A semi-empirical model for estimating permeability and inertial coefficient of pin-fin heat sinks

2005 ◽  
Vol 48 (15) ◽  
pp. 3140-3150 ◽  
Author(s):  
Tzer-Ming Jeng ◽  
Sheng-Chung Tzeng
Keyword(s):  
Empirical Model ◽  
Heat Sinks ◽  
Pin Fin ◽  
Inertial Coefficient ◽  
Semi Empirical

A Semi-Empirical Heat Transfer Model for Forced Convection in Pin-Fin Heat Sinks Subjected to Nonuniform Heating

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
S. S. Feng ◽  
T. Kim ◽  
T. J. Lu
Keyword(s):  
Heat Transfer ◽  
Substrate Temperature ◽  
Analytical Model ◽  
Heat Sinks ◽  
Nonuniform Heating ◽  
Transfer Model ◽  
Substrate Thickness ◽  
Fluid Temperature ◽  
Pin Fin ◽  
Semi Empirical

This paper presents a cost effective semi-empirical analytical model for convective heat transfer in pin-fin heat sinks subjected to nonuniform heating set by a circular hot gas impinging jet. Based on empirical correlations taken from the open literature, temperature variations in the heat sink are obtained from the finite volume solution of the semi-empirical model. Based on a purpose-built experimental setup, measurements of a substrate temperature are performed using an infrared camera. These, along with the convective fluid temperature measured at the exit of the pin-fin array, are compared against analytical model predictions, with overall good agreement achieved. Subsequently, the influences of the convection Reynolds number, substrate thickness, and thermal conductivity of material on the distribution of substrate temperature are quantified by the validated model. It is demonstrated that the present model is capable of predicting local thermal behaviors such as the footprints of the pin fins. In addition, with the spreading resistance captured accurately, the model can be used for the design optimization of pin-fin/substrate systems subjected to nonuniform heating.

A Novel Semi-empirical Model for Evaluating Thermal Performance of Porous Metallic Foam Heat Sinks

2004 ◽  
Vol 127 (3) ◽  
pp. 223-234 ◽  
Author(s):  
Tzer-Ming Jeng ◽  
Li-Kang Liu ◽  
Ying-Huei Hung
Keyword(s):  
Heat Transfer ◽  
Liquid Crystal ◽  
Empirical Model ◽  
Aluminum Foam ◽  
Heat Sinks ◽  
Metallic Foam ◽  
Porous Aluminum ◽  
Transfer Behavior ◽  
Medium Porosity ◽  
Semi Empirical

A novel semi-empirical model with an improved single blow method for exploring the heat transfer performance of porous aluminum-foam heat sinks in a channel has been successfully developed. The influencing parameters such as the steady-state air preheating temperature ratio, Reynolds number and medium porosity on local and average heat transfer behavior of porous aluminum-foam heat sinks in a channel are explored. The heat transfer enhancement of using a porous heat sink in a channel to a hollow channel is, (Nu¯b)ss∕(Nu¯b)ε=1, much greater than unity and generally decrease with increasing Re. Furthermore, two new correlations of (Nu¯b)ss and (Nu¯i)ss in terms of ϴ,Re,Da,γ and ε are proposed. As compared with the results evaluated by the transient liquid crystal method, the channel wall temperatures predicted by the present semi-empirical model have a more satisfactory agreement with the experimental data, especially for the cases with smaller porosities. The limitations with relevant error maps of using the transient liquid crystal method in porous aluminum foam channels are finally postulated.

Optimization of Pin-Fin Heat Sinks for Impingement Cooling of Electronic Packages

2000 ◽  
Vol 122 (3) ◽  
pp. 240-246 ◽  
Author(s):  
Y. Kondo ◽  
H. Matsushima ◽  
T. Komatsu
Keyword(s):  
Cost Effective ◽  
Heat Sinks ◽  
Design Parameters ◽  
Air Cooling ◽  
Electronic Packages ◽  
Electronic Components ◽  
Impingement Cooling ◽  
Zonal Model ◽  
Pin Fin ◽  
Semi Empirical

Optimization of pin-fin heat sinks for impingement cooling of electronic components was studied. The study was based on a semi-empirical zonal model for determining thermal resistance as well as pressure drop. To test the validity of the model’s predictions, experiments and flow visualization were performed. The experimental results validated the model. The model enables cost-effective designs to be calculated in order to optimize pin-fin heat sinks. These calculations took into consideration 16 design parameters including pin diameter, minimum spacing between pins, and fin height. For the particular blower considered in our study, the optimum pin diameter was found being 0.35 mm. And the characteristics and limitations of air-cooling for such applications were investigated under various conditions. [S1043-7398(00)01704-7]

scholarly journals A Semi-Empirical Model for Predicting Frost Properties

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 412
Author(s):  
Shao-Ming Li ◽  
Kai-Shing Yang ◽  
Chi-Chuan Wang
Keyword(s):  
Thermal Conductivity ◽  
Linear Programming ◽  
Numerical Model ◽  
Empirical Model ◽  
Quantitative Method ◽  
Predictive Ability ◽  
Dimensionless Temperature ◽  
Crystal Shape ◽  
Proposed Model ◽  
Semi Empirical

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.

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