Fluid Flow and Heat Transfer Analysis of Automotive Radiator Using CFD Tools

2005 ◽  
Author(s):  
V. P. Malapure ◽  
A. Bhattacharya ◽  
Sushanta K. Mitra
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Temperature Drop ◽  
Three Dimensional ◽  
Heat Transfer Analysis ◽  
Coolant Temperature ◽  
Flow And Heat Transfer ◽  
Optimization Study

This paper presents a three-dimensional numerical analysis of flow and heat transfer over plate fins in a compact heat exchanger used as a radiator in the automotive industry. The aim of this study is to predict the heat transfer and pressure drop in the radiator. FLUENT 6.1 is used for simulation. Several cases are simulated in order to investigate the coolant temperature drop, heat transfer coefficient for the coolant and the air side along with the corresponding pressure drop. It is observed that the heat transfer and pressure drop fairly agree with experimental data. It is also found that the fin temperature depends on the frontal air velocity and the coolant side heat transfer coefficient is in good agreement with classical Dittus–Boelter correlation. It is also found that the specific dissipation increases with the coolant and the air flow rates. This work can further be extended to perform optimization study for radiator design.

Measurements and Numerical Simulations of Heat Transfer and Pressure Drop in a Duct With Smooth Walls

2017 ◽  
Author(s):  
Puxuan Li ◽  
Steve J. Eckels
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Numerical Models ◽  
Convective Heat Transfer Coefficient ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Inlet Temperature ◽  
Ansys Fluent

Accurate measurements of heat transfer and pressure drop play important roles in thermal designs in a variety of pipes and ducts. In this study, the convective heat transfer coefficient was measured with a semi-local surface average based on Newton’s Law of cooling. Flow and heat transfer data for different Reynolds numbers were collected and compared in a duct with smooth walls. Pressure drop was measured with a pressure transducer from OMEGA Engineering Inc. The experimental results were compared with numerical estimations generated in ANSYS Fluent. Fluent contains the broad physical modeling capabilities needed to model heat transfer and pressure drop in the duct. Thermal conduction and convection in the three-dimensional (3D) duct are simulated together. Special cares for selecting the viscosity models and the near-wall treatments are discussed. The goal of the paper is to find appropriate numerical models for simulating heat conduction, heat convection and pressure drop in the duct with different Reynolds numbers. The relationship between the heat transfer coefficient and Reynolds numbers is discussed. Heat flux and inlet temperature measured in the experiment are applied to the boundary conditions. The study provides the unique opportunity to verify the accuracy of numerical models on heat transfer and pressure drop in ANSYS Fluent.

Numerical and experimental analysis of microchannel heat transfer for nanoliquid coolant using different shapes and geometries

2014 ◽  
Vol 229 (11) ◽  
pp. 2056-2065 ◽  
Author(s):  
Harry Garg ◽  
Vipender Singh Negi ◽  
Nidhi Garg ◽  
AK Lall
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Fluid Flow ◽  
Transfer Coefficient ◽  
Experimental Analysis ◽  
High Heat ◽  
Heat Transfer Analysis ◽  
Flow And Heat Transfer ◽  
High Heat Transfer ◽  
High Heat Transfer Coefficient

As part of the liquid cooling, most of the work has been done on fluid flow and heat transfer analysis for flow field. In the present work, the experimental and numerical studies of the microchannel the fluid flow and heat transfer analysis using nanoliquid coolant have been discussed. The practical aspects for increasing the high heat transfer coefficient from conventional studies and the different geometries and shapes of the microchannel are studied. The Aspect Ratio has significant effect on the microchannels and has been varied from AR 2, 4 and 8 to choose the optimum one. Three different fluids, i.e. de-ionized water, ethylene glycol, and a custom nanofluid are chosen for study. The proposed nanofluid almost interacts as another solid and has reduced thermal resistance, friction effect, and thus it almost vanishes high hot spots. Experimental analysis shows that the proposed nanofluid is excellent fluid for high rate heat removals. Moreover, the performance of the overall system is excellent in terms of high heat transfer coefficient, high thermal conductivity, and high capacity of the fluid. It has been reported that the heat transfer coefficient can be increased to 2.5 times of the water or any other fluid. It was also reported that the AR 4 rectangular-shaped channels are the optimum geometry in the Reynolds number ranging from 50 to 800 considering laminar flow. Examination and identification is based upon the practical result that includes fabrication constraints, commercial application, sealing of the system, ease of operation, and so on.

Conjugate heat transfer from surface-mounted finite blunt plates

2006 ◽  
Vol 220 (1) ◽  
pp. 83-94 ◽  
Author(s):  
M Yaghoubi ◽  
E Velayati
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Three Dimensional ◽  
Leading Edge ◽  
Fin Efficiency ◽  
Flow And Heat Transfer ◽  
Flow Reynolds Number ◽  
The Heat Transfer Coefficient

Numerical studies of fluid flow and heat transfer are made in the separated, reattached, and redeveloped regions of the three-dimensional air flow on an array of finite plates with blunt leading edge. The flow reattachment occurs at a place downstream from the leading edge and the heat transfer coefficient becomes maximum around this region. The heat transfer coefficient is found to increase sharply near the leading edge and reduces in the wake. For the range of the parameters investigated in this study, some correlations have been developed for the length of reattachment region and variation of overall heat transfer coefficient for the considered bluff obstacles with various geometry and flow Reynolds number. For such blunt plates, when they are acting like fins, fin efficiency is determined and a relation based on flow Reynolds number and geometric parameters is developed to predict variation of the overall fin efficiency.

THREE-DIMENSIONAL HEAT TRANSFER ANALYSIS OF HOT GAS TORCH (HGT)-ASSISTED AUTOMATED FIBER PLACEMENT OF THERMOPLASTIC COMPOSITES

2021 ◽  
Author(s):  
LORENZ ZACHERL ◽  
ALLYSON FONTES ◽  
FARJAD SHADMEHRI
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Three Dimensional ◽  
Heat Transfer Analysis ◽  
Thermoplastic Composites ◽  
Hot Gas

In-situ manufacturing of thermoplastic composites using the Automated Fiber Placement (AFP) process consists of heating, consolidation, and solidification steps. During the heating step using Hot Gas Torch (HGT) as a moving heat source, the incoming tape and the substrate are heated up to a temperature above the melting point of the thermoplastic matrix. The convective heat transfer occurs between the hot gas flow and the composites in which the convective heat transfer coefficient h plays an important role in the heat transfer mechanism, which in turn significantly affects temperature distribution along the length, width, and through the thickness of the deposited layers. Temperature is the most important process parameter in AFP in-situ consolidation that affects bonding quality, crystallization, and consolidation. Although it is well known that the convective heat transfer coefficient h is not constant and has a distribution, most studies have assumed a constant value for h for heat transfer analysis, which leads to discrepancies between numerical and experimental results. It has already been shown by the authors that, unlike other studies assuming constant h value, using a distribution function to approximate the convective heat transfer coefficient h in a three-dimensional finite element transient heat transfer analysis the temperature distribution can be well predicted in thermoplastic composite parts and matches experimental data. In this study, the use of the proposed h distribution function is analysed and validated by several measuring points. Furthermore, experimental trials are carried out to validate the results from the simulation.

Supercritical Heat Transfer and Pressure Drop in Refrigerant R410A

2003 ◽  
Author(s):  
Biswajit Mitra ◽  
Srinivas Garimella
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Cooling Water ◽  
Local Heat Transfer ◽  
Local Heat ◽  
Coolant Temperature ◽  
Transfer Coefficients ◽  
Water Stream

This paper presents the results of an experimental study on heat transfer and pressure drop at critical and supercritical pressures of refrigerant R410A inside a horizontal 9.4 mm I.D. tube. Knowledge of heat transfer and pressure drop in such refrigerants blends at elevated pressures is gaining increasing attention for the design of vapor-compression space-conditioning and water heating systems at high heat rejection temperatures. Local heat transfer coefficients and pressure drops were measured for the mass flux range 200 < G < 800 kg/m2-s for the temperature range from 30–110°C. A technique that simultaneously allows accurate measurement of low local heat duties and deduction of the tube-side heat transfer coefficient from the measured overall resistance was used. A primary cooling loop using water at high flow rates ensures that the refrigerant side presents the governing thermal resistance. Heat exchange with a secondary cooling water stream at a much lower flow rate amplifies the coolant temperature difference, which in turn enables accurate heat duty measurements. The results show that the heat transfer coefficient exhibits a sharp peak in the vicinity of the vapor-liquid dome. These data are compared with the most relevant correlations from the literature and possible explanations for agreement and discrepancies between the data and predictions are provided.

Three-dimensional inverse heat transfer analysis during the grinding process

2002 ◽  
Vol 216 (2) ◽  
pp. 199-212 ◽  
Author(s):  
C-C Wang ◽  
C-K Chen
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Heat Source ◽  
Transfer Coefficient ◽  
Three Dimensional ◽  
Heat Transfer Analysis ◽  
Grinding Process ◽  
Workpiece Surface ◽  
Inverse Heat Transfer ◽  
Error Method

A three-dimensional inverse analysis is adopted to estimate the unknown conditions on the workpiece surface during a grinding process. The numerical method (linear least-squares error method) requires just one iteration and can solve the inverse problems given only the temperature information at a finite number of locations beneath the working surface within a specified time domain. Results show that the heat source into the grinding zone and the heat transfer coefficient in the cooling region can be obtained by the proposed method even when under the influence of measured errors. Furthermore, it is found that the estimated heat transfer coefficient is more sensitive than the heat source to different measured errors and depths. Analyses of the temperature, heat distribution and heat transfer coefficient of the workpiece will help prevent the occurrence of thermal damage to the workpiece, which are caused by the high temperatures generated during the grinding process.

Novel Arrangement of Rough Tubes for Heat Flux Improvement

2012 ◽  
Vol 326-328 ◽  
pp. 81-86
Author(s):  
Farshad Farahbod ◽  
Sara Farahmand ◽  
Farzaneh Farahbod
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Crude Oil ◽  
Transfer Coefficient ◽  
Three Dimensional ◽  
Operating Conditions ◽  
Set Up ◽  
The Heat Transfer Coefficient

The objective of the research is to represent a novel arrangement of conical three dimensional rough tubes (FS3D) for heat transfer coefficient enhancement. Experiments were performed with 316 stainless steel tubes of FS3D roughness and hot crude oil was circulated in constant heat flux condition in the related set up. The pressure drop is measured in this set up and compared with the pressure drop in a smooth tube with the same operating conditions. The heat transfer coefficient is one of essential parameters for design of heat transfer equipments and in this experimental work this is investigated for an Iranian crude oil in the FS3D rough tube. The heat transfer coefficient in FS3D rough tubes is higher than in other commercial enhanced tubes. FS3D rough tubes improve the performance of heat transfer equipments and also optimize the size of the mentioned devices. Consequently this type, the FS3D rough tube, is advantageous in energy and cost saving.

scholarly journals Local Heat Transfer and Pressure Drop in a Rotating Two-Pass Ribbed Rectangular Channel

2001 ◽  
Vol 7 (3) ◽  
pp. 183-194 ◽  
Author(s):  
Shou-Shing Hsieh ◽  
Hsiu-Cheng Liao
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Aspect Ratio ◽  
Transfer Coefficient ◽  
Rectangular Channel ◽  
Three Dimensional ◽  
Local Heat Transfer ◽  
Local Heat ◽  
Uneven Heating

The influences of rotation and uneven heating condition as well as passage aspect ratio on the local heat transfer coefficient and pressure drop in a rotating, two pass ribroughened (rib heighte/DH≈0.27; rib pitchp/e=8) rectangular channel with a crosssection aspect ratio of 3 was studied for Reynolds numbers from 5000 to 25,000 and rotation numbers from 0 to 0.24. Regionally averaged Nusselt number variations along the duct have been determined over the trailing and leading surfaces for two pass straight channels and U-bend region. Implementing with the data from Hsieh and Liu (1996) forAR=1and 1.5 withp/e=5ande/DH=0.17and 0.20, passage aspect ratio effect was further examined. Furthermore, data for180∘U-bend region with ribroughened turbulator on heat transfer were also measured. It was found that a complicated three-dimensional accelerated flow and secondary flow in this U-bend region caused higher heat transfer on both leading/trailing walls. Enhancement performance ratios are also presented and discussed. Results again indicate a slight decrease in heat transfer coefficient for an increase in passage aspect ratio as compared to those of previous studies.

Development of a New Correlation and Post Processing of Heat Transfer Coefficient and Pressure Drop of Functionalized COOH MWCNT Nanofluid by Artificial Neural Network

2018 ◽  
Vol 14 (2) ◽  
pp. 104-112 ◽  
Author(s):  
Mohammad Hemmat Esfe ◽  
Somchai Wongwises ◽  
Saeed Esfandeh ◽  
Ali Alirezaie
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Thermal Conductivity ◽  
Artificial Neural Network ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Regression Coefficient ◽  
New Correlation ◽  
The Neural Network

Background: Because of nanofluids applications in improvement of heat transfer rate in heating and cooling systems, many researchers have conducted various experiments to investigate nanofluid's characteristics more accurate. Thermal conductivity, electrical conductivity, and heat transfer are examples of these characteristics. Method: This paper presents a modeling and validation method of heat transfer coefficient and pressure drop of functionalized aqueous COOH MWCNT nanofluids by artificial neural network and proposing a new correlation. In the current experiment, the ANN input data has included the volume fraction and the Reynolds number and heat transfer coefficient and pressure drop considered as ANN outputs. Results: Comparing modeling results with proposed correlation proves that the empirical correlation is not able to accurately predict the experimental output results, and this is performed with a lot more accuracy by the neural network. The regression coefficient of neural network outputs was equal to 99.94% and 99.84%, respectively, for the data of relative heat transfer coefficient and relative pressure drop. The regression coefficient for the provided equation was also equal to 97.02% and 77.90%, respectively, for these two parameters, which indicates this equation operates much less precisely than the neural network. Conclusion: So, relative heat transfer coefficient and pressure drop of nanofluids can also be modeled and estimated by the neural network, in addition to the modeling of nanofluid’s thermal conductivity and viscosity executed by different scholars via neural networks.

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