scholarly journals Prediction of nucleate pool boiling heat transfer coefficient

Thermal Science â—½  
2010 â—½  
Vol 14 (2) â—½  
pp. 353-364 â—½  
Author(s):  
Alangar Sathyabhama â—½  
Ramakrishna Hegde
Keyword(s):  
Heat Transfer â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Boiling Heat Transfer â—½  
Pool Boiling â—½  
Correct Prediction â—½  
Nucleate Pool Boiling â—½  
Successful Operation â—½  
Refrigeration Unit â—½  
Boiling Heat Transfer Coefficient

The correct prediction of the heat transfer performance of the boiling liquid within the evaporator of a refrigeration unit is one of the essential features for the successful operation of the whole unit. There are many correlations available in the literature for the prediction of boiling heat transfer coefficient of pure components. Eight heat transfer pool-boiling correlations that are well known in the literature have been selected and their prediction accuracy has been assessed against experimental data of ammonia available in the literature. The analysis concludes that within the investigated ranges of boiling conditions, the Kruzhilin, Kutateladze, Labuntsov, Mostinski nucleate pool-boiling correlations are the most accurate among those assessed.

scholarly journals Experimental studies on nucleate pool boiling heat transfer to ethanol/MEG/DEG ternary mixture as a new coolant

2012 â—½  
Vol 18 (4-1) â—½  
pp. 577-586 â—½  
Author(s):  
M.M. Sarafraz â—½  
S.M. Peyghambarzadeh â—½  
Alavi Fazel
Keyword(s):  
Heat Transfer â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Boiling Heat Transfer â—½  
Ternary Mixture â—½  
Pool Boiling â—½  
Heat Fluxes â—½  
Nucleate Pool Boiling â—½  
Pool Boiling Heat Transfer â—½  
Boiling Heat Transfer Coefficient

In this paper, nucleate pool boiling heat transfer coefficient of ternary mixtures of ethanol, monoethylene glycol (MEG) and diethylene glycol (DEG) as a new coolant with higher heat transfer coefficient has been investigated. Therefore, at varied concentrations of MEG and DEG and also at different heat fluxes, pool boiling heat transfer coefficients, have been experimentally measured. Results demonstrated the higher heat transfer coefficient in comparison with Water/MEG/DEG ternary mixture. In particular, at high heat fluxes, for ethanol/MEG/DEG mixture, higher boiling heat transfer coefficient is reported. Besides, experimental data were compared to well-known existing correlations. Results of this comparison express that the most accurate correlation for predicting the heat transfer coefficient of ethanol/MEG/DEG is modified Stephan - Preu?er which has been obtained in our earlier work.

Experimental study of the effect of various surfactants on surface sediment and pool boiling heat transfer coefficient of silica/DI water nano-fluid

Powder Technology â—½  
2019 â—½  
Vol 356 â—½  
pp. 391-402 â—½  
Author(s):  
Zhe Tian â—½  
Sasan Etedali â—½  
Masoud Afrand â—½  
Ali Abdollahi â—½  
Marjan Goodarzi
Keyword(s):  
Heat Transfer â—½  
Experimental Study â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Surface Sediment â—½  
Boiling Heat Transfer â—½  
Pool Boiling â—½  
Pool Boiling Heat Transfer â—½  
Nano Fluid â—½  
Boiling Heat Transfer Coefficient

scholarly journals Quantitative Evaluation of the Dependence of Pool Boiling Heat Transfer Enhancement on Sintered Particle Coating Characteristics

10.1115/1.4034901 â—½  
2016 â—½  
Vol 139 (2) â—½  
Author(s):  
Suchismita Sarangi â—½  
Justin A. Weibel â—½  
Suresh V. Garimella
Keyword(s):  
Heat Transfer â—½  
Thermal Conductivity â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Boiling Heat Transfer â—½  
Pool Boiling â—½  
Transfer Enhancement â—½  
Pool Boiling Heat Transfer â—½  
Boiling Heat Transfer Coefficient â—½  
Coating Characteristics

Immersion cooling strategies often employ surface enhancements to improve the pool boiling heat transfer performance. Sintered particle/powder coatings have been commonly used on smooth surfaces to reduce the wall superheat and increase the critical heat flux (CHF). However, there is no unified understanding of the role of coating characteristics on pool boiling heat transfer enhancement. The morphology and size of the particles affect the pore geometry, permeability, thermal conductivity, and other characteristics of the sintered coating. In turn, these characteristics impact the heat transfer coefficient and CHF during boiling. In this study, pool boiling of FC-72 is experimentally investigated using copper surfaces coated with a layer of sintered copper particles of irregular and spherical morphologies for a range of porosities (∼40–80%). Particles of the same effective diameter (90–106 μm) are sintered to yield identical coating thicknesses (∼4 particle diameters). The porous structure formed by sintering is characterized using microcomputed tomography (μ-CT) scanning to study the geometric and effective thermophysical properties of the coatings. The boiling performance of the porous coatings is analyzed. Coating characteristics that influence the boiling heat transfer coefficient and CHF are identified and their relative strength of dependence analyzed using regression analysis. Irregular particles yield higher heat transfer coefficients compared to spherical particles at similar porosity. The coating porosity, pore diameter, unit necking area, unit interfacial area, effective thermal conductivity, and effective permeability are observed to be the most critical coating properties affecting the boiling heat transfer coefficient and CHF.

scholarly journals Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces

Sustainability â—½  
10.3390/su132212631 â—½  
2021 â—½  
Vol 13 (22) â—½  
pp. 12631
Author(s):  
Uzair Sajjad â—½  
Imtiyaz Hussain â—½  
Muhammad Sultan â—½  
Sadaf Mehdi â—½  
Chi-Chuan Wang â—½  
...  
Keyword(s):  
Heat Transfer â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Thermophysical Properties â—½  
Boiling Heat Transfer â—½  
Pool Boiling â—½  
Morphological Features â—½  
Porous Surfaces â—½  
Boiling Heat Transfer Coefficient â—½  
Influential Parameters

The boiling heat transfer performance of porous surfaces greatly depends on the morphological parameters, liquid thermophysical properties, and pool boiling conditions. Hence, to develop a predictive model valid for diverse working fluids, it is necessary to incorporate the effects of the most influential parameters into the architecture of the model. In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. The optimized model is then employed to perform sensitivity analysis for finding the most influential parameters in the boiling heat transfer assessment of sintered coated porous surfaces on copper substrate subjected to a variety of high- and low-wetting working fluids, including water, dielectric fluids, and refrigerants, under saturated pool boiling conditions and different surface inclination angles of the heater surface. The model with all the surface morphological features, liquid thermophysical properties, and pool boiling testing parameters demonstrates the highest correlation coefficient, R2 = 0.985, for HTC prediction. The superheated wall is noted to have the maximum effect on the predictive accuracy of the boiling heat transfer coefficient. For example, if the wall superheat is dropped from the modeling parameters, the lowest prediction of R2 (0.893) is achieved. The surface morphological features show relatively less influence compared to the liquid thermophysical properties. The proposed methodology is effective in determining the highly influencing surface and liquid parameters for the boiling heat transfer assessment of porous surfaces.

Experimental and Numerical Study of Nucleate Pool Boiling Heat Transfer and Bubble Dynamics in Saline Solution

10.1115/ht2020-8988 â—½  
2020 â—½  
Author(s):  
Qi Liu â—½  
Yuxin Wu â—½  
Yang Zhang â—½  
Junfu Lyu
Keyword(s):  
Heat Transfer â—½  
Experimental Data â—½  
Heat Transfer Coefficient â—½  
Transfer Coefficient â—½  
Boiling Heat Transfer â—½  
Saline Solution â—½  
Numerical Study â—½  
Pool Boiling â—½  
Pool Boiling Heat Transfer â—½  
Boiling Heat Transfer Coefficient

Abstract A visual pool boiling experimental device based on ITO coating layer heater and high-speed shooting technology was established for studying the bubble behavior and heat transfer characteristics of saline solution, which is of great significance for ensuring heat transfer safety in nuclear power plants, steam injection boilers and seawater desalination. Volume of fluid method was applied to simulate numerically the liquid–vapor phase change by adding source terms in the continuity equation and energy equation. The predictions of the model are quantitatively verified against the experimental data. It can be found based on the experimental data that the pool boiling heat transfer coefficient is enhanced as the salt concentration increases. Visualization studies and numerical data have shown that the presence and precipitation of salt leads to a decrease in the detachment diameter and growth time of the bubble and an increase in the frequency of detachment, thereby increasing the pool boiling heat transfer coefficient.

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