hADIABATIC and u’MAX

2003 ◽  
Author(s):  
Robert J. Moffat
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Electronics Cooling ◽  
Adiabatic Temperature ◽  
Preliminary Design ◽  
Mean Temperature ◽  
Mixed Mean ◽  
The Heat Transfer Coefficient

In all electronics cooling situations, and many other practical situations, the surface temperature varies in the stream-wise direction. In these cases, defining the heat transfer coefficient using the adiabatic temperature of the surface instead of the mixed mean temperature of the coolant result in significant benefits. The resulting definition is hadiabatic. The theoretical and practical bases for hadiabatic are presented. Examples of its use in electronics cooling are described to show the operational advantages this approach offers. Turbulence strongly affects heat transfer. A simple, turbulence-based correlation is presented that yields an estimate of the heat transfer coefficient good enough for preliminary design estimates and often as accurate as can be relied upon from CFD calculations using present codes.

h adiabatic and umax′

2004 ◽  
Vol 126 (4) ◽  
pp. 501-509 ◽  
Author(s):  
Robert J. Moffat
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Flow Characteristics ◽  
Electronics Cooling ◽  
Preliminary Design ◽  
Streamwise Direction ◽  
Root Cause ◽  
Mixed Mean ◽  
The Heat Transfer Coefficient

In all electronics cooling situations, and many other practical situations, the surface temperature may vary rapidly in the streamwise direction. In these cases, defining the heat transfer coefficient using the adiabatic temperature of the surface instead of the mixed mean temperature of the coolant results in significant benefits. The resulting coefficient, called hadiabatic, is well behaved, being a function only of the geometry and flow characteristics. Calling attention to Tadiabatic, as opposed to Tmean, helps designers identify the root cause of overheating problems and more quickly reach good solutions. The theoretical and practical bases for hadiabatic are presented. Examples of its use in electronics cooling are described to show the operational advantages this approach offers. Turbulence strongly affects heat transfer. A simple, turbulence-based correlation is presented that yields an estimate of the heat transfer coefficient good enough for preliminary design estimates and often as accurate as can be relied on from CFD calculations using present codes.

High Resolution Heat Transfer Measurements on the Stator Endwall of an Axial Turbine

2014 ◽  
Vol 137 (4) ◽  
Author(s):  
Benoit Laveau ◽  
Reza S. Abhari ◽  
Michael E. Crawford ◽  
Ewald Lutum
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
High Resolution ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Mass Flow ◽  
Wall Temperature ◽  
Adiabatic Wall ◽  
Axial Turbine ◽  
The Heat Transfer Coefficient

In order to continue increasing the efficiency of gas turbines, an important effort is made on the thermal management of the turbine stage. In particular, understanding and accurately estimating the thermal loads in a vane passage is of primary interest to engine designers looking to optimize the cooling requirements and ensure the integrity of the components. This paper focuses on the measurement of endwall heat transfer in a vane passage with a three-dimensional (3D) airfoil shape and cylindrical endwalls. It also presents a comparison with predictions performed using an in-house developed Reynolds-Averaged Navier–Stokes (RANS) solver featuring a specific treatment of the numerical smoothing using a flow adaptive scheme. The measurements have been performed in a steady state axial turbine facility on a novel platform developed for heat transfer measurements and integrated to the nozzle guide vane (NGV) row of the turbine. A quasi-isothermal boundary condition is used to obtain both the heat transfer coefficient and the adiabatic wall temperature within a single measurement day. The surface temperature is measured using infrared thermography through small view ports. The infrared camera is mounted on a robot arm with six degrees of freedom to provide high resolution surface temperature and a full coverage of the vane passage. The paper presents results from experiments with two different flow conditions obtained by varying the mass flow through the turbine: measurements at the design point (ReCax=7.2×105) and at a reduced mass flow rate (ReCax=5.2×105). The heat transfer quantities, namely the heat transfer coefficient and the adiabatic wall temperature, are derived from measurements at 14 different isothermal temperatures. The experimental data are supplemented with numerical predictions that are deduced from a set of adiabatic and diabatic simulations. In addition, the predicted flow field in the passage is used to highlight the link between the heat transfer patterns measured and the vortical structures present in the passage.

scholarly journals Heat Transfer Determined by the Temperature Sensitive Paint Method

2018 ◽  
Vol 2018 (4) ◽  
pp. 45-57
Author(s):  
Łukasz Jeziorek ◽  
Krzysztof Szafran ◽  
Paweł Skalski
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Thermal Power ◽  
Test Method ◽  
Temperature Sensitive ◽  
Complex Objects ◽  
Temperature Sensitive Paint ◽  
The Heat Transfer Coefficient

Abstract The paper presents practical aspects of determining the amount of heat flow by measuring the distribution of surface temperature using the Temperature Sensitive Paint (TSP) method. The quantity measured directly with TSP is the intensity of the excited radiation, which is then converted to surface temperature. The article briefly presents three different methods for determining the heat transfer coefficient. Each of these methods is based on a separate set of assumptions and significantly influences the construction of the measuring station. The advantages of each of the presented methods are their individual properties, allowing to improve accuracy, reduce the cost of testing or the possibility of using them in tests of highly complex objects. For each method a mathematical model used to calculate the heat transfer coefficient is presented. For the steady state heat transfer test method that uses a heater of constant and known thermal power, examples of the results of our own research are presented, together with a comparison of the results with available data and a discussion of the accuracy of the results obtained.

Comparison of Surface Heat-Transfer Coefficient of GCr15 Steel Quenched by Clear Water and Nitrogen-Spray Water

2013 ◽  
Vol 444-445 ◽  
pp. 1290-1294
Author(s):  
Li Jun Hou ◽  
He Ming Cheng ◽  
Jian Yun Li ◽  
Bao Dong Shao ◽  
Jie Hou
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Thermal Stresses ◽  
Surface Heat ◽  
Water Quenching ◽  
Surface Heat Transfer ◽  
Surface Heat Transfer Coefficient ◽  
The Heat Transfer Coefficient

In order to simulate the thermal stresses, thermal strains and residual stresses of steel during quenching by numerical means, it is necessary to obtain an accurate boundary condition of temperature field. The explicit finite difference method, nonlinear estimate method and the experimental relation between temperature and time during water and nitrogen-spray water quenching have been used to solve the inverse problem of heat conduction. The relations between surface heat-transfer coefficient in water and nitrogen-spray water quenching and surface temperature of cylinder have been given. In numerical calculation, the thermal physical properties of material were treated as the function of temperature. The results show that the relations between surface heat-transfer coefficient and surface temperature are non-linear during water and nitrogen-spray water quenching, the heat-transfer coefficient is bigger when water quenching than when nitrogen-spray water before 580°C, the heat-transfer coefficient is smaller when water quenching than when nitrogen-spray water after 400°C. The results of calculation coincided with the results of experiment. This method can effectively determine the surface heat-transfer coefficient during water and nitrogen-spray water quenching.

High Resolution Heat Transfer Measurements on the Stator Endwall of an Axial Turbine

2014 ◽  
Author(s):  
Benoit Laveau ◽  
Reza S. Abhari ◽  
Michael E. Crawford ◽  
Ewald Lutum
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
High Resolution ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Mass Flow ◽  
Wall Temperature ◽  
Adiabatic Wall ◽  
Axial Turbine ◽  
The Heat Transfer Coefficient

In order to continue increasing the efficiency of gas turbines, an important effort is made on the thermal management of the turbine stage. In particular understanding and accurately estimating the thermal loads in a vane passage is of primary interest to engine designers looking to optimize the cooling requirements and ensure the integrity of the components. This paper focuses on the measurement of endwall heat transfer in a vane passage with a 3D airfoil shape and cylindrical endwalls. It also presents a comparison with predictions performed using an in-house developed RANS solver featuring a specific treatment of the numerical smoothing using a flow adaptive scheme. The measurements have been performed in a steady state axial turbine facility on a novel platform developed for heat transfer measurements and integrated to the nozzle guide vane row of the turbine. A quasi-isothermal boundary condition is used to obtain both the heat transfer coefficient and the adiabatic wall temperature within a single measurement day. The surface temperature is measured using infrared thermography through small view ports. The infrared camera is mounted on a robot-arm with six degrees of freedom to provide high resolution surface temperature and a full coverage of the vane passage. The paper presents results from experiments with two different flow conditions obtained by varying the mass flow through the turbine: measurements at the design point (ReCax = 7,2.105) and at a reduced mass flow rate (ReCax = 5,2.105). The heat transfer quantities, namely the heat transfer coefficient and the adiabatic wall temperature, are derived from measurements at 14 different isothermal temperatures. The experimental data are supplemented with numerical predictions that are deduced from a set of adiabatic and diabatic simulations. In addition, the predicted flow field in the passage is used to highlight the link between the heat transfer patterns measured and the vortical structures present in the passage.

On Selection of Reference Temperature of Heat Transfer Coefficient for Complicated Flows

2007 ◽  
Author(s):  
X. C. Li ◽  
J. Zhou ◽  
K. Aung
Keyword(s):  
Heat Transfer ◽  
Heat Flux ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Wall Temperature ◽  
Convective Heat Transfer Coefficient ◽  
Internal Heat ◽  
Reference Temperature ◽  
The Heat Transfer Coefficient

One of the most fundamental concepts in heat transfer is the convective heat transfer coefficient, which is closely related with the flow Reynolds number, flow geometry and the thermal conditions on the heat transfer surface. To define the heat transfer coefficient, a reference temperature is needed besides the surface temperature and heat flux. The reference temperature can be chosen differently, such as the fluid bulk mean temperature (for internal flows) and the temperature at the far field (for external flows). For complicated flows, the adiabatic wall temperature, defined as the wall temperature when the surface heat flux is zero, is commonly adopted as the reference temperature. Other options can also be applied to complicated flows. This paper analyzed some of the potential selections of the reference temperature for different flow settings, including film cooling, jet impingement with cross flows and a mixing flow in a straight duct with or without internal heat source. Both laminar and turbulent flows are considered with different boundary conditions. Dramatic changes of heat transfer coefficient are observed with different reference temperatures. In some special conditions the heat transfer coefficient becomes negative, which means the heat flux has a different direction with the driving temperature difference defined. An innovative method is proposed to calculate the heat transfer coefficient of complicated flows with constant surface temperature.

Applying Heat Transfer Coefficient Data to Electronics Cooling

1990 ◽  
Vol 112 (4) ◽  
pp. 882-890 ◽  
Author(s):  
R. J. Moffat ◽  
A. M. Anderson
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Heat Release ◽  
Data Base ◽  
Electronics Cooling ◽  
Superposition Method ◽  
Air Cooling ◽  
Fluid Temperature ◽  
The Heat Transfer Coefficient

Many electronics cooling applications involve direct air cooling of the components and their heat transfer performance is often estimated, in the design phase, using heat transfer coefficient data from either in-house data or published sources. The agreement between predicted and observed system performance is quite often not acceptable, which means that the cooling system must be developed empirically—an expensive and time-consuming process. The authors believe they have identified one important reason for this state of affairs: the heat transfer coefficient values presented in the literature are being used improperly. Almost all of the published heat transfer coefficient data are from single-active-component experiments, which implicitly define h based on the adiabatic temperature of the component (had), while most users assume h to be defined on the basis of the mean fluid temperature (hm). This misunderstanding leads to underpredictions of the temperature rise of the components by 20–30 percent or more. This paper reviews the options for defining the heat transfer coefficient, shows how the problem arises, and then describes the steps necessary to properly use the existing heat transfer coefficient data base. There are two options for applying the existing data base to a fully powered array: One can either calculate the adiabatic temperatures of the components from the known heat release distribution in the array or calculate the values of hm that can be used with Tm, again using the known heat release distribution. The two options represent different ways to apply the same general method, superposition. The superposition method of Sellars, et al., (1956) is adapted to discrete systems and used as a guide to the forms recommended.

Numerical Simulation to Determine the Heat Transfer Coefficient in the Boiling Phenomenon of Run-Out Table of a Hot Strip Mill

2003 ◽  
Author(s):  
S. Sikdar ◽  
A. Mukhopadhyay
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Temperature Profile ◽  
Hot Strip Mill ◽  
Simple Correlation ◽  
Strip Surface ◽  
Hot Strip ◽  
The Heat Transfer Coefficient

A Mathematical model has been developed to predict the temperature profile of the strip in the Run-out Table (ROT) of the Hot Strip Mill (HSM) at Tata Steel, India. The prediction of temperature profile across the thickness of the strip shows good results. A simple correlation for heat transfer coefficient has emerged from this study. A polynomial as a function of strip surface temperature has been found to represent the heat transfer coefficient at water-strip interface accurately. The salient features of this paper are described as follows: 1) An off-line model has been developed to predict the through thickness temperature of the strip in the Run-out Table of a Hot Strip Mill. 2) The heat transfer coefficient at water-strip interface on the water-cooled zone over the bed of Run-out Table can be considered as a polynomial of strip surface temperature. Tests have been performed to validate the correlation of heat transfer coefficient against several thousand coils.

Effects of Vapor Velocity and Pressure on Marangoni Condensation of Steam-Ethanol Mixtures on a Horizontal Tube

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Hassan Ali ◽  
Hua Sheng Wang ◽  
Adrian Briggs ◽  
John W. Rose
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Surface Temperature ◽  
Transfer Coefficient ◽  
Temperature Difference ◽  
Atmospheric Pressure ◽  
Optimum Composition ◽  
Diffusion Resistance ◽  
Vapor Velocity ◽  
The Heat Transfer Coefficient

Careful heat-transfer measurements have been conducted for condensation of steam-ethanol mixtures flowing vertically downward over a horizontal, water-cooled tube at pressures ranging from around atmospheric down to 14 kPa. Care was taken to avoid error due to the presence of air in the vapor. The surface temperature was accurately measured by embedded thermocouples. The maximum vapor velocity obtainable was limited by the maximum electrical power input to the boiler. At atmospheric pressure this was 7.5 m/s while at the lowest pressure a velocity of 15.0 m/s could be achieved. Concentrations of ethanol by mass in the boiler when cold prior to start up were 0.025%, 0.05%, 0.1%, 0.5%, and 1.0%. Tests were conducted for a range of coolant flow rates. Enhancement of the heat-transfer coefficient over pure steam values was found by a factor up to around 5, showing that the decrease in thermal resistance of the condensate due to Marangoni condensation outweighed diffusion resistance in the vapor. The best performing compositions (in the liquid when cold) depended on vapor velocity but were in the range 0.025–0.1% ethanol in all cases. For the atmospheric pressure tests the heat-transfer coefficient for optimum composition, and at a vapor-to-surface temperature difference of around 15 K, increased from around 55 kW/m2 K to around 110 kW/m2 K as the vapor velocity increased from around 0.8 to 7.5 m/s. For a pressure of 14 kPa the heat-transfer coefficient for optimum composition, and at a vapor-to-surface temperature difference of around 9 K, increased from around 70 kW/m2 K to around 90 kW/m2 K as the vapor velocity increased from around 5.0 to 15.0 m/s. Photographs showing the appearance of Marangoni condensation on the tube surface under different conditions are included in the paper.

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