Thermophysical characteristics of ZnO nanofluid in L-shape enclosure. Introduction Bin Wang, version 6, 05/25/2015 Conventional heat transfer fluids, such as water, ethylene glycol and engine oil, have limited capabilities of thermal cooling. In order to find new effective heat transfer fluid, nanofluids appear to be a very interesting alternative for advanced thermal applications [1]. The first experimental works regarding nanofluids [2-5] and numerous theoretical works [6-8] has been proposed. There are many experimental works regarding ZnO nanofluid [9-14]. Many researches [9-11] reported that the thermal conductivity of ethylene glycol based ZnO nanofluid increase as volume fraction and temperature growth. While the viscosity increases as volume fraction increases and it decreases as temperature increases. Suganthi, et al. [12] measured the zeta electric potential and viscosity at different temperature on ZnO-water nanofluid. Hong J, et al. [13] has shown that different nano-particle diameters influence the thermal conductivity. Zhang et al. [14] found that ZnO nanofluids have prospective application in antibacterial field. Recently, Majid Saidi [15] has shown different shapes of copper-water nanofluid. Yang et al. [16-17] using entropy generation minimize nanofluid flow in microchannels. In this work, we examine the influence of the volume fraction of ZnO nanoparticles and Rayleigh number in L-shape enclosure filled with ZnO-water nanofluid. The results of the present study can be used as a guideline for the electronic cooling systems optimizing. Governing equations The system schematics of L-shape enclosure (Fig.1) governed by mass, momentum, and energy equation (1-5) u v w ( ) (2) (1) u v w ( ) ( ) ( ) (3) u v w ( ) (4) u v w ( ) (5) Where the effective density, thermal diffusivity and dynamic viscosity of the nanofluid are defined as follows: ( ), (6) ( ), (7) ( ), (8) 1
The heat capacitance and thermal expansion coefficient of the nanofluid are given by: ( ) ( )( ) ( ), (9) ( ) ( )( ) ( ), (10) The nanofluid thermal conductivity can be calculated by Maxwell equation [6] ( ) ( ) ( ) ( ) where f=fluid, s=solid, nf= nanofluid, =volume fraction of nanofluid. Equations (1-5) can be converted to dimensionless forms, and using the following non-dimensional parameters, respectively: (11) (12) ( ) ( ) ( ) (13) ( )( ) (14) ( ) (15) X L, Y L Z L, L, L L 0 G G ( 0 )L,,. The local Nusselt number can be expressed as u h Heat transfer coefficient and thermal conductivity are calculated from the following equations, h h (16) (17), on the vertical walls. (18), on the horizontal walls. (19) By substituting above three Eqs. (17-19) into Eq. (16), the local Nusselt number can be written as u ( ) on the vertical walls. (20) u ( ) on the horizontal walls. (21) *Here we report heat transfer enhancement by using ZnO nanofuid in L-shape natural convection flow. The boundary conditions show in Fig.1 as follows: Non-slip condition is imposed for all velocities on the walls; thermal boundary 2
conditions are for the hot walls, for the cold walls and for the adiabatic walls. By applying the dimensionless parameters, the following boundary conditions are obtained. U=V=0, =1, on the hot walls. U=V=0, =0, on the cold walls. U=V=0, =0, on the hot walls, where n is normal direction to the walls. Numerical approach To solve such problems requires combination of the continuity, momentum, and energy equations simultaneous. In this work, the numerical techniques are based on finite element method to discretize the governing equations. The pressure and velocity fields in the momentum equation used SIMPLER algorithm and successive over under relaxation method is used to solving the equations. The convective and diffusive terms are approximated by second order upwind and central differential schemes, respectively. The convergence criterion in this study is based on a tolerance function less than. Results and discussion Fig.1 System schematics In order to investigate the heat transfer performance of L-shape enclosures regarding ZnO-water nanofluid, the temperature, velocity and Nusselt number profiles are obtained. The effects of volume fraction of ZnO nanoparticles in the nanofluid and Rayleigh number on the heat transfer rate are examined. The Rayleigh number (Ra) and the nanoparticles volume fraction ( ) of the nanofluid are ranging from 1e3 to 1e6, and 0.2 to 0.4, respectively. The results are presented in the following sections. * The effect of Ra, and on free convection. *Fig.2 The isotherms profile of the effect of parameter and Ra in the nanofluid. 3
The isothermal profiles of L-shape enclosures regarding the nanofluid follow with the Ra and (Fig.2). At low Rayleigh number, such as 1e3 and 1e4, the isothermal are parallel. While as Rayleigh number increased, the isotherms are changed. At high Rayleigh numbers, the heat transfer mechanism of the nanofluid shift from conduction to free convection. *Fig.3 The velocity profiles of the effect of parameter and Ra in the nanofluid. The velocity profiles of L-shape enclosures regarding the nanofluid follow with the Ra and (Fig.3). The heated fluid moves to the cold wall and eddy is created. At low Rayleigh numbers, the flow in the horizontal section of the enclosure is nearly stagnant. At high Rayleigh numbers, the number of eddies formed is increase and the flow circulation is augmented. According to Eq. (6) and Eq. (8), the addition of nanoparticles influences the velocity and temperature profiles by increasing viscosity and effective thermal conductivity of fluid. Examination of Fig.3 indicated that as increases, the maximum velocity decreases due to increased density and the viscosity of the nanofluid. Even though increases with, the effect of buoyancy decreased. At a fixed Ra, because of the decrease in vertical velocity with decrease in, the strength of circulation reduces. On the other hand, at a constant (the same viscosity and density), the strength of circulation enhances as Ra increases. A similar trend is reported by Majid [15] for isotherm and velocity profile at different and Ra. *Fig.4 The local heat transfer coefficient profiles of the effect of parameter and Ra in the nanofluid. The local heat transfer coefficients in L-shape enclosure regarding the nanofluid parameterized by Ra and are presented (Fig.4). For all range of the Rayleigh number, the heat transfer coefficient will be increased by increasing. At a fixed, the maximum heat transfer coefficient at low Rayleigh numbers is more than those of high Rayleigh numbers. For example, at =0.6, the maximum heat transfer coefficient for Ra= 1e3, 1e4, 1e5 and 1e6 are 6733.8, 3067.4, 1045.2, 1043.6 respectively. The difference of heat transfer coefficient become negligible at higher Ra numbers (e.g. between Ra= 1e5 and 1e6). Conclusion In conclusion, the effect of parameters volume fraction of nanoparticles ( ), and Rayleigh number ( ) on heat transfer rate in L-shape enclosure with ZnO-water nanofluid has been studied. The additions of ZnO nanoparticles in water enhance heat transfer coefficient. At low Ra, the dominant heat transfer mechanism in L-shape enclosure is conduction. However, at high Ra, the dominant heat transfer mechanism for that is free convection. On the other hand, we find that decrease Ra and increase can enhance the heat transfer coefficient in these systems. * References [1]. Lee, S., Choi, S.U.S., 1996. Application of metallic nanoparticle suspensions in 4
advanced cooling systems. ASME Publications PVP-vol. 342/MD-vol. 72, pp. 227 234. [2]. Masuda, H., Ebata, A., Teramae, K., Hishinuma, N., 1993. Alteration of thermal conductivity and viscosity of liquid by dispersing ultrafine particles (dispersion of c-al2o3, SiO2 and TiO2 ultra-fine particles). Netsu Bussei (in Japanese) 4 (4), 227 233. [3]. Choi, S.U.-S., 1995. Enhancing thermal conductivity of fluids with nanoparticles. ASME Publications FED-vol. 231/MD-vol. 66, pp.99 105. [4]. Pak, B.C., Cho, Y.I., 1998. Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particles. Experiment. Heat Transfer 11 (2), 151 170. [5]. Xuan, Y., Li, Q., 2000. Heat transfer enhancement of nanofluids. Int. J. Heat Fluid Flow 21, 58 64. [6]. Maxwell, J.C., 1904. A Treatise on Electricity and Magnetism, seconded. Oxford University Press, Cambridge, pp. 435 441. [7]. Jeffrey, D.J., 1973. Conduction through a random suspension of spheres. Proc. R. Soc. Lond., Series A 335, 355 367 [8]. Gupte, S.K., Advani, S.G., Huq, P., 1995. Role of micro-convection due to non-affine motion of particles in a mono-disperse suspension. Int. J. Heat Mass Transfer 38 (16), 2945 2958. [9]. Rosari Saleh, Nandy Putra, Suhendro Purbo Prakoso., et al. Experimental investigation of thermal conductivity and heat pipe thermal performance of ZnO nanofluids. Int. J. Therm. Sci. 2013,63: 125-132 [10]. Lee G J, Lee M K, J, Rhee C K., et al. Thermal conductivity enhancement of ZnO nanofluid using a one-step physical method. Thermochim. Acta. 2012, 542: 24-27 [11]. Yu W, Xie H Q, Chen L F.,et al. Investigation of thermal conductivity and viscosity of ethylene glycol based ZnO nanofluid. Thermochim. Acta. 2009,491: 92-96 [12]. Suganthi K S, Raj an K S. Effect of Calcination Temperature on the Transport Properties and Colloidal Stability of ZnO-Water Nanofluids. Asian J.Sci. Res. 2012, 5: 207-2173033 [13]. Hong J, Kim S H, Kim D. Effect of laser irradiation on thermal conductivity of ZnO nanofluids. J.Phys. 2007, 59: 301-304 [14]. Zhang L L, Ding Y L. ZnO nanofluids - A potential antibacterial agent. Prog. Nat. Sci.2008,18: 939-944 [15]. Majid Saidi, Gholamreza Karimi, Free convection cooling in modified L-shape enclosures using copper-water nanofluid, Energy 70 (2014) 251-271 [16]. Yue-Tzu Yang, Yi-Hsien Wang, & Bo-Ying Huang, Numerical Optimization for Nanofluid Flow in Microchannels Using Entropy Generation Minimization, Numerical Heat Transfer, Part A, 67: 571 588, 2015 5
[17]. M. Habibi Matin, R. Hosseini, M. Simiari, P. Jahangiri, Entropy generation minimization of nanofluid flow in a MHD channel considering thermal radiation effect Mechanika. 2013 Volume 19(4): 445-450 Acknowledgments This work is supported in part by the Institute for Complex Adaptive Matter, University of California, Davis, under Grant ICAMUCD 13-08291. Appendix *Fig.2 The isotherms profile of the effect of parameter (a) =0 and Ra in the nanofluid. (b) =0.03 (c) =0.06 6
(d) =0.1 *Fig.3 The velocity profiles of the effect of parameter (a) =0 and Ra in the nanofluid. 7
(b) =0.03 (c) =0.06 (d) =0.1 8
*Fig.4 The local heat transfer coefficient profiles of the effect of parameter Ra (a) =0 and (b) =0.03 (c) =0.06 (d) =0.1 9
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