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.

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.

The Design of Transient Wall Heating Experiments for the Determination of Convective Heat Transfer Using Liquid Crystal Thermography

2000 ◽  
Author(s):  
David Graham ◽  
Jeff Rhine
Keyword(s):  
Heat Transfer ◽  
Liquid Crystal ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Operating Conditions ◽  
Transfer Coefficients ◽  
Liquid Crystal Thermography ◽  
Heat Transfer Coefficients ◽  
Wall Heating ◽  
Convective Heat Transfer Coefficients

The use of liquid crystals as surface temperature sensors in transient wall heating experiments, to measure steady-state convective heat transfer coefficients, is becoming increasingly popular. This paper describes a simple graphical method to assist in the design of these experiments. The analysis assumes that the test specimen, perspex in the given example, behaves as a semi-infinite solid. Given an expected range of convective heat transfer coefficients, the experimenter can determine the optimum combination of liquid crystal colour change temperature, bounding wall thickness and experiment duration. It is also possible to determine the sensitivity of experimental uncertainty to the operating conditions and the physical properties of the bounding wall. Emphasis is given to the use of liquid crystal thermography but the methodology could be applied when other temperature measurement devices are employed.

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.

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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