# INTERNATIONAL JOURNAL OF RESEARCH IN AERONAUTICAL AND MECHANICAL ENGINEERING

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1 ISSN (ONLINE): INTERNATIONAL JOURNAL OF RESEARCH IN AERONAUTICAL AND MECHANICAL ENGINEERING Study of forced convection heat transfer With DAQ & ANSYS First Authors Moopanar karthikeyan 1, Raote Sarvesh 2, Sawant Rahul 3, Bhoi Sandesh 4 Department of Mechanical Engineering Saraswati college of engineering, Navi Mumbai, Maharashtra, India Second Author Prof. Madan Jagtap Department of Mechanical Engineering Saraswati college of engineering, Navi Mumbai, Maharashtra, India Abstract The aim of this work is to validate the Dittus-Boelter equation by experimental, correlation and Simulation method. It used to find the value of heat transfer coefficient h for turbulent flow in many fluid transfer systems. This work discusses how the Dittus-Boelter equation is applied to the problem of circular pipe. In experimental verification a DATA ACQUISTION (DAQ) SYSTEM is used to measure the temperature accurately & reliably. This DAQ system also serves the purpose of condition monitoring system, which records the temperature changes of the system continuously. In CFD simulation ICEM CFD for modeling and FLUENT 14 for analysis are used. Results of CFD simulation will be obtained by CFD-POST. Here heat transfer coefficient value is compared by correlations, experiment and CFD simulations, finally the aim of this work is to validate Dittus-Boelter equation. Keywords: ANSYS; Heat Transfer; CFD; FLUENT; DAQ 1. Introduction In the study of thermodynamics the average heat transfer coefficient, is used in calculating the convection heat transfer between a moving fluid and a solid. This is the single most important factor for evaluating convective heat loss or gain. Knowledge of h is necessary for heat transfer design and calculation and is widely used in manufacturing processes, oil and gas flow processes and air-conditioning and refrigeration systems. The heat transfer coefficient is critical for designing and developing better flow process control resulting in reduced energy consumption and enhanced energy conservation. It is also influenced by flow velocity and surface geometry. It may be noted that the physical or thermal properties of the surface material play no part in the process of convective heat transfer. As the fluid properties vary with the Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 174

2 temperature and locations the value of convective heat transfer coefficient vary from point to point, this leads to the situation that analytically derived equation are applicable only to a limited extent 1.1 DITTUS-BOELTER RELATION The conventional expression for calculating the heat transfer coefficient in fully developed turbulent flow in smooth pipes is the Dittus-Boelter equation. = Where C, m and n are constant determined experimentally. We will use these values - C = 0.023, m = 0.8 and n = 0.4 for heating of the fluid n = 0.3 for cooling of the fluid The properties of this relation have been calculated at the average fluid bulk temperatures. Equation is valid for single phase heat transfer in fully developed turbulent flows in smooth pipes for fluids with Prandtl number ranging from 0.6 to 100 at low heat fluxes. At high fluxes the fluid properties changes resulting in higher errors. At higher heat fluxes the Sieder-Tate equation is used to reduce the error. The work presented is about designing and acquiring data from an experimental setup to verify the Dittus-Boelter empirical relation by finding the heat transfer coefficient. The value of the heat transfer coefficient has been calculated from theory, experiment and CFD simulation to compare the results. 2. Methodology The below flow chart represents the step by step working procedure of this work. Thestandard procedure for ICEM- CFD work follows the above components. For the present work, in case of pipe creating the geometry then computational domain is constructed around the pipe geometry, later set the mesh parameters then generates the mesh. Later this mesh is exported in the fluent readable format METHODOLOGY EXPERIMENTAL ANALYSIS USING DAQ SYSTEM CORRELATION METHOD USING DITTUS-BOELTER EQUATION CFD SIMULATION USING ANSYS Fig 2.1: Methodology Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 175

3 3. Experimental Set Up Of Forced Convection Fig. 3.1: Experimental Set Up Of Forced Convention The experimental set up consists of a blower unit fitted with the rest pipe. The test section pipe is grey cast iron surrounded by nichrome heater. Four temperature sensors are embedded on the test section and two temperature sensors are placed in the air stream at the entrance and exit of the test section to measure air inlet and outlet temperature. Test pipe is connected to the delivery side of blower along with orifice to measure flow of air through the pipe. Input to the heater through dimmer stat and measured by voltmeter and ammeter. Air flow is controlled by gate valve and is measured with the help of orifice meter and the manometer fitted on board. Specifications: Length of hallow pipe L = 0.6 m Pipe inner diameter Di = m Orifice diameter D o = m 3.2 Lay Out Of Experimental Setup Fig 3.2 Lay Out Of Experimental Setup Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 176

4 3.3 Data Acquisiton (DAQ) System Our DAQ system consists of an Arduino Duemilanove microcontroller and six DS18B20 sensors. The sensors are connected in Daisy chain arrangement and connected to the microcontroller using one wire bus. Another serial port application COOL TERM is used to display & save the data sent by these sensors. Fig 3.3 Sensors Connected to Arduino The main advantage of using the DAQ system to measure temp is the accuracy & flexibility. They have a very quick response time compared to thermocouple based system & can also function as a condition monitoring system. The data can be saved to an excel file as shown in fig Calculation of Heat Transfer Coefficient 1. Results obtained by experimental set up: Fig 3.4: Recorded Temperature T 1 = c, T 2 = c, T 3 = c, T 4 = c, Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 177

5 T 5 = c, T6 = c, H =.12 m T s = T2 +T 3 + T 4+ T 5 = c 4 T a = T 1+ T6 = 40.1 c 2 Properties of air: Density = 1.2 kg/m 3, γ= , K = 0.027, = 0.711, C p = kj/kg A i =area of inlet is 8.04 * 10-4 m 2 Discharge through orifice: Where = 0.65, is the area of orifice which is h a = (Density of water * head of water) = 1000 * 0.12 = 100 m Density of air 1.2 q = 0.65 * 2.01 * 10-4 * (2*9.81*100) = 5.79*10-3 m 3 /s Velocity V = (q/a) = 7.2 m/s Mass flow rate m = q * density of air = * 10-3 kg/s Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 178

6 Heat Carried by air: Q a = m * C p * dt = J/s A = π * D i * L = 0.06 m 2 Now, Q a = h A (T s - T a ) Therefore, h = Q a = = W/m 2 K A (T s - T a ) 0.06 * ( ) h = W/m 2 K 2. Result by correlation method In the correlation method, we use Dittus-Boelter eqn to obtain the value of Nusselt (Nu) number for the given system & with the eqn for Nu we obtain the heat transfer coefficient. R e = VD = 7.2 * = γ γ is kinematic viscosity obtained from data hand book properties of air which is. Using Dittus-Boelter eqn, = = We know,, where h is heat transfer coefficient, D is pipe inner diameter and k is thermal Conductivity of air at mean temperature obtained from properties Therefore, h = Nu * K = * = W/m 2 K D h = W/m 2 K Experimental h= W/m 2 K. Now validate the correlation using CFD simulation. Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 179

7 4. CFD Simulation 4.1 CFD Analysis of Pipe There are four basic steps involved in the CFD analysis of pipe. They are given as below: 1. Creating Geometry & meshing 2. Pre-processing 3. Solver 4. Post-processing 4.2 Geometry Model ANSYS ICEM is used to build a 3D geometry for CFD analysis. The geometry is created and Meshed using ANSYS ICEM CFD. The length of pipe is 600mm and inner diameter is 0.032m. 4.3 Meshing Fig. 4.1: Modelling of Pipe Using ICEM CFD The computational model is created in ICEM-CFD as per the dimensions shown in Figure 4.2. Later the Tetrahedral Mesh with Smooth Transition grid is generated. Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 180

8 Fig. 4.2: Mesh Generated Using ICEM CFD 4.4 CFD Simulation in FLUENT The computational model is created in ICEM-CFD as per the dimensions shown in Figure 4.1. Later the Tetrahedral Mesh with Smooth Transition grid is generated.the solver and the boundary conditions are specified in FLLUENT i.e. used segregated solver with asymmetric space and k-epsilon for turbulent modelling. The boundary conditions and reference values are shown below. Boundary Conditions: 1. Location = inlet Boundary details, subsonic Normal speed = 7.2 m/sec Medium intensity heat transfer Static temp = 310 k 2. Location outlet Boundary details Relative pressure = 1 Pa Wall Option: no slip wall,smooth wall Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 181

9 4.5 Results Fig 4.3 : Temperature Plane Fig 4.4: Temperature Plane Fig 4.5: Heat Transfer Coefficient Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 182

10 Fig 4.6: Heat Transfer Coefficient 5. Validation of Experimental, Cfd And Correlation Experimental h= W/m 2 K Correlation h= 34.29W/m 2 K CFD simulation h= 36.5 W/m 2 K (from fig 4.6) From this, we observe that the value obtained by CFD is very nearer to correlation and experimental hence Dittus- Boelter equation is validated. The primary objective of this work is to determine heat transfer coefficients (local and average) for different flow geometries and this heat transfer coefficient (h) may be obtained by experimental or theoretical methods. Theoretical methods involve solution of the boundary layer equations to get the Nusselt number. On the other hand the experimental methods involve performing heat transfer measurement under controlled laboratory conditions and correlating data in dimensionless parameters. Many correlations for finding the convective heat transfer coefficient are based on experimental data which needs uncertainty analysis, although the experiments are performed under carefully controlled conditions. The causes of the uncertainty are many. Actual situations rarely conform completely to the experimental situations for which the correlations are applicable. Whatever the value obtained by experimental, correlation and CFD simulation agree with each other with an error less than 10 %. Hence Dittus- Boelter has been validated 6. Conclusion By carrying out experiment, simulation and calculation, it is conclude that these correlations give an error well within the range 10 % and usually less in controlled environment. The results clearly validate the use of Dittus- Boelter correlation in many industrial applications. There are many reasons which contribute to the errors. The heat loss does account for errors, but the value of heat loss is negligible as compared to total heat flux. The heaters are local made and do not provide constant surface heat flux although it has been tried to control wattage of each heater. Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 183

11 Secondly all sensors (temperature) are attached in a close proximity of 220 V AC lines coming from heaters. Therefore signals from sensors are distorted and give an error. If somehow these problems are overcome results may improve. Another thing is correlation results must be more but here it is less because this has been taking the property of air at mean temperature of inlet and out let obtained by experiment. References [1] Dittus, F. W., and L. M. K. Boelter. University of California (Berkley) Pub. Eng., vol. 2. p. 443, [2] Holman, J. P., Heat Transfer, 9th edition, McGraw Hill, p [3] Diane L. Linne, Michael L. Meyer, Tim Edwards, and David A. Eitman. Evaluation of Heat Transfer and Thermal Stability of Supercritical JP 7 Fuel. NASA Technical Memorandum [4] Incropera, Fundamentals of Heat and Mass Transfer, 5th edition, John Wiley and Sons [5] J. R. Lamarsh& Anthony B., Intro to Nuclear Engineering, 3rd edition, Wiley [6] Munson, Young, Okishi, Fundamentals of Fluid Dynamics, 4th edition, Wiley [7] Incropera F. and D. De Witt. Fundamentals of Heat and Mass Transfer, 5th Edition, USA [8] Fand, R. M. and K. K. Keswani. A Continuous Correlation Equation for Heat Transfer from cylinders to Air in Crossflow for [9] Reynold s Numbers from 10-2 to 2(10)5, International Journal of Heat and Mass Transfer, 15: CFD Simulation & Experimental Verification of Air Flow through heated pipe. Jamuna A.B., Somashekar V. Moopanar karthikeyan, Raote Sarvesh, Sawant Rahul, Bhoi Sandesh, Prof. Madan Jagtap 184

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