Experimental investigations on nucleate pool boiling over micro-finned cylindrical surfaces

2022 ◽  
pp. 095440622110627
Author(s):  
Balkrushna Shah ◽  
Kathit Shah ◽  
Parth Patel ◽  
Vikas J Lakhera
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Dimensional Analysis ◽  
Heat Exchangers ◽  
Boiling Heat Transfer ◽  
Pool Boiling ◽  
Experimental Investigations ◽  
Boiling Heat Transfer Coefficient

The nucleate pool boiling heat transfer over micro-finned cylindrical surfaces has application in the heat exchangers used in thermal power plants and chemical industries. The estimation of boiling heat transfer coefficient is an important parameter in the design of two-phase heat exchangers using micro-finned cylindrical surfaces. In the present work, related experimental investigations on four micro-finned cylindrical surfaces with different surface geometry using refrigerant R-141b at atmospheric pressure are conducted to determine the boiling heat transfer coefficient over micro-finned cylindrical surfaces. A correlation is developed by dimensional analysis wherein the effects of geometrical parameters, operating pressure and thermo-physical properties of fluids are taken into consideration and dimensional analysis conducted using Buckingham π-theorem. The correlation developed utilizes experimental data obtained over the present study as well as from previous studies by various researchers including experimental data for water over different micro-finned cylindrical surfaces at 1 bar by Mehta and Kandlikar, experimental data for R123 at 0.97 bar by Saidi et al. and experimental data for R134a over micro-finned cylindrical surface at 6.1 bar, 8.1 bar, 10.1 bar and 12.2 bar by Rocha et al. The heat flux ranging from 5 to 1100 kW/m2 are considered for the analysis. The data points have been compared with the proposed correlation and the absolute average deviation of the whole data set was obtained as 13.43% with root mean square deviation of 0.0273. All the predicted values were within ±15% of the experimental values of the boiling heat transfer coefficient.

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

2020 ◽  
Author(s):  
Qi Liu ◽  
Yuxin Wu ◽  
Yang Zhang ◽  
Junfu Lyu
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Boiling Heat Transfer ◽  
Saline Solution ◽  
Numerical Study ◽  
Pool Boiling ◽  
Pool Boiling Heat Transfer ◽  
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.

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

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Suchismita Sarangi ◽  
Justin A. Weibel ◽  
Suresh V. Garimella
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Boiling Heat Transfer ◽  
Pool Boiling ◽  
Transfer Enhancement ◽  
Pool Boiling Heat Transfer ◽  
Boiling Heat Transfer Coefficient ◽  
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

2021 ◽  
Vol 13 (22) ◽  
pp. 12631
Author(s):  
Uzair Sajjad ◽  
Imtiyaz Hussain ◽  
Muhammad Sultan ◽  
Sadaf Mehdi ◽  
Chi-Chuan Wang ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Thermophysical Properties ◽  
Boiling Heat Transfer ◽  
Pool Boiling ◽  
Morphological Features ◽  
Porous Surfaces ◽  
Boiling Heat Transfer Coefficient ◽  
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.

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