- Open Access
- Authors : Lovepreet Singh, Pankaj Kumar, Gurpreet Singh
- Paper ID : IJERTV13IS060003
- Volume & Issue : Volume 13, Issue 06 (June 2024)
- Published (First Online): 07-06-2024
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Analysis of the Performance of Radiator Tube with Angular Bend Using Low Concentration Particles
Lovepreet Singh, Pankaj Kumar, Gurpreet Singh, Student, Department of Mechanical Engineering, Chandigarh University (CU), Mohali, Punjab(INDIA), Pin code- 140413
AbstractThe analysis of the performance of radiator tube with angular bend using low concentration particles presents a numerical investigation under different boundary conditions on the heat transfer performance of a radiator tube with an angular bend. The investigation is centered on the application of nanofluids of aluminium oxide and copper oxide, with aluminium being the chosen material for the automobile radiator tube. At 100, 120, and 140 degrees Celsius as the inlet temperatures, the nanofluids are examined. To evaluate the car radiator tube's heat transmission efficiency, a number of parameters are examined. During analysis heat transmission is enhanced by higher input temperatures, and copper oxide nanofluid can boost heat transfer efficiency by up to 15%. Furthermore, a higher Reynolds number accelerates the transfer of heat.
Keywords Nanofluid, angular bend tube, Rate of Heat Transfer, Pressure drop, Heat transfer coefficient.
Nomenclature:
N Kinematics Viscosity
Density
Cp Specific heat Capacity k Thermal conductivity
H Heat transfer coefficient
V Velocity
Dh Hydraulic Diameter
Di Diameter of the inner tube Do Diameter of the outer tube
Ah cross-sectional area of the inner tube passing hot fluid Ac cross-sectional area of the inner tube passing cold fluid
p Pressure drop
U Overall heat transfer coefficient Q Heat Transfer heat
Re Reynold's number Nu Nusselt Number
T Temperature gradient K Kelvin
°C Degree Celsius
INTRODUCTION
In spite of significant growth during the past years, researchers have focused on developing various methods to meet growing energy demands. Improving the performance of heat exchange devices is a potential method to reduce energy consumption. Research focuses on improving industrial device's heating/cooling performance and enhancing heat transfer for longer equipment lifespan. Heat transfer rate and pumping power are key factors in heat exchange device design. For high-density fluids, heat transfer is more crucial than friction loss in radiator operation [1]. The radiator plays a crucial role in a vehicle's cooling system, dissipating excess heat from the engine to ensure its proper functioning. Countless studies have been conducted to enhance its performance. To enhance the heat transfer performance of radiators, there are various approaches such as fluid modification, geometric modification, and enhancing the thermal conductivity of the heat exchanger material. Traditionally, water and ethylene glycol have been utilized as heat transfer fluids for cooling car radiators. Unfortunately, these liquids have suboptimal thermophysical properties that limit their heat transfer efficacy. Improving the heat transfer performance of these fluids would result in better engine performance. In the pursuit of enhancing the thermal conductivity of conventional fluids, various methods involving micro and millimeter sized particles have been attempted. By increasing the heat transfer efficiency of these fluids, engines can operate more efficiently, leading to better fuel economy and lessened environmental impact [2-3].
Fluid modification involves the use of nanofluids, which contain nanoparticles of metals, oxides or carbon allotropes, to improve the fluid properties. Geometric modification introduces roughness to the surface of the radiator. Scientists are primarily focused on developing nanofluids, as the nanoparticles offer high thermal conductivity. Examples of metal nanoparticles are copper, gold, and silver, while metal oxide nanoparticles such as aluminium, silica, titania, bismuth oxide, and zirconia are also used. The chemical stability of the nanoparticles is crucial. Granqvist et al. [4] initially discovered ultrafine particles later on known as nanoparticles, which have size in nanometres. It was choi [5] who introduced that nanofluid is a diluted mixture of nanoparticles. When added to base fluids, the thermo-physical properties of the fluids are improved. The heat transfer properties are affected by factors such as particle volume concentrations, size and shape, material, base fluid properties, and temperature.
Ali and Arshad [6] conducted an experiment to evaluate the angle effect of pin fin heat sink channel using nanofluids with GNPs. They studied three heat sinks with channel angles of 22.5°, 45°, and 90°. The heat sink with a channel angle of 22.5° showed better thermal performance compared to the other two. They analyzed thermal resistance, convection heat transfer coefficient, and log mean temperature difference. Arshad and Ali [7] also compared the thermal and hydrodynamic performance of graphene nanoplatelets nanofluids with distilled water on an integral fin heat sink. They observed greater pumping power for GNPs nanofluids compared to distilled water. At a Reynolds number of 972, using GNPs nanofluids achieved a minimum base temperature of 36.81 °C and the highest convective heat transfer enhancement of 23.91%. Pumping power varied with flow rate and heat flux, with the maximum being observed for the GNPs nanofluid at a heat flux of 47.96 kW/m2.
Naraki et al [14] studied the overall heat transfer coefficient of a car radiator using CuO-water nanofluid as the coolant. They found that the heat transfer performance improved as the particle concentration increased while keeping the flow rate of nanofluids constant, compared to the conventional fluid used in radiators. Ali et al [15] conducted an experimental study to enhance heat transfer in car radiators using ZnO/water and MgO/water nanofluids. They added surfactant SHMP to stabilize the ZnO/water nanofluid in a 1:5 ratio with particles and maintained a pH of 2.2. To enhance the stability of the MgO nanofluid, they lowered the pH of the mixture. The heat transfer rate increased up to an optimum flow rate, after which the particles started to stick on the surface, causing a decrease in heat transfer rate. Elias et al [16] investigated the thermo- physical properties of nanofluids containing Al2O3 nanoparticles in a water/ethylene glycol mixture (50:50), including thermal conductivity, density, viscosity, and specific heat. They found that the thermal conductivity improved with an increase in temperature due to an increase in Brownian motion of particles. An increase in the volume concentration of nanoparticles resulted in higher thermal conductivity, viscosity, and density, but a lower specific heat of the nanofluid. The lower specific heat of the nanofluid was attributed to the lower specific heat of the added particles compared to the base fluid.
MATHEMATICS MODELLING
Using computer-aided design (CAD) software, construct a 3D model of the radiator tube with the angle bend. Make sure the radiator tube's exact physical dimensions and properties are represented in the model. Heat transmission is enhanced by the presence of low-concentration particles in the fluid passing through the radiator tube. By encouraging turbulence and raising the fluid's effective Thermal conductivity, these particles raise the convective Heat Transfer Coefficient. The radiator dissipates heat more effectively as a result.
Fig. 1. Angular bend tube (2D) Fig. 2. Angular bend tube (3D)
Thermal conductivity C of nanofluids was calculated using (1) equation given below:
b
Knf/kf = 1+ 64.70.7460 (f/ds)0.3690 (ks/kf)0.7476 Pr0.9955Re 1.2321
(1)
Velocity of Aluminum oxide and Copper oxide has been calculated by using Equation:
Unf/uf = 1/ (1-34.87(ds/df)-0.3 1.03
(2)
Density of nanofluids was calculated as:
(3)
Specific heat of Aluminum oxide and Copper oxide has been calculated by flowing equation:
)s )/
(4)
Hydraulic diameter of flat tube was calculated as :
Dh = (4 x [(/4)]d2 +(D-d) x d] ) /( x d+2x(D-d)) (5)
Where, D and d are the major and minor diameters of the flat tube, respectively. Heat transfer rate from nanofluid was calculated as,
= × . × ( ) (6)
The average heat transfer coefficient of nanofluid in flat tube was calculated as
hexp = (mnf xcp(nf)x(tin+tout) ) / ( (AS x (tin+tout)LM ) (7)
The bulk mean temperature (Tb) of nanofluid is given
Tb= (tin +tout)/2 (8)
Table 1. Boundary Conditions for nanofluids
Set No. |
Fluid |
Velocity |
Inlet Temp. () |
Mass flow Rate Kg/s |
Hydra ulic diame ter |
1 |
Nanofluid (Al203/water) |
2m/s |
100 140 |
15.1759 |
0.07m |
Nanofluid (Cu2O/Water) |
2m/s |
100 140 |
15.1759 |
0.07m |
Fig 3. Meshing of angular bend tube 1 Fig 4. Meshing of angular bend tube 2.
RESULT AND DISCUSSION
In this investigation, the counter flow configuration of radiator tube has been taken into consideration and different materials and fluids for inner angular tube have been selected. Three different sets of boundary conditions e.g.- inlet temperature, hydraulic diameter, mass glow rate for aluminium oxide and copper oxide have been introduced for CFD method of angular tube. The output results of angular radiator tube according to the inlet boundary conditions have been studied to determine the heat transfer performance based on Reynolds number.
The rate of heat transfer determines the heat transfer performance in the radiator tube. It has been evaluated by using following equation:
= × . × ( )
Table 2. Heat transfer at 100° C inlet temp.
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
100 |
76.0927 |
0.039 |
4.182 |
3023.573 |
12000 |
100 |
79.5745 |
0.053 |
4.182 |
4305.386 |
15000 |
100 |
81.9407 |
0.066 |
4.182 |
4567.955 |
18000 |
100 |
83.6063 |
0.079 |
4.182 |
4837.758 |
21000 |
100 |
84.8575 |
0.093 |
4.182 |
5106.872 |
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
120 |
90.1159 |
0.039 |
4.182 |
4913.307 |
12000 |
120 |
94.4681 |
0.053 |
4.182 |
5704.637 |
15000 |
120 |
97.4258 |
0.066 |
4.182 |
6280.937 |
18000 |
120 |
99.5079 |
0.079 |
4.182 |
6824.695 |
21000 |
120 |
101.072 |
0.093 |
4.182 |
7420.913 |
Table 3. Heat transfer at 120° C inlet temp.
Table 4. Heat transfer at 140°C inlet temp
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
140 |
104.1391 |
0.039 |
4.182 |
5895.9 |
12000 |
140 |
109.3618 |
0.053 |
4.182 |
6845.5 |
15000 |
140 |
112.911 |
0.066 |
4.182 |
7537.1 |
18000 |
140 |
115.409 |
0.079 |
4.182 |
8124.1 |
21000 |
140 |
117.286 |
0.093 |
4.182 |
8905.0 |
It was observed that the heat transfer characteristics of the water increased with the trends of Reynolds number. By increasing the Reynolds value, the rate of heat transfer increased because of the increasing Reynolds value the flow of the water changes. The rate of heat transfer easily identifies by the graph which is given below:
Fig.5. Heat Transfer of water at different temperature on different Reynolds number
Similarly, the rate of heat transfer of car radiator tube studied by using aluminium oxide nanofluid and evaluated the all results which are given below:
Table 5. Heat transfer at 100°C inlet temperature
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
100 |
75.1015 |
0.039 |
4.17556 |
4093.614 |
12000 |
100 |
78.6953 |
0.053 |
4.17556 |
4760.153 |
15000 |
100 |
81.5248 |
0.066 |
4.17556 |
5140.44 |
18000 |
100 |
82.5921 |
0.079 |
4.17556 |
5797.515 |
21000 |
100 |
83.8261 |
0.093 |
4.17556 |
6341.133 |
Table 6. Heat transfer of Al2O3 at 120°C inlet temperature
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
120 |
89.9772 |
0.039 |
4.17556 |
4889.166 |
12000 |
120 |
94.1923 |
0.053 |
4.17556 |
5711.417 |
15000 |
120 |
96.2015 |
0.066 |
4.17556 |
6558.621 |
18000 |
120 |
98.2402 |
0.079 |
4.17556 |
7177.960 |
21000 |
120 |
99.7827 |
0.093 |
4.17556 |
7851.019 |
Table 7. Heat transfe of Al2O3 at 140 °C inlet temperature
Fig. 6. Heat transfer of Al2O3 nanofluids at different inlet temperatures
And following given tables provide the data of heat transfer radiator tubes by using copper oxide nanofluids:
Table 8. Heat transfer of CuO at 100 °C inlet temperature
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
140 |
103.577 |
0.039 |
4.17556 |
5931.345 |
12000 |
140 |
108.772 |
0.053 |
4.17556 |
6910.813 |
15000 |
140 |
112.286 |
0.066 |
4.17556 |
7637.60749 8 |
18000 |
140 |
113.888 |
0.079 |
4.17556 |
8613.562 |
21000 |
140 |
115.739 |
0.093 |
4.17556 |
9421.215 |
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
100 |
68.6437 |
0.039 |
2.91808 |
4740.308 |
12000 |
100 |
72.3454 |
0.053 |
2.91808 |
5955.325 |
15000 |
100 |
75.1318 |
0.066 |
2.91808 |
6959.915 |
18000 |
100 |
77.1869 |
0.079 |
2.91808 |
7928.12 |
21000 |
100 |
79.1398 |
0.093 |
2.91808 |
8882.632 |
Table 9. Heat transfer of CuO at 120 °C inlet temperature
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
120 |
68.6839 |
0.039 |
2.91808 |
5840.03 |
12000 |
120 |
72.617 |
0.053 |
2.91808 |
7328.16 |
15000 |
120 |
75.5776 |
0.066 |
2.91808 |
8555.45 |
18000 |
120 |
77.7611 |
0.079 |
2.91808 |
9737.25 |
21000 |
120 |
79.446 |
0.093 |
2.91808 |
11005.6 |
Table 10. Heat transfer of CuO at 140 °C inlet temperature
Re |
Ti(°C) |
To(°C) |
M |
Cp |
Q(watt) |
9000 |
140 |
79.0207 |
0.039 |
2.91808 |
6939.75 |
12000 |
140 |
83.7405 |
0.053 |
2.91808 |
8701 |
15000 |
140 |
87.2931 |
0.066 |
2.91808 |
10151 |
18000 |
140 |
89.9133 |
0.079 |
2.91808 |
11546.4 |
21000 |
140 |
91.9352 |
0.093 |
2.91808 |
13043.9 |
Fig. 7. Heat transfer of CuO at different inlet temperature
In following graphs, the rate of heat transfer shows of water, aluminium oxide and copper oxide nanofluids and compare the heat transfer of all fluids.
Fig. 8. Graph of heat transfer of water, aluminium oxide and copper oxide nanofluids at 100 °C temperature
Fig. 9. heat transfer of water, aluminium oxide and copper oxide at 120
°C temperature
Fig. 10. Graph of heat transfer of water, aluminium oxide and copper oxide nanofluids at 140 °C temperature
Reynold's number ;
Reynoldss Number is a dimensionless parameter which is defined as the ratio of inertia forces to the viscous forces. As the flow configuration in pipes mainly depends on flow velocity, surface geometry, surface roughness, type of fluid
among other characteristics, Reynolds number is used to determine the flow configuration whether the flow is laminar or turbulent. If the Reynolds number is less than 2400, the flow is said to be laminar and if the Reynolds number is greater than 4000, the flow is said to be turbulent.
Reynolds number for hot fluid and cold fluid has been calculated by using the following equation:
Re = VD/ or VD/v
Table 11: The Reynolds number for different fluids
Sr No. |
Fluid |
Reynoldss No.(Re) |
1. |
Water |
9000-21000 |
2. |
Al2O3 |
9000-21000 |
3. |
CuO |
9000-21000 |
In this study, the heat transfer evaluated on the basis of vary of Reynolds number from 9000-21000.
Nusselt Number;
Nusselt Number is a dimensionless quantity which signifies the improvement of heat transfer through a fluid layer as a result of convection related to conduction across the same fluid layer. It helps to determine the heat transfer coefficient in the Heat Exchanger.
The following correlation is used to determine the Nusselt No. for aluminum and copper oxide fluid:
Nu= 0.023 Re0.8 Pr0.4
The following table shows the results of Nusselt No. for hot and cold fluid:
Table 12. Nusselt Number for different fluids
CONCLUSION
This numerical study on heat transfer performance of Radiator Tube with angular bend has been conducted by doing the simulation of the angular flat tube with different sets of boundary conditions. Aluminium oxide and copper oxide have been considered as nanofluids respectively. Aluminium have been selected as a material for tube of the Car Radiator. The inlet temperatures of nanofluids are taken as 100 , 120 and 140 . Different parameters have been analyzed to measure the heat transfer performance of the Car Radiator Tube. The following outcomes of the investigation have been observed:
-
The thermal conductivity and viscosity of the nanofluid are increased once the nanoparticles are dispersed in distilled water, and this enhancement grows as particle concentrations rise.
-
The density and viscosity increased with increasing the particle concentration, while they both decreased with increase in temperature.
-
The deviation between viscosity of nanofluids and base fluid reduced with increase in temperature.
-
Nusselt No. increases with the increment of Reynolds No.
-
The heat transfer rate increased with increase in fluid inlet temperature, particle concentration and Reynolds number.
-
Thermal conductivity, other factors such as fluid inlet temperature, Reynolds number and flid velocity also affect heat transfer rate.
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|
1 |
Al2O3 |
0.122 |
Water |
0.108 |
|
2 |
CuO |
1.112 |
Water |
1.009 |
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