Nucleate pool boiling heat transfer characteristics of R600a with CuO nanoparticles

Gobinath, N.; Venugopal, T.

doi:10.1007/s12206-018-1246-x

Cited by 14 publications

(3 citation statements)

References 22 publications

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“…In line with the experimental condition, no mass transfer is allowed across the boundary of the boiling chamber in the simulation work. The procedure of the experiments and method of data reduction are explained in the previous work [24]. Henceforth, the continuity, momentum (x and y), and energy equations across the cells (part of ANSYS Fluent) are solved using 2-D steady implicit pressure based solver.…”

Section: Solver Detailsmentioning

confidence: 99%

Effect of Thermophoresis on Heat Diffusion in Isobutane/Copper‐Oxide Nanofluid under Pool Boiling Condition: Numerical Investigation

Feroskhan

Venugopal

Almakayeel

et al. 2022

Journal of Nanomaterials

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Understanding thermophoresis in nanorefrigerants stands challenging for a long period despite the phenomenon is attributed for the motion dynamics of particles in nanofluids. Influence of thermophoretic mobility of copper-oxide nanoparticles on the heat transfer behavior of isobutane (R600a) refrigerant is reported in this work. Pool boiling of the isobutane/copper-oxide nanofluid is numerically simulated in computational fluid dynamics utilizing both single and two-phase approaches. Mobility of particles in the saturated refrigerant is studied, and the time scales associated with (Brownian and momentum) diffusions are numerically solved. The temperature contour of the liquid pool is validated with the experimental data, and the properties of the nanorefrigerant such as thermal conductivity, viscosity, and specific heat are estimated in ANSYS Fluent. 5% increase in thermal conductivity and marginal reduction in specific heat of the nanorefrigerant for 0.01% volume fraction of copper-oxide nanoparticles is witnessed. Mobility of particles due to temperature gradient is found higher near the heater; however, thermophoretic velocity is predicted to be lower because of the narrow temperature gradient. Numerical results showed that the time scale for momentum diffusion is shorter (in the order of e+03) than Brownian diffusion, and hence the momentum diffusion is found to be the predominant mode of heat transfer in nanorefrigerant.

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Section: Solver Detailsmentioning

confidence: 99%

Effect of Thermophoresis on Heat Diffusion in Isobutane/Copper‐Oxide Nanofluid under Pool Boiling Condition: Numerical Investigation

Feroskhan

Venugopal

Almakayeel

et al. 2022

Journal of Nanomaterials

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“…Gobinath and Venugopal [14] claim that CuO nanoparticles of 0.1 % volume fraction in R600a established nearly 20 % enhancement in heat transfer coefficient of the refrigerant at higher heat flux. The optimum concentration of CuO nanoparticles in stable dispersion for a prolonged time and contribute for significant enhancement in the heat transfer coefficient of R600a refrigerant is experimentally found as 0.05 % by volume.…”

Section: Introductionmentioning

confidence: 99%

Flow Patterns in Two Nanorefrigerants R600a/CuO and R410A/CuO During the Boiling Process

Toapanta-Ramos,

Suquillo,

Cornejo

2024

Enfoque UTE

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The present study aims to know the flow patterns in two nanorefrigerants R600a / CuO and R410A / CuO throughout the forced boiling process in horizontal square pipes. Those are obtained using the thermophysical properties of the refrigerants R600a and R410A in state liquid and vapor, as well as the properties of the CuO nanoparticles. The analysis was carried out using two methods: analytical and numerical. The analytical method was established by formulas and correlations through scientific articles and books to find an improvement in the two-phase heat transfer, under the conditions at an inlet temperature of 8 ° C and with a quality range of 0 to 1. This allowed to verify that by adding nanoparticles to the refrigerant, the transition between the flow regimes increases progressively, while the quality of the vapor decreases. For the numerical method, the different transition limits are specified in a simulation process in the Ansys Fluent CFD Software, under established design conditions, which consequently increases the general efficiency of any refrigeration system.

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“…The author reported that nanoparticle alters the nucleation site density, bubble size, and the frequency of the bubble generation from the heated surface. Gobinath and Venugopal experimentally studied the effect of heat flux and nanoparticle volume fraction on nucleate pool boiling of CuO‐isobutane refrigerant nanofluid. They reported that an increase in nanoparticle and heat flux enhances the nucleate boiling heat transfer.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of thermal performance of single‐walled carbon nanotube nanofluid under turbulent flow conditions

Fadodun

Amosun

Salau

et al. 2019

Engineering Reports

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In this paper, a numerical study is performed to investigate the effect of Reynolds number and nanoparticle concentration on the thermal performance of single‐walled carbon nanotubes (SWCNTs) nanofluids flowing through a straight pipe with constant heat flux in a turbulent flow regime. The governing equations (continuity, momentum, energy, rate of turbulent production, and rate of turbulent dissipation) are solved using a computational fluid dynamic approach (ie, finite volume method). In the sensitivity analysis, the Reynolds number is varied between (10 000‐200 000) and nanoparticle concentration between (0%‐0.25%). The simulation results show that convective heat transfer (average Nusselt number) increases by 7.48% while the pressure drop and pumping power increase by 119% and 199%, respectively. In addition, at low Reynolds number (104), increase in nanoparticle concentration (0%‐0.25%) decreases entropy production rate by 16.95%. However, at higher Reynolds number (2*105), the entropy production rate increases by 149.77%. Furthermore, other results such as entropy generation number, Bejan number, second thermodynamic law efficiency, and thermal performance factor, which combine the first and second law of thermodynamics, are presented as functions of Reynolds number and nanoparticle's concentration. The overall result shows that SWCNT nanofluid will only be beneficial at low Reynolds number of (10 000‐50 000).

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Nucleate pool boiling heat transfer characteristics of R600a with CuO nanoparticles

Cited by 14 publications

References 22 publications

Effect of Thermophoresis on Heat Diffusion in Isobutane/Copper‐Oxide Nanofluid under Pool Boiling Condition: Numerical Investigation

Effect of Thermophoresis on Heat Diffusion in Isobutane/Copper‐Oxide Nanofluid under Pool Boiling Condition: Numerical Investigation

Flow Patterns in Two Nanorefrigerants R600a/CuO and R410A/CuO During the Boiling Process

Numerical investigation of thermal performance of single‐walled carbon nanotube nanofluid under turbulent flow conditions

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