Proceedings of the ASME-JSME-KSME Joint Fluids Engineering Conference 2015 AJK2015-FED

July 26-31, 2015, SEOUL, KOREA

AJK2015-25816

HEAT TRANSFER AND PRESSURE DROP TEST OF ALUMINA NANOFLUID IN NANO ROD BUNDLE FOR FUSION-FISSION HYBRID SYSTEM

Jubair A. Shamim Department of Nuclear Engineering

Seoul National University Seoul 151-744, Republic of Korea.

Palash K. Bhowmik Department of Nuclear Engineering

Seoul National University Seoul 151-744, Republic of Korea.

Kune Y. Suh* Department of Nuclear Engineering

Seoul National University Seoul 151-744, Republic of Korea.

ABSTRACT Experiments were performed in the so-called NANO

(Numerics Applied Nanofluid Operation) rod bundle using pure water and different volume concentrations of alumina nanofluid as coolant to investigate rate of convective heat transfer and the effects of grid spacer on flow restriction under fully developed single phase turbulent flow condition. The pressurized water reactor (PWR) conditions were considered while designing the NANO test loop using a total of nine cartridge type heater rods installed in a 33 square array fashion. The Nusselt numbers and convective heat transfer co-efficient for a wide range of flow inlet velocity and input power were obtained and compared against the well-known correlations available in the literature. By experimentation it was revealed that inclusion of very tiny amount (e.g. 0.01 vol.% and 0.025 vol.%) of alumina nanoparticles is capable to boost the convective heat transfer coefficient over 25% compared to pure water without significant compensation of pumping power required. The experimental pressure drop while pure water was used as coolant fall within 5-18% of theoretical predictions depending on the inlet Reynolds number. Finally, constant coefficients of well-known Dittus-Boelter correlation were modified for this NANO specific rod bundle to approximate the heat transfer performance more precisely.

INTRODUCTION In the recent era, nanofluid has gained much attention as a

promising coolant for PWR rod bundle due to its enhanced thermal capabilities with insignificant rise in pressure drop. While most conventional designs to elevate heat transfer performance are limited to only variation of mechanical structures, such as addition of heat surface area (fins), vibration of heated surface, injection or suction of fluids, applying electrical or magnetic fields etc., application of these

techniques in a nuclear fuel rod assembly will require not only designing complex core geometries but also elevate the manufacturing cost as well as may jeopardize essential safety features accompanied by reduced lifetime of reactor pressure vessel. Hence, nanofluid coolant with its tiny particle size, relatively large surface area and small volume fraction can be an outstanding alternatives for PWR coolants.

Several mechanisms have been proposed until now to elucidate the thermal conductivity enhancement of nanofluids where it has been shown that thermal conductivity of nanofluid is affected by multifarious parameters like temperature, particle size, PH value etc. Most of these models can be categorized either as static or dynamic model [1]. While static models presume that nanoparticles are stationary in the base fluid and thus forms a composite material, dynamic models portray that nanoparticles are in constant random motion in the base fluid (termed as Brownian motion) which is the key reason of elevated thermal properties of nanofluid. The interpretation of this Brownian motion is shown in Fig.1.

FIGURE 1. INTERPRETATION OF BROWNIAN MOTION [2].

Keblinski et al. [3] proposed four possible ways of heat transfer enhancement mechanism by nanofluids one of which was Brownian motion. Nevertheless, they concluded that since a particle may travel across a larger distance over many different paths to reach a final destination that may be very short from the starting point, Brownian motion can not be the pivotal factor to ameliorate heat transfer, no matter how agitated or energetic they may be.

Later Jang and Choi [4] developed a model that takes into account convective heat transfer induced by Brownian motion of nanoparticles. The four modes of energy transport in nanofluid introduced by them are as follows:

a) Collision between base fluid molecules b) Thermal diffusion in nanoparticles in base fluid c) Collision between nanoparticles due to Brownian

motion d) Thermal interaction of dynamic nanoparticles with

base fluid molecules. The thermal conductivity of their model is given by Eq.

(1) as follows:

(1) where, keff is the effective thermal conductivity of

nanofluid, kbf is the base fluid conductivity, is the volume fraction, knano is the thermal conductivity of nanoparticles, C1 is an empirical constant, dbf is the diameter of the base fluid molecule and dnano is the diameter of nanoparticle [5]. Rednano is the Reynolds number defined by Eq. (2):

(2)

where, is the dynamic viscosity of the base fluid, and

CR.M. is the random motion velocity of nanoparticles defined by Eq. (3):

(3)

where, IBf is the mean-free path of a base fluid molecule. D0 is the nanoparticle diffusion coefficient given by Eq. (4):

(4)

where, is the viscosity of the base fluid, T is the temperature of the base fluid, and kb is the Boltzmann constant.

Pak and Cho [6] carried out experimentation to observe the turbulent friction and heat transfer behaviors of dispersed fluids in a circular pipe using two different metallic oxide particles, -alumina (Al2O3) and titanium dioxide (TiO2) with mean diameters of 13 and 27 nm, respectively. The results revealed that the Nusselt number for the dispersed fluids increased with increasing volume concentration as well as

Reynolds number. But at constant average velocity, the convective heat transfer coefficient of the dispersed fluid was 12% smaller than that of pure water. They proposed a new correlation for the Nusselt number under their experimental ranges of volume concentration (0-3%), the Reynolds number (104 - 105), and the Prandtl number (6.54 - 12.33) for the dispersed fluids -alumina (Al2O3) and titanium dioxide (TiO2) particles as given by Eq. (5):

(5)

Maiga et al. [7] numerically studied the hydrodynamic and thermal characteristics of turbulent flow in a tube using different concentrations of Al2O3 nanoparticle suspension under the constant heat flux boundary condition and proposed the following correlation as shown by Eq. (6) to estimate the heat transfer coefficient in terms of the Reynolds and the Prandtl numbers, valid for 104 Re 5x105, 6.6 Pr 13.9 and 0 10%:

(6)

Xuan and Li [8] investigated experimentally for 35 nm Cu/deionized water nanofluid flowing in a tube with constant wall heat flux. They showed that at fixed velocities if the volume fraction of nanofluid increases from 0.5% to 2.0%, the heat transfer coefficient of Cu nanoparticles is enhanced as much as 40% compared to that of pure water. Finally, they have proposed a correlation in the form of Eq. (7) according to which Nusselt number, Nu for the turbulent flow of nanofluids inside a tube can be approximated as follows:

(7)

Despite numerous studies available in literatures, the

authors felt that no appropriate correlations have been presented yet that is entirely satisfactory to calculate heat transfer to, and pressure drop across, the coolant flowing through rod-bundle assemblies like NANO. Therefore, the current experimentation has been conducted with a view to investigate the forced convection heat transfer and pressure drop characteristics of alumina nanofluid for up flow in presence of grid spacers valid for 10082.71 Re 20904.95, and 0 0.025% and finally, based on experimental data the coefficients of Dittus-Boelter correlation [9] have been modified for this NANO specific rod bundle assembly.

THERMOPHYSICAL PROPERTIES OF NANOFLUID In order to utilize nanofluid as PWR coolant, it is first

necessary to understand mechanisms involved in enhancement of thermal conductivity of nanofluid such as Brownian motion, clustering or liquid layering around nanoparticles and also to evaluate other properties like density, viscosity, specific heat precisely. The physical properties of alumina nanoparticles (

Density, specific heat, viscosity and thermal conductivity of alumina nanofluid are estimated using Eq. (8) through Eq. (11) respectively as reported in [7, 10].

(8)

(9)

(10)

(11)

NANO TEST FACILITY The NANO apparatus has been constructed to measure heat

transfer to and pressure drop across a 33 square array rod assembly featuring a pitch-to-diameter (P/D) ratio 1.286 and hydraulic diameter (Dh) 0.010288 m. While Fig.2 illustrates the schematic of NANO loop, Fig.3 depicts the form loss locations in test geometry respectively. The same thermo-hydraulic test loop was previously used by Son & Suh to carry out a different experimentation for designing a liquid metal natural circulation small reactor [as reported in 11].

The system consists of a test section, a plate type heat exchanger (OLAER PWO K Series), a water reservoir, a centrifugal pump (Wilo MHi403EM), flow control valves & stainless steel piping (pipe mat: A269 TP 316L). A total of 9 cartridge type heaters are installed in a 33 square array fashion which resembles a PWR fuel rod bundle. From the pump the coolant enters to the plenum connected to the lower part of the vertical test section. The plenum is an empty space upstream of the heated rod bundle which houses a specially designed inlet flow distributor to suppress non-uniformity of the flow generated by pipe fittings. The flow rate is measured by an electromagnetic flow meter (Toshiba LF400, 0.5% Accuracy) downstream of the pump. Pressure drop along the test section is measured by two identical pressure transducers (Allsensor P601, 0.25% FSO Accuracy) at inlet and outlet. K-type thermocouples are used to measure coolant bulk temperature and central heater rod surface temperature distribution. A collecting tank is installed at the upper end of the test section to abate the flow fluctuations. The overall

temperature of the fluid can be controlled by changing heater current input. Tab.2 summarizes the specification of the heater assembly regionwhere projected frontal areas of the inlet flow distributor and grid spacers have been computed using CAD program. The bundle hydraulic diameter (Dh) is evaluated using Eq. (12) as follows:

(12)

where, x is the side of square duct (42.8 mm) and D is the heater rod diameter (9.8 mm).

FIGURE 3. FORM LOSS LOCATIONS IN NANO TEST FACILITY [11].

FIGURE 2. NANO SCHEMATIC DIAGRAM.

TABLE 1. PHYSICAL PROPERTIES OF ALUMINA NANOPARTICLES AND WATER

Properties Alumina

Nanoparticles Pure Water

Specific Heat, Cp (J/kg. K) 880 4182 Density, (kg/m3) 3970 998.2 Thermal conductivity, k (W/m. K)

40 0.6

1 - Pn f b f

1 -p p pn f b f pC C C

2123 7.3 1nf bf

2 - 2 -

2 -p pb f b f

n f b fp pb f b f

k k k kk k

k k k k

2 294 44 9hx D

Dx D

Description Unit Value

Number of Heater Rods Nos. 9 Configuration - Square Array (33) Heater Rods Diameter mm 9.8 Heater Rods Length mm 2150 Heated Length mm 2000 Rod Pitch mm 12.86 Pitch to Diameter Ratio - 1.286 Grid Spacer Frontal Area mm2 234.019 Inlet Distributor Frontal Area mm2 1241.887

NANOFLUID PREPARATION The Al2O3 nanoparticles [

Conc. Of Al2O3 (%)

Zeta Potential (+mV) pH Time Interval

0.5 hr 14 hr 40 hr 60 hr 0.1 29.0 30.2 30.3 29.9 8.06 0.01 30.6 29.8 29.8 9.21 7.61

0.001 26.2 28.3 28.7 3.10 6.88

HEAT TRANSFER EXPERIMENTATION One important parameter required to quantify heat

transfer characteristics in single phase forced-convection turbulent flow regime is heat flux q (W/m2), which can be defined in terms of total heat input Q (W) into flow channel, dia D (m) and heated length l (m) of heater rods as shown by Eq. (13) since there are nine heater rods heated circumferentially:

(13)

The total heat input Q is assumed as uniform axially and azimuthally since the thickness of heater rods is constant throughout the heated length and it can be obtained either with the product Q1 of input current I (Ampere) and voltage V (Volt) applied to heater rods or with the product Q2 of coolant flow rate (kg/s), coolant temperature increase Tb (K) over the flow channel and specific heat of coolant Cp (J/kg.K) and can be expressed as follows:

(14)

Q2 = Cp Tb (15) To validate the estimation of Q, values of Q1 and Q2

obtained using above equations are plotted in Fig.6. Since they are in fairly good agreement, any of these two values can provide precise estimation of Q. In this study, values obtained by Eq. (15) is used to accomplish further calculations.

Nusselt Number Evaluation In order to compute Nusselt number, Nu for pure water

under single phase forced-convection turbulent flow regime numerous correlations available in literature can be implemented subject to geometry of fluid flow walls and fluid mean velocity (Reynolds number). Among those, the most frequently applied correlations are Dittus-Boelter, Sieder-Tate & Silberberg-Huber as expressed through Eq. (16) to Eq. (18) respectively.

(16)

(17)

(18)

Implementation of above correlations to estimate Nu is justified when the fluid flow sections does not vary significantly from circular. Such channels may include square, rectangular (not too far from square), and probably equilateral or nearly equilateral triangles.

In case of fully turbulent flow along rod bundles, values of Nu may remarkably deviate from the circular geometry due to geometric non-uniformity of the subchannels that creates substantial variation of Nu azimuthally. Apart from that for a given subchannel in a finite rod bundle, the effect of turbulence may affect adjacent subchannels differently depending on the location of subchannels with respect to the duct boundaries. Thus, the value of Nu is a function of position within the bundle [12]. Therefore, for rod bundles, the Nusselt numbers for fully developed conditions (Nu) is expressed as a product of (Nu)c.t. for a circular tube multiplied by a correction factor as stated in Eq. (19):

(19)

where, (Nu)c.t. is usually given by Dittus-Boelter equation

unless otherwise stated. For a square array and specifically for water with 1.1 P/D 1.3, Weisman [13] has defined as follows:

(20)

(21)

Since the applicability of above mentioned correlations are limited to only pure water, the Nusselt number, Nu of alumina nanofluid (0.01 vol.% and 0.025 vol.%) can be estimated by Eq. (5) through Eq. (7) as discussed in the earlier section of this study. All of the above correlations to evaluate Nusselt number can be re-presented in a simplified form as shown in Eq. (22):

(22)

TABLE 3. ZETA POTENTIAL TEST RESULT

FIGURE 6. COMPARISON OF HEAT INPUT BY ELECTRIC POWER (Q1) AND BY ENTHALPY INCREASE (Q2).

9

Qq

Dl

1Q V I

0.8 0.40.023Re PrNu 0.14

0.8 0.3330.027 Re PrW

Nu

0.85 0.30.016Re PrNu

. .c tNu Nu

1.826 1.0430P D

Re PrbNu a

0.8 0.333. . 0.023Re Prc tNu

Since Prandtl number, Pr does not vary significantly during experiment, it can be assumed as constant for simplification and the following equation can be substituted in place of Eq. (22):

(23)

where, (24)

By using a logarithmic function, Eq. (23) can be written as follows:

(25)

The above equation is equivalent to a first degree polynomial (i.e. y=ax+b). Now, if we re-evaluate Nu and Re according to our experimental condition and plot Eq. (25), by fitting a first degree polynomial we can obtain the modified values of coefficient and for NANO rod-bundle assembly.

The experimental values of Nu can be obtained using following equation based on hydraulic diameter, Dh (m) of the flow channel and thermal conductivity, k (W/m.K) at coolant bulk temperature:

(26)

where, h is the convective heat transfer coefficient for fully developed turbulent flow and it can be estimated using following equation:

(27)

where, TW and Tb are central heater rod wall surface temperature and mean bulk fluid temperature respectively.

Heat Transfer with Pure Water In our present study, the experimental Nusselt number, Nu

for pure water as well as alumina nanofluid is computed using Eq. (26) and Eq. (27) for a wide range of Re spanning from 10,082.71 to 20,904.95. The values thus obtained for pure water is compared with the Nu obtained by most renowned correlations as discussed in earlier sections and tabulated in Tab.4. Variations of Nu with inlet Re for NANO experiment and different correlations are plotted in Fig.7. Finally, using logarithmic function as depicted in Eq. (25), Nu obtained by experiment is plotted against inlet Re (Fig.8) and by fitting a curve featuring first degree polynomial the values of coefficient and in Eq. (25) are modified for NANO test apparatus. A similar study was carried out by Makhmalbaf [14] for a vertical hexagonal rod bundle with 7 vertical rods in a hexagonal tube featuring 1.4 cm tube hydraulic diameter and the results of NANO experiment have been compared with that of Makhmalbaf in Tab.5.

The analogy shows that Nu obtained by NANO experiment significantly varies from those obtained by different correlations for same inlet Re. The correlations used in this study predicts Nu based on only two dimensionless parameters namely inlet Reynolds number and Prandtl

number. But in reality, more complex phenomenon such as geometry of coolant flow channel, velocity & temperature gradient of coolant, contact time between heater rod and coolant, heated length of heater rod, heater capacity, heat loss through insulation, precision of sensing device e.g. thermocouples, pressure transducers, flow meters etc. may directly affects the value of Nusselt number and convective heat transfer coefficient.

One pivotal reason behind low Nu obtained by NANO experiment may be slow sensing capacity of thermocouples to rapid temperature change used in NANO apparatus. Moreover, due to high flow velocity inside the flow channel, the contact time between coolant and heater rod was short and hence experimental T between inlet and outlet temperature of coolant was not so high. Therefore, the total heat input as well as experimental Nu as computed by Eq. (15) and Eq. (26) respectively, also became small compared to predictions made by different correlations.

Apart from that, although spacer grids are originally designed to maintain proper geometrical configurations of the rod bundle, it also plays a significant role on heat transfer enhancement by disrupting and re-establishing the thermal boundary layers. Spacer grids may have various special geometrical features to promote turbulence such as mixing vanes of different configurations. For example, while the split vanes may deflect the upward flow to mix between neighboring subchannels, the swirl vanes are designed to generate a pronounced swirling flow within subchannel. Another innovative design is twisted vanes having two mixing vanes at the upper ends of the interconnections between straps which are bent in opposite directions at the top slope of the triangular base to generate a cross flow between subchannels as well as swirling flow in the subchannel by regulating flow simultaneously to the fuel rod and to the gap region. Due to high cost and complexity of manufacturing, grid spacers used in NANO rod bundle are very simple in design having no mixing vanes, which in turn failed to promote turbulence as well as heat transfer rate from heater rod to coolant and hence, it is assumed as another key reason behind low Nu obtained by experiment.

Heat Transfer with Alumina Nanofluid A similar study as described in the last section is carried

out to evaluate the effects of alumina nanoparticles inclusion into pure water on heat transfer performance using two different concentrations (0.01 vol.% and 0.025 vol.%) of alumina/water nanofluid as coolant. Comparison of experimental Nusselt number, Nu with that of predictions made by different correlations is summarized in Tab.6 & Tab.7 and plotted in Fig.9 and Fig.10. Another comparison showing the increment of Nusselt number, Nu as well as convective heat transfer coefficient, h by amalgamation of different concentrations of alumina nanofluid into pure water has been tabulated in Tab.8 and Tab.9 and plotted in Fig. 11 and Fig. 12 respectively.

ReNu

Prba

ln ln ln ReNu

W b

qhT T

hh DNuk

The result reveals that both Nusselt number and convective heat transfer coefficient is increased over 20% and 25% respectively compared to pure water with the inclusion of only 0.01 vol.% of alumina nanoparticles into pure water. More interestingly, it can be seen that Nusselt number approximated by Pak & Cho and Maiga et al. is decreased while the concentration of alumina nanoparticles is increase from 0.01 vol.% to 0.025 vol.%. This is due to the fact that with the increase of vol.% of alumina nanoparticles, the density of the nanofluid has also been increased which in turn has lowered the specific heat capacity as well as Prandtl number of the solution with higher concentration.

Finally, like pure water using logarithmic function as presented in Eq. (25), Nu obtained by experiment with different concentrations of alumina nanofluid is plotted against inlet Re (Fig.8) and by curve fitting, the values of constant coefficient and are modified for different coolants as reported in Tab.10.

UNCERTAINTY ANALYSIS Uncertainty of measurement is the doubt that may exist

about the experimental data arises from measuring errors of various parameters such as heat flux, temperatures, flow rate etc. It can be defined as follows [8]:

(28)

In order to reduce the uncertainty of results, the experiments have been repeated four times with each different coolants and an uncertainty analysis has been carried out using statistics and it is observed that measuring error is less than 1.0%.

Reynolds Number

(Re)

Nusselt Number, Nu

NANO Exp.

Dittus-Boelter

Sieder-Tate

Silberberg-Huber

Weisman

1104 15.14 63.90 70.89 57.52 76.01 1.3104 20.45 79.14 87.79 72.20 94.13 1.7104 22.69 97.57 108.23 90.18 116.05 2104 25.64 114.51 127.03 106.91 136.20

Correlation Name NANO Experiment

(Square Array) Makhmalbafs

Experiment (Hexagonal Array)

Experiment 0.026617 0.69 0.03337 0.8112 Dittus-Boelter 0.040055 0.80 0.0309 0.80 Sieder-Tate 0.044431 0.80 0.0345 0.80 Silberburg-Huber 0.022740 0.85 0.0187 0.875

Reynolds Number

(Re)

Nusselt Number, Nu

NANO Experiment

Xuan & Li

Pak & Cho

Maiga et al.

1104 20.34 71.74 72.04 101.09 1.3104 26.34 89.45 86.32 119.43 1.7104 30.74 110.12 102.01 139.61 2104 33.28 127.31 113.91 155.41

Reynolds Number

(Re)

Nusselt Number, Nu

NANO Experiment

Xuan & Li

Pak & Cho

Maiga et al.

1104 20.59 85.37 70.30 99.38 1.3104 27.03 106.45 84.23 117.40 1.7104 30.40 131.05 99.55 137.24 2104 31.82 151.51 111.16 152.78

Reynolds Number

(Re)

Nusselt Number, Nu

% increasing by 0.01 Vol.%

% increasing by 0.025 Vol.%

1104 25.57 26.49 1.3104 22.38 24.36 1.7104 26.21 25.39 2104 22.97 19.43

Reynolds Number

(Re)

Convective Heat Transfer Coefficient , h (W/m2.K)

% increasing by 0.01 Vol.%

% increasing by 0.025 Vol.%

1104 27.66 31.51 1.3104 24.56 29.53 1.7104 28.28 30.49 2104 25.13 24.93

TABLE 6. COMPARISON OF Nu OBTAINED BY EXPERIMENT AND VARIOUS CORRELATIONS FOR ALUMINA

NANOFLUID (0.01 VOL.%)

TABLE 9. COMPARISON OF h INCREMENT BY ALUMINA NANOFLUID COPMARED TO PURE WATER

TABLE 8. COMPARISON OF Nu INCREMENT BY ALUMINA NANOFLUID COPMARED TO PURE WATER

TABLE 7. COMPARISON OF Nu OBTAINED BY EXPERIMENT AND VARIOUS CORRELATIONS FOR ALUMINA

NANOFLUID (0.025 VOL.%)

TABLE 5. COMPARISON OF MODIFIED CONSTANT COEFFICIENTS

TABLE 4. COMPARISON OF Nu OBTAINED BY EXPERIMENT AND VARIOUS CORRELATIONS FOR PURE WATER

2 2 2Nu q T vNu q T v

Coolant NANO Experiment

Pure Water 0.026617 0.69 0.01% Alumina Nanofluid 0.042429 0.67 0.025% Alumina Nanofluid

0.093574 0.59

TABLE 10. COMPARISON OF MODIFIED CONSTANT COEFFICIENTS FOR DIFFERENT COOLANTS

FIGURE 12. COMPARISON OF h OBTAINED BY DIFFERENT COOLANTS.

FIGURE 11. COMPARISON OF Nu OBTAINED BY DIFFERENT COOLANTS.

FIGURE 10. COMPARISON OF Nu OBTAINED BY EXPERIMENT & CORRELATIONS FOR 0.025%

ALUMINA NANOFLUID.

FIGURE 9. COMPARISON OF Nu OBTAINED BY EXPERIMENT & CORRELATIONS FOR 0.01%

ALUMINA NANOFLUID.

FIGURE 8. PLOT OF Nu AGAINST INLET Re USING LOGARITHMIC FUNCTION FOR DIFFERENT COOLANTS.

FIGURE 7. COMPARISON OF Nu OBTAINED BY EXPERIMENT & CORRELATIONS

FOR PURE WATER.

PRESSURE DROP EXPERIMENTATION The pressure drop across the NANO rod bundle assembly

is experimentally measured by means of two digital differential pressure transducers (one at inlet of test section & another at outlet of test section as shown in Fig. 2) for single phase turbulent flow. The pressure loss in the complex configuration of commercial spacers arises from several hydrodynamic effects included in the flow. The spacer is used to fix the rods in the bundle. The velocity and temperature distributions redeveloped due to the blockage of the flow cross section downstream of the spacer.

The total pressure drop for the test section of this study is mainly aroused from the presence of inlet flow distributor, grid spacers, frictional loss along the piping of the test section, due to presence of various pipe fittings such as 900elbows, 1800 flow dividers etc., presence of sudden enlargement and contraction in the path of coolant flow & due to the effect of gravity. Hence, the theoretical pressure drop (P=Pin Pout) can be expressed as follows:

(29)

In the above equation, pressure drop due to spacer grids & inlet flow divider has been calculated using the following correlation of Rehme [15]:

(30)

where, Cv is modified drag coefficient, Vv is average bundle fluid velocity, Av is unrestricted flow area away from the grid or spacer and As is projected frontal area of the spacer. The drag coefficient (Cv) is a function of average bundle, unrestricted area Reynolds number. In this study value of Cv is taken as 9.5 (at Re =104) as indicated by Rehmes data for square arrays [12]. The frictional pressure drop has been calculated by using the following equation:

(31) where, f is the average friction factor depends on the

channel geometry and flow velocity. In case of turbulent flow, Rehme [15] proposed a method

to obtain the friction factor for subchannels in actual geometry. Cheng and Todreas fitted results of this method with polynomial of Eq. (32) as presented below [16]:

(32)

for turbulent flow:

(33)

The above correlation can be used to obtain friction factor in square array subchannel if the coefficients a, b1 and b2 are

evaluated using Table 9-3 as documented by Todreas & Kazimi [16].

To obtain friction factor for circular piping of the NANO apparatus, Mc Adams and Blasius correlations have been used as presented in Eq. (34) and Eq. (35) respectively:

Mc Adams (for 30,000 Re 106):

(34)

Blasius (for Re 30,000):

(35)

Pressure drop due to gravity and form loss due to presence of abrupt change in flow directions and sudden expansion/contraction have been estimated by using Eq. (36) and Eq. (37) respectively [12]:

(36)

(37)

Comparison of experimental pressure drop with that of

theoretical estimation for different inlet Re and percentage of estimated pressure drop caused by different components present in NANO apparatus is shown in Fig.13 and Fig.14 respectively while pure water is used as coolant. Tab.11 documents the comparison of experimental pressure drop for pure water and different concentrations of alumina nanofluid.

The results demonstrates that for pure water estimated pressure drop falls within 5% to 18% of the experimental pressure drop depending on inlet velocity. Note that as the flow velocity is decreased, effect of grid spacers on pressure drop is also lessened and effect of gravity starts to prevail (Fig.14) which is logical as the test section is vertical. In case of the lowest inlet Re, pressure drop due to the effect of gravity is almost 69% of the total pressure drop. More interestingly, it is observed that there is no change in pressure drop during experiment with the inclusion of higher volume concentration of nanoparticles. One logical explanation behind this phenomena may be since the change in pressure drop when concentration of nanofluid is increased from 0.0 vol% to 0.01 vol.% or 0.025 vol.% is too small that it could not be sensed by the digital pressure transmitter with only two digit precision as used in NANO apparatus. It is extremely difficult to establish a pressure loss coefficient correlation of general validity for grid spacers because of variation and complexity of the grid spacer geometry.

Estimated SpacerGrid Friction Gravity FormP P P P P

22

2V S

SpacerGrid VV

P CV A

A

2

2Friction hP f

L VD

2/ 1 21 1fiT P PC a b bD D

/

0.18/RefiT

iT

iT

Cf

0.20.184 Ref

0.25

0.316Re

f

cosGravityP g Z

2

2Form formP k

V

APPLICATION TO FUSION-FISSION HYBRID SYSTEM A fusion-fission hybrid is defined as a subcritical nuclear

reactor consisting of a fusion core surrounded by a fission blanket. The fusion core provides an independent source of neutrons, which allows the fission blanket to operate subcritically.

The main applications of hybrids are: (1) nuclear waste management by means of burning long-lived radioactive waste products, (2) the simultaneous production of energy and management of nuclear waste by deep-burn fuel cycles, and (3) the breeding of new fissile fuel by substantially increasing the utilization efficiency of U-238, or alternatively, converting to a Th-232 fuel cycle.

One of the promising concepts of such fusion-fission hybrid system is Fusion-driven subcritical reactor for energy multiplier (FDS-EM), proposed by Y. Wu et al. [17]. The basic concept of FDS-EM blanket is shown in Fig.15 featuring a banana type module of 7.5 degree section angle, closed by steel wall and internally supported by stiffening plate. It is divided into the thick first wall (FW) containing coolant tube bundles, fission fuel zone, thick stiffening plate (SP) containing coolant tube bundles and tritium breeding zone in radial direction. The circle tubes lead coolant water flowing down. The coolant water is collected at bottom, and then feeds into fission fuel zone cooling fuel assemblies. The entire structure design with FW, side wall (SW), and stiffening plate may sustain 15.5 MPa water coolant pressure.

The LiPb serves as tritium breeder and coolant which self-cools the breeding zone in six channels parallelly at the rear of blanket. The LiPb is fed into blanket from the top of the blanket and flow out at the bottom.

The present thermo-hydraulic study of square array rod bundle using nanofluid coolant can be readily applied in designing fission fuel zone of such a fusion-fission hybrid system to enhance heat transfer and reduce pressure drop.

CONCLUSION Despite analysis of reviewed literature as well as results of

NANO experiment delineates that nanofluid is capable of augmenting the heat transfer capability remarkably, there is still no satisfactory explanation proposed yet regarding the prevention of clustering in nanoparticle suspensions. Therefore, while attempting to implement nanofluid coolant in PWR for long term use, clustering phenomenon of nanoparticles may eventually decrease the thermal conductivity and initiate problems like corrosion and wear inside piping and pumps. Hence, the clustering of nanoparticles to be solved first in order to utilize nanofluid as a promising coolant in PWR to achieve both extended life time of associated equipment and higher thermal efficiency.

The present study has been carried out in 33 square array vertical rod bundle housed in a square shell with single phase turbulent flow covering a range of Re from 7,463 to 20,904. During analysis of convective heat transfer, the applicability of

well-known correlations from literature has been verified and finally the constant coefficients of Dittus-Boelter correlation have been modified for this NANO specific rod bundle using pure water as well as two different concentrations of alumina nanofluid. It has been experimentally observed that inclusion of only 0.01 vol.% of alumina nanoparticles in pure water can boost the convective heat transfer coefficient above 25% subject to inlet Re.

In case of pressure drop, it is observed that deviation between experimental and estimated pressure drop lies within acceptable range which indicates that NANO apparatus is capable of measuring pressure drop as well as pumping power requirement satisfactorily. Finally, it may be concluded that despite the difference in elevation plays a vital role in pressure drop when velocity is low enough, the innovative design of grid spacer is also of utmost importance to minimize the overall pressure drop as well as pumping power.

Reynolds Number

Experimental Pressure Drop (Bar) Estimated Pr. Drop with Pure

Water (Bar)

Pure Water

Alumina Nanofluid

0.01% 0.025%

20904.95 0.90 0.90 0.90 0.76 17111.90 0.80 0.80 0.80 0.66 13173.32 0.60 0.60 0.60 0.54 10082.71 0.50 0.50 0.50 0.44 7463.18 0.40 0.40 0.40 0.34

FIGURE 13. COMPARISON OF EXPERIMENTAL AND ESTIMATED PRESSURE DROP

FOR PURE WATER.

TABLE 11. COMPARISON OF PRESSURE DROP FOR DIFFERENT COOLANTS

ACKNOWLEDGEMENTS This work was supported by the National Research

Foundation of Korea (NRF) grant funded by the Korean Government (MSIP) (No. 2008-0061900) and partly supported by the Brain Korea 21 Plus Project (No. 21A20130012821).

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FIGURE 15. SCHEMATIC VIEW OF ENERGY MULTIPLIER OUTBOARD BLANKET [18].

FIGURE 14. PERCENTAGE OF ESTIMATED PRESSURE DROP CAUSED BY DIFFERENT

COMPONENTS OF NANO APPARATUS.