Enhanced tunneled surfaces for water pool boiling heat transfer under low pressure

Halon, Tomasz; Zajączkowski, Bartosz; Michaïe, Sandra; Rullière, Romuald; Bonjour, Jocelyn

doi:10.1016/j.ijheatmasstransfer.2017.09.025

Cited by 19 publications

(5 citation statements)

References 19 publications

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“…The physical mechanism of boiling on structured surface is complex, which involves the dynamics of interaction between vapor, liquid, the solid heating surface and a series of complex phenomena such as flow field disturbance. Therefore, many experiments have been conducted to study the BHT mechanism and the physical phenomena in the boiling process (Xie et al 2021a(Xie et al , 2021b(Xie et al , 2020Zonouzi et al 2018, Halon et al 2018Kim et al 2015;Tang et al 2016). Xie et al (2021a) designed experiments to investigate the pool boiling heat transfer characteristics of multi-oriented hierarchical structured surfaces.…”

Section: Introductionmentioning

confidence: 99%

“…The departure time and fully developed vapor film thickness of the inclined surfaces increased with increasing surface orientation. Halon et al (2018) designed two different kinds of enhanced boiling surfaces: NTS (narrow tunnel structure) and TS (tunnel structure), and studied the low-pressure boiling phenomenon and BHT performance of these two structured surfaces. Their results indicated that the BHT performance of tunnel structure was significantly improved at lower pressure, at even one order of magnitude higher than that of a flat surface.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing Pool Boiling Heat Transfer by Structured Surfaces– A Lattice Boltzmann Study

Huang

YiShui

et al. 2022

JAFM

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The structured surface-enhanced pool boiling process and associated heat transfer enhancement characteristics are numerically investigated by using the pseudopotential multiphase flow lattice Boltzmann (LB) model coupled finite difference method (FDM). In the current study, the effects of different microstructure geometries(square structures, triangular serrated structures, triangular-raised structures) and varying spacing in triangular-raised structures (d = 0, 22, 44, 66, 88, 110 l.u. (lattice units)) on boiling heat transfer (BHT) characteristics and bubble dynamics behavior are studied in detail. The results showed that microstructure can accelerate bubble nucleation. Among the three microstructures, the heat transfer performance of triangularraised structures was significantly better than that of square and triangular serrated structures in the nucleate boiling (Ja number is 0.124-0.145). The oscillation and deformation of bubbles led to the lateral migration of bubbles, the continuous nucleation of small bubbles. The phenomenon of re-wetting of heating surface occurred in the process of bubble migration, necking, deformation and detachment was found, which enhances heat transfer in nucleate boiling. At the same time, the growth, oscillation and detachment of bubbles also perturb the liquid and enhance the natural convection around the bubbles.Therefore the main BHT mechanism of nucleate boiling on the three kinds of structured surface is the combined action of transient heat conduction and micro-convection. The variation of the spacing between microstructures showed an important effect on the BHT performance of the heating surface and the generation of activated nucleation sites in the nucleate boiling. Triangular-raised structures can enhance transient heat conduction and micro-convection, with the strongest enhancement effect at d = 66 l.u when the Ja number is 0.124.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing Pool Boiling Heat Transfer by Structured Surfaces– A Lattice Boltzmann Study

Huang

YiShui

et al. 2022

JAFM

View full text Add to dashboard Cite

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“…that influence CHF and BHTC. There are several techniques to modify these properties like porous coating [7,12,19,26,33,45,47,52,55,65,67,74], nanotexture [14,27,28,38,40,44,50,73], nanowire [34,35,49,58,59,70,71], microstructures [69], microchannels [20,21,25,51,60,63], pin-fin [22,32,54], nanoparticle deposition [1-3, 8, 18, 53] etc.…”

Section: Introductionmentioning

confidence: 99%

Pool Boiling Heat Transfer on a Micro‐Structured Copper Oxide Surface with Varying Wettability

et al. 2022

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Copper surface is modified to copper oxide surface for high heat flux electronics applications. Copper oxide surface is prepared by chemical etching using NaOH and (NH 4 ) 2 S 2 O 8 . A pool boiling experiment is conducted to investigate the critical heat flux (CHF) and boiling heat transfer coefficient (BHTC). The results indicate that BHTC of all copper oxide surfaces are enhanced remarkably. Bubble dynamics are also analyzed by means of a high-speed camera. Bubble visualization demonstrates that the active nucleation sites for the copper oxide surfaces are higher than the bare copper surface.

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“…Furthermore, they also developed a simple semi-analytical model to predict the boiling heat transfer. Halon et al [9] tested the samples manufactured by Pastsuzko et al [8] and analyzed the boiling behavior under sub-atmospheric conditions using water as the working fluid. They also observed enhancement in heat transfer.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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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Enhanced tunneled surfaces for water pool boiling heat transfer under low pressure

Cited by 19 publications

References 19 publications

Enhancing Pool Boiling Heat Transfer by Structured Surfaces– A Lattice Boltzmann Study

Enhancing Pool Boiling Heat Transfer by Structured Surfaces– A Lattice Boltzmann Study

Pool Boiling Heat Transfer on a Micro‐Structured Copper Oxide Surface with Varying Wettability

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

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