into the weighed R113 to form a R113/Cu nanolubricant; 4) putting the surfactants into the R113/Cu nanolubricant to form the R113/Cu nanolubricant mixture with surfactant; 5) vibrating the R113/Cu nanolubricant mixture with surfactant by an ultrasonic processor for 1 h to disperse the nanoparticles evenly. Experimental observation shows that the stable dispersion of Cu nanoparticles in the R113/Cu nanolubricant mixture with surfactant can be kept for more than 24 h. The duration of the experiment for each sample of R113/Cu nanolubricant mixture with surfactant is less than 4 h which is shorter than 24 h,
Table 3 e Properties of the surfactants used in the experiments. Surfactant name
SDS
CTAB
Span-80
Chemical formula Ionic nature Form
C12H25SO4Na Anionic White powder
C19H42NBr Cationic White powder
Molecular weight HLB value
288.3 40
364.5 15.8
C24H44O6 Nonionic Pale yellow oily liquid 428.6 4.3
so the prepared R113/Cu nanolubricant mixture with surfactant can maintain good uniformity in the experiment. In order to quantitatively describe the composition of refrigerant/nanolubricant mixture with surfactant, the following concentrations are defined. 1) Surfactant concentration (C ), which is the ratio of the mass of surfactant to the mass of refrigerant/nanolubricant mixture with surfactant, presented as Eq. (1): C¼
ms mn;o þ mr þ ms
(1)
where, ms, mn,o and mr are the mass of surfactant, nanolubricant and refrigerant, respectively. 2) Nanolubricant concentration (xn,o), which is the ratio of the mass of nanolubricant to the mass of refrigerant/nanolubricant mixture with surfactant, presented as Eq. (2): xn;o ¼
mn;o mn;o þ mr þ ms
(2)
3) Nanoparticles concentration in nanolubricant (un), which is the ratio of the mass of nanoparticles to the mass of nanolubricant, presented as Eq. (3): un ¼
mn mn þ mo
(3)
where, mn and mo are the mass of nanoparticles and lubricating oil, respectively. 4) Nanoparticles concentration in the refrigerant/nanolubricant mixture ( yn), which is the ratio of the mass of nanoparticles to the mass of refrigerant/nanolubricant mixture, presented as Eq. (4): yn ¼
mn mn;o þ mr
(4)
In the experiments for each type of surfactant, C is from 200 to 10,000 ppm, xn,o is from 1 to 5 wt%, un is 20 wt%, and yn is from 0.2% to 1%.
2.2.
Fig. 1 e TEM photographs of Cu nanoparticles.
Experimental facility and test conditions
The experimental facility used for testing the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture with surfactant is composed of a test
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Fig. 2 e Schematic diagram of experimental facility.
section, a boiling apparatus and a condensation loop, as schematically shown in Fig. 2. The test section is fabricated by a copper block. The top horizontal surface of the copper block is circular with a diameter of 20.0 mm, and flat with an average roughness (Ra) of 1.6 mm. This surface is used as the test surface for pool boiling heat transfer experiments. Five calibrated K-type thermocouples with a precision of 0.1 C are inserted into five 1.0 mm diameter holes in the top part of the copper block in order to obtain the temperature gradient of the test surface accurately, and then to determine the heat flux and the test surface temperature. The liquid temperature is measured by a calibrated K-type thermocouple with a precision of 0.1 C, and the pressure inside the boiling chamber is measured by a pressure transducer with a precision of 0.1 kPa. The heat flux through the test surface is controlled
by adjusting the heating power of the cartridge heater. The saturation pressure is controlled by two methods: 1) adjusting the heating power of the electrical heating wire; 2) adjusting the mass flow rate of the cool water by controlling the opening of the valve in the condensation loop. The principle and operation procedure of the experimental facility were introduced in detail in Peng et al. (2010). Test conditions are tabulated in Table 4. Total 456 experimental data are recorded, including 432 experimental data of R113/Cu nanolubricant mixtures with three different types of surfactants (i.e., SDS, CTAB and Span-80) and 24 experimental data of R113/Cu nanolubricant mixtures without surfactant as baseline. All signals of temperature and pressure are collected by a data acquisition system and transmitted to a computer after the system reaches a steady state.
Table 4 e Test conditions. Test fluid
R113/Cu/VG68/SDS, R113/Cu/VG68/CTAB, R113/Cu/VG68/Span-80
Heat flux (kW m2)
Saturation pressure (kPa)
10, 20, 30, 40, 50, 60, 70, 80
101.3
Nanolubricant Nanoparticles concentration in concentration xn,o (wt %) nanolubricant (un) 20
1, 3, 5
Surfactant concentration C (ppm)
No. of experimental data
0, 200, 500, 1000, 2000, 5000, 10,000
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2.3.
Data reduction and uncertainties
The nucleate pool boiling heat transfer coefficient, h, is calculated as: h ¼ q=ðTw Tsat Þ
(5)
where, q is the heat flux, Tw is the test surface temperature, and Tsat is the saturated liquid temperature. For pure R113, the saturated liquid temperature, Tsat, is 47.6 C at the saturated pressure of 101.3 kPa. For refrigerant/ nanolubricant mixture with surfactants, the saturated liquid temperature, Tsat, changes with the variations of the composition, and is measured by the K-Type thermocouple. The measured value of the saturated liquid temperature can reflect its change with the variations of the compositions of refrigerant/nanolubricant mixture with surfactant. The heat flux, q, is calculated by Eqs. (6) and (7) based on the one-dimensional heat conduction equation: dT dz w
(6)
T ¼ a1 þ a2 z
(7)
q ¼ lc
where, lc is the copper thermal conductivity, z is the coordinate perpendicular to the test surface, a1 and a2 are constants correlated based on the measured five temperatures on the copper block. The test surface temperature, Tw, is calculated as: Tw ¼ ða1 þ a2 zÞjz¼0 ¼ a1
(8)
The relative uncertainties of heat flux and nucleate pool boiling heat transfer coefficient are estimated to be smaller than 8.9% and 9.2%, respectively. Tests under several conditions were repeated for three times, and the differences among the three testing results under each condition are less than 5%.
3.
Experimental results and discussion
3.1. Nucleate pool boiling heat transfer coefficients of refrigerant/nanolubricant mixture with surfactant The nucleate pool boiling heat transfer coefficients of R113/Cu nanolubricant mixtures with three types of surfactants (i.e., SDS, CTAB and Span-80) are shown in Fig. 3 (a)e(c), respectively. For each type of surfactant, experimental conditions cover three nanolubricant concentrations (xn,o), i.e., 1 wt%, 3 wt% and 5 wt %. Fig. 3 (a) shows the experimental data of the mixture with anionic surfactant (SDS). It can be seen that at nanolubricant concentration (xn,o) of 1 wt%, the presence of SDS enhances the nucleate pool boiling heat transfer characteristics for all SDS concentrations, and the maximum enhancement occurs at the SDS concentration (CSDS) of 2000 ppm. At xn,o of 3 wt% and 5 wt%, the presence of SDS enhances the nucleate pool boiling heat transfer under the experimental conditions except at CSDS of 10,000 ppm, and the maximum enhancements occur at CSDS of 5000 ppm. Fig. 3 (b) shows the experimental data of the mixture with cationic surfactant (CTAB). It can be seen that at each
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nanolubricant concentration (xn,o), the presence of CTAB enhances the nucleate pool boiling heat transfer characteristics under the experimental conditions except at the CTAB concentration (CCTAB) of 10,000 ppm. The maximum enhancements occur at CCTAB of 500 ppm, 1000 ppm and 2000 ppm when the values of xn,o are 1 wt%, 3 wt% and 5 wt%, respectively. Fig. 3 (c) shows the experimental data of the mixture with nonionic surfactant (Span-80). It can be seen that at each nanolubricant concentration (xn,o), the presence of Span-80 enhances the nucleate pool boiling heat transfer characteristics under the experimental conditions except at the Span-80 concentration (CSpan-80) of 10,000 ppm. The maximum enhancements occur at CSpan-80 of 1000 ppm, 2000 ppm and 5000 ppm when the values of xn,o are 1 wt%, 3 wt% and 5 wt%, respectively. From the experimental results, it can be concluded that the surfactant concentration, surfactant type, nanolubricant concentration and heat flux have influences on the nucleate pool boiling heat transfer characteristics of refrigerant/nanolubricant mixture. The influences will be quantitatively analyzed in the following sections.
3.2. Influence of surfactant concentration on the nucleate pool boiling heat transfer characteristics Surfactant impact factor, SIF, is defined to quantify and analyze the surfactant influence on the nucleate pool boiling heat transfer characteristics of refrigerant-nanolubricant mixture with surfactant, presented as Eq. (9): SIF ¼ hr;n;o;s =hr;n;o
(9)
where, hr,n,o,s and hr,n,o are the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant and that of refrigerant/nanolubricant mixture without surfactant, respectively. Fig. 4 (a)e(c) show the influences of surfactant concentration on the nucleate pool boiling heat transfer characteristics for SDS, CTAB and Span-80, respectively. It can be seen that SIF for SDS, CTAB and Span-80 are in the ranges of 0.85e1.58, 0.73e1.31 and 0.68e1.24, respectively. The values of SIF are higher than 1.0 when the surfactant concentration is smaller than or equal to 5000 ppm. With the increase of surfactant concentration, SIF initially increases and reaches the maximum value, and then decreases with further increase of surfactant concentration. At high surfactant concentration (e.g., 10,000 ppm), the values of SIF are lower than 1.0. This phenomenon is caused by the conjunct role of enhancement factors and deterioration factors. The enhancement factors include: 1) the surfactant decreases the mixture surface tension (Wu et al., 1995), and then decreases the bubble departure diameter and increases the bubble departure frequency; 2) the surfactant increases the active nucleation sites (Kedzieski, 1999); 3) the surfactant may aggregate and serve as boiling nuclei (Zhang, 2004), causing the secondary nucleation on the bubble. The deterioration factors include: 1) the surfactant increases the viscosity, and then suppresses the micro-convection near heating surface (Zhang, 2004); 2) the surfactant weakens the interaction between nanoparticles and heating surface. At low surfactant concentration, the enhancement factors dominate; while at high surfactant concentration, the deterioration factors dominate.
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Fig. 3 e Nucleate pool boiling heat transfer coefficients of R113/Cu nanolubricant mixtures with three types of surfactants: (a) SDS; (b) CTAB; (c) Span-80.
i n t e r n a t i o n a l j o u r n a l o f r e f r i g e r a t i o n 3 6 ( 2 0 1 3 ) 1 0 4 5 e1 0 5 5
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Fig. 4 e Surfactant impact factor (SIF ) for three types of surfactants: (a) SDS; (b) CTAB; (c) Span-80.
Therefore, SIF increases with the increase of surfactant concentration, and then decreases. It can also be seen from Fig. 4 that, the optimal surfactant concentrations corresponding to the maximal SIF are different for different surfactant types and lubricant concentrations.
For surfactant SDS, the optimal surfactant concentrations are 2000 ppm, 5000 ppm and 5000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. For surfactant CTAB, the optimal surfactant concentrations are 500 ppm, 1000 ppm and 2000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. For surfactant
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Span 80, the optimal surfactant concentrations are 1000 ppm, 2000 ppm and 5000 ppm at xn,o of 1 wt%, 3 wt% and 5 wt%, respectively. The possible reason for this phenomenon is as follows. With the increase of nanolubricant concentration, the surfactant aggregation is suppressed, and then more surfactant is needed to form the large surfactant particles serving as boiling nuclei. Therefore, the optimal surfactant concentration increases with the increase of nanolubricant concentration. For the refrigerant-based nanofluid (xn,o ¼ 0), the aggregation of the surfactant is not influenced by the change of nanolubricant concentration, so the optimal surfactant concentration is a constant value for a fixed type of surfactant (Peng et al., 2011a).
3.3. Influence of surfactant type on the nucleate pool boiling heat transfer characteristics Fig. 5 shows the influence of surfactant type on the nucleate pool boiling heat transfer characteristics. It can be seen that the values of SIF are in the order of SDS > CTAB > Span-80 at one certain surfactant concentration (C ) and nanolubricant concentration (xn,o), which is opposite to the order of the molecular weight values for SDS (M ¼ 288.3), CTAB (M ¼ 364.5) and Span-80 (M ¼ 428.6). The possible reason for this phenomenon is as follows. With the decrease of molecular weight, the diffusion velocities of surfactant molecules increase, and the accumulation of surfactant on the growing bubble surface is intensified, resulting in more obvious influences of surfactant on the surface tension and the heat transfer characteristics. Therefore, SIF increases with the decrease of molecular weight value.
3.4. Influence of nanolubricant concentration on the nucleate pool boiling heat transfer characteristics Fig. 6 shows the influence of nanolubricant concentration on the nucleate pool boiling heat transfer characteristics. It can be seen that SIF increases with the decrease of nanolubricant concentration (xn,o). On the condition of C ¼ 500 ppm, the value of SIF for SDS increases maximally by 22.2% with the decrease of xn,o from 5 wt% to 1 wt%. The possible reasons for this
Fig. 5 e Influence of surfactant type on SIF.
Fig. 6 e Influence of nanolubricant on SIF.
phenomenon are as follows. The decrease of nanolubricant concentration leads to the decrease of the mixture viscosity and the increase of the diffusion velocities of surfactant molecules, resulting in more surfactant molecules accumulating on the growing bubble surface and surface tension decreasing rapidly. With the decrease of surface tension, the enhancement of nucleate pool boiling becomes larger, and then SIF increases with the decrease of nanolubricant concentration. Fig. 7 shows the comparison of SIF for refrigerant/nanolubricant mixture with that for refrigerant-based nanofluid (Peng et al., 2011a). The comparison results show that, the values of SIF for refrigerant/nanolubricant mixture and refrigerant-based nanofluid are in the ranges of 1.01e1.11, and 1.07e1.19, respectively. The values of SIF for refrigerant/ nanolubricant mixture are smaller than those for refrigerantbased nanofluids (xn,o ¼ 0). It is in accordance with the regularity that SIF increases with the decrease of nanolubricant concentration (xn,o).
Fig. 7 e Comparison of SIF for refrigerant/nanolubricant mixture with that for refrigerant-based nanofluid.
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3.5. Influence of heat flux on the nucleate pool boiling heat transfer characteristics From Fig. 7, it can also be seen that the value of SIF increases with the decrease of heat flux (q). With the decrease of q from 80 kW m2 to 10 kW m2, the values of SIF for SDS, CTAB and Span-80 increases by 7.4%, 5.5% and 4.3%, respectively. The possible reason for the increase of SIF with the decrease of heat flux is as follows. At high heat flux, the bubble departure
hr;n;o ¼
are suitable for both the refrigerant/nanolubricant mixture with surfactant and that without surfactant. The new correlation is proposed at the form of the product of the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture without surfactant (hr,n,o) and the surfactant impact factor (SIF ), as shown in Eq. (10). hr;n;o;s ¼ SIF,hr;n;o
(10)
q "
1:3068 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi#0:33 Cp;r;n;o;f mr;n;o;f hfg dn q sr;n;o
0:0093 þ 0:00356 0:0048un þ 0:0025xn;o Cp;r;n;o;f d0 lr;n;o;f mr;n;o;f hfg g r r r;n;o;f
frequency increases, weakening the accumulation of surfactant on the growing bubble surface, thus the influence of surfactant on the surface tension becomes weaker and SIF increases with the decrease of heat flux.
4. A nucleate pool boiling heat transfer correlation for refrigerant/nanolubricant mixture According to the above analysis and the existing research results (Kedzierski and Gong, 2009; Kedzierski, 2011, 2009; Peng et al., 2010; 2011b), the conclusion can be deduced that, the influencing factors for nucleate pool boiling heat transfer characteristics of refrigerant/lubricant mixture with surfactant include surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. Therefore, in order to develop a correlation of the nucleate pool boiling heat transfer coefficient for refrigerant/nanolubricant mixture, the above influencing factors should be reflected in the correlation. Peng et al. (2011b) correlation is one existing nucleate pool boiling heat transfer coefficient correlation for refrigerant/ nanolubricant mixture, and it reflects the effect of nanolubricant concentration, host fluid types, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. One effective method for developing a general correlation is to introduce the surfactant impact factor (SIF ) in Peng et al. (2011b) correlation. SIF should be expressed as the function of surfactant concentration, molecular weight of surfactant, nanolubricant concentration and heat flux. Furthermore, when the surfactant concentration is equal to zero, the value of SIF should be equal to 1, making sure that the correlations
( qexp ð1395C þ 14CÞ 2
hr;n;o;s ¼
(11)
r;g
where, Cp,r,n,o,f, mr,n,o,f, and lr,n,o,f are the isobaric specific heat, the dynamic viscosity and the thermal conductivity of liquid refrigerant/nanolubricant mixture, respectively; sr,n,o is the surface tension of refrigerant/nanolubricant mixture; rr,g and rr,n,o,f are the densities of vapor refrigerant and liquid refrigerant/nanolubricant mixture, respectively; hfg is the latent heat of vaporization; dn is the nanoparticle diameter; d0 is the benchmark nanoparticle size (the value is 100 nm); un is the nanoparticle concentration in the nanolubricant. The properties of refrigerant/nanolubricant mixture can be calculated with the models presented in Appendix. The key for development of the new correlation is to determine the SIF in Eq. (10). The SIF is expressed as Eq. (12). SIF ¼ exp m1 C2 þ m2 C
m3 ðqMxn;o Þn
(12)
The four coefficients m1, m2, m3 and n in Eq. (12) are fitted based on experimental data of R113/Cu nanolubricant mixtures with three different types of surfactants (i.e., SDS, CTAB and Span-80) in this study, covering the surfactant concentrations from 200 to 10,000 ppm, and the nanolubricant concentrations from 1 to 5 wt%. By nonlinear programming solution method, the four coefficients of m1, m2, m3 and n can be determined as 1395, 14, 2400 and 0.48, respectively. Therefore, Eq. (12) for calculating SIF becomes Eq. (13). ( SIF ¼ exp
1395C2 þ 14C
2400
)
ðqMxn;o Þ0:48
(13)
Based on Eqs. (10), (11) and (13), the new correlation for predicting the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant is expressed as Eq. (14).
2400
)
ðqMxn;o Þ0:48 "
1:3068 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi#0:33 Cp;r;n;o;f mr;n;o;f hfg dn q sr;n;o
0:0093 þ 0:00356 0:0048un þ 0:0025xn;o Cp;r;n;o;f d0 lr;n;o;f mr;n;o;f hfg g r r r;n;o;f
r;g
(14)
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for other kinds of refrigerant/nanolubricant mixtures with or without surfactants.
5.
Fig. 8 e Comparison of the predicted values of the new correlation with the experimental data of refrigerant/ nanolubricant mixture with surfactant and that without surfactant.
Fig. 8 shows the comparison of the predicted values of the new correlation with the experimental data of R113/Cu nanolubricant mixture with surfactant obtained in the present study and the experimental data of refrigerant/nanolubricant mixture without surfactant (Kedzierski and Gong, 2009; Peng et al., 2010; 2011b). It can be seen that the predicted values can agree with 91% of the experimental data of refrigerant/nanolubricant mixture with surfactant within a deviation of 25%; the predicted values can agree with 95% of the experimental data of R134a/nanolubricant mixture (Kedzierski and Gong, 2009) and R113/nanolubricant mixture (Peng et al., 2010, 2011b) within the deviation of 25%. The new correlation considers the influencing factors of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux, and is verified to have good predictions to refrigerant/nanolubricant mixture with surfactant and that without surfactant. The ranges of applicability for the new correlation are as follows: the surfactant types of SDS, CTAB and Span-80, surfactant concentrations from 0 to 10,000 ppm, nanolubricant concentrations from 1 wt% to 5 wt%, nanoparticle concentrations from 0.1 wt % to 1 wt%, nanoparticle sizes from 20 nm to 80 nm, heat fluxes from 10 to 120 kW m2. More verifications are needed in the future in order to ensure the accuracy of this correlation
Property Specific heat (J kg
Conclusions
(1) The presence of SDS, CTAB and Span-80 enhances the nucleate pool boiling heat transfer of R113/Cu nanolubricant on most conditions except at high surfactant concentrations. The ratio of nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture with surfactant to that without surfactant, SIF, are in the ranges of 0.85e1.58, 0.73e1.31, and 0.68e1.24 for SDS, CTAB and Span-80, respectively. With the increase of surfactant concentration, SIF increases and reaches the maximum value, and then decreases. (2) The values of SIF are in the order of SDS > CTAB > Span-80 at one certain surfactant concentration and nanolubricant concentration, which is opposite to the order of the molecular weight values for SDS, CTAB and Span-80. (3) SIF increases with the decrease of nanolubricant concentration, and the optimal surfactant concentration corresponding to the maximal SIF increases with the increase of nanolubricant concentration. (4) For one certain surfactant concentration, nanolubricant concentration and surfactant type, SIF increases with the decrease of heat flux. (5) A correlation for predicting the nucleate pool boiling heat transfer coefficient of refrigerant/nanolubricant mixture is proposed, and it can reflect the influences of surfactant type, surfactant concentration, nanolubricant concentration, host fluid type, nanoparticle type, nanoparticle size, nanoparticle concentration and heat flux. The new correlation agrees well with the experimental data of refrigerant/nanolubricant mixture with surfactant and that without surfactant.
Acknowledgments The authors gratefully acknowledge the support from the National Natural Science Foundation of China (Grant No. 50976065).
Appendix. Calculation of the properties of refrigerant/nanolubricant mixture
Model for calculating property 1
1
K )
Viscosity (Pa s)
Thermal conductivity (W m1 K1)
Cp,r,n,o,f ¼ (1 xn,o)Cp,r,f þ xn,oCp,n,o Cp,n,o ¼ (1 fn)Cp,o þ fnCp,n mr;n;o;f ¼ eðxn;o lnmn;o þð1xn;o Þlnmr;f Þ 1 mn;o ¼ mo ð1 fn Þ2:5 lr,n,o,f ¼ lr,f(1 xn,o) þ ln,oxn,o0.72xn,o(1 xn,o)(ln,o lr,f) ln þ 2lo 2fn ðlo ln Þ ln;o ¼ lo ln þ 2lo þ fn ðlo ln Þ
Author Jensen and Jackman (1984) Pak and Cho (1998) Kedzierski and Kaul (1993) Brinkman (1952) Baustian et al. (1988)
Hamilton and Crosser (1962)
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(continued ) Property Surface tension (N m1) Density (kg m3) Volume fraction of nanoparticles in the nanolubricant
Model for calculating property 0:5 sr;n;o ¼ sr þ ðsn;o sr Þxn;o !1 sn,o ¼ so xn;o 1 xn;o rr;n;o;f ¼ þ rn,o¼(1 fn) rn;o rr;f ro þ fnrn un ro fn ¼ un ro þ ð1 un Þrn
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