Enhanced pool boiling of dielectric and highly wetting liquids – A review on surface engineering

Sajjad, Uzair; Sadeghianjahromi, Ali; Ali, Hafız Muhammad; Wang, Chi-Chuan

doi:10.1016/j.applthermaleng.2021.117074

Cited by 66 publications

(14 citation statements)

References 134 publications

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“…For microchannels, the Bond number is defined as the square of the ratio of hydraulic diameter to capillary length, Bo = (d h /L cap ) 2 , which can also be defined as:…”

Section: Methodsmentioning

confidence: 99%

“…Boiling of dielectric liquids is an area of interest for many researchers. Sajjad et al [2] have presented an overview of surfaces and techniques used to enhance heat transfer through pool boiling of dielectric liquids and highly wetting liquids. The authors indicated that on a smooth surface, the use of FC-72 allowed them to obtain a critical heat flux (CHF) of about 270 kW/m 2 with a heat transfer coefficient (HTC) greater than 6 kW/m 2 K. The insufficient thermophysical properties of dielectric liquids force the use of special enhancement methods to increase the CHF and HTC.…”

Section: Introductionmentioning

confidence: 99%

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Boiling of FC-72 on Surfaces with Open Copper Microchannel

Kaniowski

Pastuszko

2021

Energies

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The paper presents the results of experimental research on pool boiling heat transfer of dielectric liquid FC-72. Measurements were made at atmospheric pressure on open surfaces with microchannels. Heat transfer surfaces, in the form of parallel milled microchannels, were made of copper. The rectangular cross-sectional microchannels were 0.2 to 0.5 mm deep and 0.2 to 0.4 mm wide. The surfaces, compared to a smooth flat surface, provided a five-fold increase in the heat transfer coefficient and a two-fold increase in the critical heat flux. The article analyses the influence of the width and height of the microchannel on the heat transfer process. The maximum heat flux was 271.7 kW/m2, and the highest heat transfer coefficient obtained was 25 kW/m2K. Furthermore, the experimental results were compared with selected correlations for the nucleate pool boiling.

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“…For microchannels, the Bond number is defined as the square of the ratio of hydraulic diameter to capillary length, Bo = (d h /L cap ) 2 , which can also be defined as:…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Boiling of FC-72 on Surfaces with Open Copper Microchannel

Kaniowski

Pastuszko

2021

Energies

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“…It should be noted that various ribs and corrugations were adopted in the majority of the aforementioned numerical experiments to evaluate their influences on thermoconvective phenomena within a microchannel filled with colloidal dispersions. However, pertaining to the existing literature works [24,[31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48], it can be ascertained that the influence of corrugated-wall microchannels on the thermal-hydraulic behaviour of the thermoconvective mechanisms of an elasticoviscous fluid in a microchannel that is susceptible to magnetic flux density has not been reported.…”

Section: Introductionmentioning

confidence: 99%

Application of Cylindrical Fin to Improve Heat Transfer Rate in Micro Heat Exchangers Containing Nanofluid under Magnetic Field

et al. 2021

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In this study, the convective mode heat transfer phenomena of bi-phase elasticoviscous (non-Newtonian) nanofluid is quantified by forcefully flowing it through a specially designed microchannel test section. The test section, which is rectangularly cross-sectioned and annexed internally with cylindrical needle ribs is numerically investigated by considering the walls to be maintained at a constant temperature, and to be susceptible to a magnetizing force field. The governing system-state equations are numerically deciphered using control volume procedure and SIMPLEC algorithm. With the Reynolds number (Re) varying in the turbulent range from 3000 to 11,000, the system-state equations are solved using the Eulerian–Eulerian monofluid Two-Phase Model (TPM). For the purpose of achieving an apt geometry based on the best thermo-hydraulic behavior, an optimization study must be mandatory. The geometry of the cylindrical rib consists of h (10 × 10−3, 15 × 10−3, 20 × 10−3), p (1.0, 1.5), and d (8 × 10−3, 10 × 10−3, 12 × 10−3), which, respectively, defines the height, pitch, and diameter of the obstacles, with the dimensions placed within the braces being quantified in mm. The results demonstrated that the magnetic field leads to an enhanced amount of average Nusselt number (Nuav) in contrast with the occurrence at B = 0.0. This is due to the that the magnetic field pushes nanoparticles towards the bottom wall. It was found that B = 0.5 T has the maximum heat transfer compared with the other magnetic fields. The channel with h = 15 μm height leads to the maximum value of Nuav at all studied Re for constant values of d and h. The channel with p = 1.5 μm results in the maximum value of Nuav at all studied Re for constant values of d and h. The microchannel with d = 8 μm, p = 1.5 μm, and h = 15 μm in the presence of the magnetic field with B = 0.5 T is the best geometry in the present work.

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“…Surface morphology contains microscale, nanoscale, or other features reported in the literature [1]. Micro-and nanoscale surfaces are produced using numerous fabrication techniques, including electron beam deposition [2], physical vapor deposition [3], sandblasting [4], polishing and machining [5], sintering [6], compound fabrication [7], and other surface engineering techniques [1]. These engineered surfaces offer boiling augmentation owing to their different enhancement mechanisms [8].…”

Section: Introductionmentioning

confidence: 99%

Boiling Heat Transfer Evaluation in Nanoporous Surface Coatings

et al. 2021

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The present study develops a deep learning method for predicting the boiling heat transfer coefficient (HTC) of nanoporous coated surfaces. Nanoporous coated surfaces have been used extensively over the years to improve the performance of the boiling process. Despite the large amount of experimental data on pool boiling of coated nanoporous surfaces, precise mathematical-empirical approaches have not been developed to estimate the HTC. The proposed method is able to cope with the complex nature of the boiling of nanoporous surfaces with different working fluids with completely different thermophysical properties. The proposed deep learning method is applicable to a wide variety of substrates and coating materials manufactured by various manufacturing processes. The analysis of the correlation matrix confirms that the pore diameter, the thermal conductivity of the substrate, the heat flow, and the thermophysical properties of the working fluids are the most important independent variable parameters estimation under consideration. Several deep neural networks are designed and evaluated to find the optimized model with respect to its prediction accuracy using experimental data (1042 points). The best model could assess the HTC with an R2 = 0.998 and (mean absolute error) MAE% = 1.94.

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Enhanced pool boiling of dielectric and highly wetting liquids – A review on surface engineering

Cited by 66 publications

References 134 publications

Boiling of FC-72 on Surfaces with Open Copper Microchannel

Boiling of FC-72 on Surfaces with Open Copper Microchannel

Application of Cylindrical Fin to Improve Heat Transfer Rate in Micro Heat Exchangers Containing Nanofluid under Magnetic Field

Boiling Heat Transfer Evaluation in Nanoporous Surface Coatings

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