Real-Time Determination of Convective Heat Transfer Coefficient Via Thermoelectric Modules

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Nataporn Korprasertsak ◽  
Thananchai Leephakpreeda
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Transfer Coefficients ◽  
Thermoelectric Modules ◽  
Heat Transfer Coefficients ◽  
Convective Heat Transfer Coefficients

In this paper, the determination of convective heat transfer coefficient under actual convection processes is proposed by using thermoelectric modules. The thermoelectric modules are positioned where cooling/heating processes take place. Based on the Seebeck effect and energy balance, voltage signals are mathematically related to the convective heat transfer coefficient in real time. In experiments, convective heat transfer coefficients of airflow in a wind tunnel are determined under heating/cooling processes at various wind speeds. The relative mean difference of the convective heat transfer coefficients between the proposed methodology and empirical formula is 2.31%. For real-time implementation, convective heat transfer coefficients of a copper plate, which is exposed to outdoor conditions during a whole day, are determined to predict copper plate temperatures from a governing equation. The performance of temperature prediction is confirmed by a coefficient of determination R2 of 0.9992. Analytical and experimental results show the effectiveness of the proposed thermoelectric modules in determining the convective heat transfer coefficient for air under actual cooling/heating conditions, in time.

Convective heat transfer under different jet impingement conditions – optimum design to spray parameters

2016 ◽  
Vol 68 (2) ◽  
pp. 242-249 ◽  
Author(s):  
Yanzhong Wang ◽  
Wentao Niu ◽  
Song Wei ◽  
Guanhua Song
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Spray Parameters ◽  
Transfer Coefficients ◽  
Content Type ◽  
Heat Transfer Coefficients

Purpose – This paper aims to improve the cooling performance of the impinging jet to the machining and power transmissions, and provides more parameters to the design of the cooling system. Design/methodology/approach – A multiphase flow model with heat transfer terms is established to calculate the convective heat transfer coefficient. The computational fluid dynamics method is used to simulate the jet flow. The convective heat transfer coefficients with different spray parameters are calculated and their variations are obtained. Temperatures are tested to reflect the cooling performance (convective heat transfer coefficients) with different spray parameters. Findings – The results show that the higher convective heat transfer coefficient can be obtained with the same flow rate by decreasing nozzle diameter while increasing either the number of nozzles or the oil supply pressure. The spray distance was found to have little influence on convective heat transfer; however, the more the spray is directed parallel to the surface, the higher the convective heat transfer coefficient. The computational results coincide well with the experimental results. Originality/value – The research presented here leads to a design reference guideline that could be used in machining and power transmissions to reduce the temperature, thus improving their quality and efficiency, and preventing failure at high speeds and/or under heavy loads.

scholarly journals Effects of ambient temperature, airspeed, and wind direction on heat transfer coefficient for the human body by means of manikin experiments and CFD analysis

2019 ◽  
Vol 111 ◽  
pp. 02041
Author(s):  
Shan Gao ◽  
Ryozo Ooka ◽  
Wonseok Oh
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Cfd Analysis ◽  
Standing Posture ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Convective Heat Transfer Coefficients

The purpose of this study is to confirm the effect of ambient temperature, airspeed, and wind direction on the heat transfer around the human body. A fixed surface temperature (33 °C) thermal manikin (TM) with 16 segments was employed. First, the manikin was placed in a climate chamber with ambient temperatures of 20 °C, 24 °C, and 28 °C, at airspeeds of less than 0.1 m/s to represent calm condition. Higher ambient temperatures led to a decrease in the convective heat transfer coefficient. The convective heat transfer coefficients for the sitting posture were higher than those of the standing posture. The same TM was then put in a wind tunnel with airspeeds ranging from 0.25 m/s to 1.4 m/s to represent forced convection. The TM was set to face upwind, downwind, and perpendicular to the wind (i.e., its right side facing the wind). Regression models for the convective heat transfer coefficient and airspeed for different wind directions and postures were derived. In contrast to the calm condition, the convective heat transfer coefficients for the sitting posture were lower than those for the standing posture. The convective heat transfer coefficients for the standing posture were largest when the TM was facing downwind, and smallest when the right side of the TM was facing the wind. To verify the results of the experiment, computational fluid dynamics (CFD) analysis was performed with conditions matching those of the experiment by using a computational TM with the same shape as that used in the experiment. The boundary conditions of the CFD analysis were set from the experiment. The CFD analysis results were consistent with the experimental data.

scholarly journals Determination of Heat Transfer Coefficients Over Ribbed Surfaces With Infrared Thermography

1997 ◽  
Author(s):  
Francisco P. Brójo ◽  
Luís C. Gonçalves ◽  
Pedro D. Silva
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Stanton Number ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients

The scope of the present work is to characterize the heat transfer between a ribbed surface and an air flow. The convective heat transfer coefficients, the Stanton number and the Nusselt number were calculated in the Reynolds number range, 5.13 × 105 to 1.02 × 106. The tests were performed inside a turbulent wind tunnel with one roughness height (e/Dh = 0.07). The ribs had triangular section with an attack angle of 60°. The surface temperatures were measured using an infrared (IR) thermographic equipment, which allows the measurement of the temperature with a good spatial definition (10.24 × 10−6 m2) and a resolution of 0.1°C. The experimental measures allowed the calculation of the convective heat transfer coefficient, the Stanton number and the Nusselt number. The results obtained suggested a flow pattern that includes both reattachment and recirculation. Low values of the dimensionless Stanton number, i.e. Stx*, are obtained at the recirculation zones and very high values of Stx* at the zones of reattachment. The reattachment is located at a dimensionless distance of 0.38 from the top of the rib. That distance seems to be independent of the Reynolds number. The local dimensionless Stanton number remains constant as the Reynolds number varies. The convective heat transfer coefficient presents an uncertainty in the range of 3 to 6%.

Convective Heat Transfer of Alumina Nanofluids in a Microchannel

2010 ◽  
Author(s):  
Saeid Vafaei ◽  
Dongsheng Wen
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Local Heat Transfer ◽  
Local Heat ◽  
Axial Distance ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients

This work reports an experimental study of convective heat transfer of aqueous alumina nanofluids in a horizontal microchannel under laminar flow condition. The variation of local heat transfer coefficients, in both entrance and developed flow regime, is obtained as a function of axial distance. The heat transfer coefficient of nanofluids is found to be dependent upon not only nanoparticle concentration but also mass flow rate. Different to the behavior in conventional-sized channels, the major heat transfer coefficient enhancement is observed in fully developed region in microchannels. Discussions of the results suggest that the heterogeneous nature of nanoparticle flow should be considered.

Experimental study on heat and mass transfer for heating milk

2011 ◽  
Vol 22 (3) ◽  
pp. 45-53
Author(s):  
Mahesh Kumar ◽  
K.S. Kasana ◽  
Sudhir Kumar ◽  
Om Prakash
Keyword(s):  
Heat Transfer ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Linear Regression Analysis ◽  
Convective Heat Transfer Coefficient ◽  
Simple Linear Regression ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Rate Of Heating ◽  
Convective Heat Transfer Coefficients

In this paper, an attempt has been made to estimate the convective heat transfer coefficient for sensible heating of milk in a stainless steel pot during khoa, made by traditional method. Various indoor experiments were performed for simulation of a developed thermal model for maximum evaporation by varying heat inputs from 240 watts to 420 watts. The experimental data was used to determine values of constants in the well known Nusselt expression by simple linear regression analysis and, consequently, convective heat transfer coefficients were determined. It is found that the convective heat transfer coefficients decrease with an increase in rate of heating. The experimental error in terms of percent uncertainty was also evaluated.

scholarly journals A determination methodology for the spatial profile of the convective heat transfer coefficient on building components

2016 ◽  
Vol 27 (4) ◽  
pp. 512-527 ◽  
Author(s):  
Evy Vereecken ◽  
Hans Janssen ◽  
Staf Roels
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Temperature Difference ◽  
Convective Heat Transfer Coefficient ◽  
Transfer Coefficients ◽  
Spatial Profile ◽  
Order Of Magnitude

Several experimental procedures have been established to determine the convective heat transfer coefficient, a frequently used parameter in many engineering disciplines. Almost all of these methodologies focus on point or spatially averaged values. Yet, in many studies the spatial profile of the local convective heat transfer is of importance. In this paper, a methodology to determine such spatial profile is proposed. In this method, experiments are combined with Monte Carlo simulations. Such an approach makes it possible to account for inaccuracies in the input data. As an example, the methodology is applied to determine the spatial profile of the local convective heat transfer coefficient near a corner for two thermal bridge configurations. The temperature difference between interior surface and indoor air is found to restrict the applicability of the method. Nonetheless, for the case with a sufficient temperature difference, the order of magnitude of the convective heat transfer coefficients further away from the corner is in line with literature data. An important limitation of the technique at this stage of its development is, however, its requirement for prior knowledge of the equation that describes the spatial profile of the convective heat transfer coefficient. Despite these drawbacks, the methodology shows much potential and can be valuable for other applications as well.

Parametric Study of Convective Heat Transfer Coefficients at the Tire Surface

1980 ◽  
Vol 8 (3) ◽  
pp. 37-67 ◽  
Author(s):  
A. L. Browne ◽  
L. E. Wickliffe
Keyword(s):  
Heat Transfer ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Thermal State ◽  
Convective Heat Transfer Coefficient ◽  
Operating Conditions ◽  
Test Facility ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Convective Heat Transfer Coefficients

Abstract Analyses have shown that the thermal state of a tire is influenced by both the size of and variation in the value of the convective heat transfer coefficient at the tire surface. In the work reported here, a test facility was constructed to permit the determination of convective heat transfer coefficients under a broad range of operating conditions. Data were obtained to show the effects of air speed, boundary layer thickness and turbulence level, humidity, tire surface contamination, tire surface roughness and unevenness, and tire surface wetness on convective heat transfer coefficients. The significance of these results to tire power loss is discussed.

DETERMINATION OF THE CONVECTIVE HEAT TRANSFER COEFFICIENT OF HOT AIR RISING THROUGH TERRACOTTA FLUES

2012 ◽  
Vol 36 (4) ◽  
pp. 413-427 ◽  
Author(s):  
Taylor A. Oetelaar ◽  
Clifton R. Johnston
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Numerical Study ◽  
Convective Heat Transfer Coefficient ◽  
Transfer Coefficients ◽  
Hot Air ◽  
Roman Baths

We experimentally studied natural convection processes inside terracotta flues as a part of a larger numerical study of ancient Roman baths. The air, heated in a plenum below the wall, rose through the tubes. Two clusters of thermocouples, equally spaced in the flues, measured temperatures throughout the thickness of the wall. The data from the two clusters proved to be measurably different. The resulting convective heat transfer coefficients determined using the bottom cluster, showed no dependence on the plenum temperature. The measured convective heat transfer coefficient was between 6.2 and 7.6 W/m2·°C, with an average of 7.0 W/m2·°C.

Experimental study on natural convection greenhouse drying of papad

2013 ◽  
Vol 24 (4) ◽  
pp. 37-43 ◽  
Author(s):  
Mahesh Kumar
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Linear Regression Analysis ◽  
Convective Heat Transfer Coefficient ◽  
Transfer Coefficients ◽  
Average Value

In this paper, the convective heat transfer coefficients of papad for greenhouse drying under a natural convection mode are reported. Various experiments were conducted during the month of April 2010 at Guru Jambheshwar University of Science and Technology Hisar, India (29o5’5” N 75o45’55” E). Experimental data obtained for the natural convection greenhouse drying of papad was used to evaluate the constants in the Nusselt number expression by using simple linear regression analysis. These values of the constant were used further to determine the values of the convective heat transfer coefficient. The average value of a convective heat transfer coefficient was determined as 1.23 W/m2 oC. The experimental error in terms of percent uncertainty was also evaluated.

Prediction of Velocities and Heat Transfer Coefficients in a Rotor-Stator Cavity

2004 ◽  
Author(s):  
Justin Evans ◽  
Lon M. Stevens ◽  
Clint Bodily ◽  
Moon-Kyoo Brian Kang
Keyword(s):  
Heat Transfer ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Turbulence Models ◽  
Secondary Flows ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Mesh Resolution ◽  
Convective Heat Transfer Coefficients

The calculation of swirl velocities and convective heat transfer coefficients in a rotor-stator cavity has been mostly based on equations taken from empirical data. However, the validity of these empirical relations is questionable in geometries and environments other than the specific ones for which they were derived. A commercial CFD code, Fluent, has been used to predict the swirl velocities and rotor disk convective heat transfer coefficient distribution for a rig at Arizona State University. The rig was run at several rotational Reynolds numbers (Reφ) varying from 4.6×105 to 8.6×105 and for various mass secondary flows. Several different turbulence models were used and the resulting predictions were compared with data obtained from the rig. Fluent was able to predict the swirl velocities, on average, within 30% and the convective heat transfer coefficients, on average, within 30% and often within 20%. The degree of agreement with the measured data was found to depend on which turbulence model that was used, mesh resolution, as well as the secondary flow and Reφ.

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