Effects of nanoparticle types and size on boiling feat transfer performance under different pressures

Yao, Shouguang; Huang, Xiaogan; Yang, Song; Shen, Yan; Zhang, Shili

doi:10.1063/1.5010809

Cited by 13 publications

(6 citation statements)

References 24 publications

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“…Akilu et al [122] attained ~27% thermal conductivity enrichment at 21.1% disparagement of specific heat by using hybrid nanofluids, and SiO 2 -CuO (0.5-2 vol%) dispersed into base fluid (Glycerol/EG). Yao et al [123] did the research on the boiling efficiency of Al 2 O 3 , SiO 2 , and their mixture with water at the ratio of 1:1. The significance of their study was its impact of pressure on the performance of boiling nanofluids.…”

Section: Discussion For Applicationsmentioning

confidence: 99%

Rice Husk Nanosilica Preparation and Its Potential Application as Nanofluids

Ong¹,

Iskandar²,

Khan³

2020

Engineered Nanomaterials - Health and Safety

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The fast development in the extraction technique of silica from biomass has resulted in the signification use of silica in the industry. Rice is one of the world's most significant plants, which serve as a carbohydrate intake for humans. Rice husk is one of the main agro-wastes comprising big quantities of silicate. This chapter presenting the review on rice husk nanosilica production techniques by thermal and chemical methods. A direction on efficient and sustainable nanosilica extraction method will be discussed. Apart from that, method on nanofluids preparation will be accumulated with respect to the end application. Moreover, the influence of nanoparticle in nanofluids in terms of heat conductivity, rheological properties, and stability will be discussed. The potential application area of silica nanofluids such as solar, automobile, electronic cooling, and biomedical application will be explored.

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Section: Discussion For Applicationsmentioning

confidence: 99%

Rice Husk Nanosilica Preparation and Its Potential Application as Nanofluids

Ong¹,

Iskandar²,

Khan³

2020

Engineered Nanomaterials - Health and Safety

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“…However, the CHF ratio between NF and DI water decreases as the system pressure increases; in other words, less accentuated NF CHF improvements are obtained at higher pressures, as was also observed in refs. [17,19]. According to previous studies, three main bubble dynamics are important to explain CHF modification with increasing pressure: (1) bubble size decrease due to a decrease in the density ratio between liquid and vapor;…”

Section: Chf × Pressurementioning

confidence: 97%

“…The same procedure was used for the NP size [3,19,25], as described in the Table 1 footnotes. Two further important assumptions were used for the database construction: the NF concentration unit was converted to vol.% [5,15,17,19,22,25,31,41,42,44], and 316 L stainless steel properties were used for the non-specified stainless steel heating elements [36,40].…”

Section: Database Assumptions and Limitationsmentioning

confidence: 99%

“…The DI water pool boiling experiment is usually performed prior to NF pool boiling experiments to validate the experimental apparatus, as well as to obtain a standard value for comparison. Figure 5 presents the DI water pool boiling CHF values collected from the literature [1,2,4,13,15,[17][18][19][20][21][22][23][24][25][26][27]29,[31][32][33][35][36][37][38][39][40][41][42][43] for saturated temperature as a function of pressure. Zuber's prediction [54] was also plotted for comparison.…”

Section: Water Datamentioning

confidence: 99%

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Analysis of the Effects of Different Nanofluids on Critical Heat Flux Using Artificial Intelligence

Serrao,

Kim,

Duarte

2023

Energies

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Nanofluid (NF) pool boiling experiments have been conducted widely in the past two decades to study and understand how nanoparticles (NP) affect boiling heat transfer and critical heat flux (CHF). However, the physical mechanisms related to the improvements in CHF in NF pool boiling are still not conclusive due to the coupling effects of the surface characteristics and the complexity of the experimental data. In addition, the current models for pool boiling CHF prediction, which consider surface microstructure characteristics, show limited agreement with the experimental data and do not represent NF pool boiling CHF. In this scenario, artificial intelligence tools, such as machine learning (ML) regressor models, are a very promising means of solving this nonlinear problem. This study focuses on creating a new model to provide more accurate NF pool boiling CHF predictions based on pressure, substrate thermal effusivity, and NP size, concentration, and effusivity. Three ML models (supporting vector regressor—SVR, multi-layer perceptron—MLP, and random forest—RF) were constructed and showed good agreement with an experimental database built from the literature, with MLP presenting the highest mean R2 score and the lowest variability. A systematic methodology for optimizing the ML models is proposed in this work.

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“…In addition, it affected by the microscopic motion of nanoparticles and different types of base fluids, including the Brownian motion of nanoparticles [63], and the Marangoni effect between different base liquids [64]. The applied electric field [65], magnetic field [66,67], photothermal boiling [68], and pressure [69] also have a certain influence on the boiling heat transfer of the nanofluid. The physical properties of nanofluids are influenced by the type of nanoparticles and base fluids.…”

Section: Effects Of Nanofluid Physical Properties and Heated Surface mentioning

confidence: 99%

Effect of Nanofluids on Boiling Heat Transfer Performance

Yao

Teng

2019

Applied Sciences

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At present, there are many applications of nanofluids whose research results are fruitful. Nanofluids can enhance the critical heat flux, but the effect on boiling heat transfer performance still has disagreement. Base liquids with higher viscosity improve the boiling heat transfer performance of nanofluids. When the base liquid is a multicomponent solution, the relative movement between the different solutions enhances the microscopic movement of the nanoparticles due to the different evaporation order during the boiling process, so that the boiling heat transfer performance is enhanced. Compared with the thermal conductivity of the heated surface, the deposition of the low thermal conductivity nanoparticles reduces the heat dissipation rate of the heated surface and improves the wall superheat. Then the enhancement of the boiling heat transfer coefficient should be attributed to the thermal conductivity improvement of base fluid and the bubble disturbance resulted from the nanoparticle’s microscopic motion.

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Effects of nanoparticle types and size on boiling feat transfer performance under different pressures

Cited by 13 publications

References 24 publications

Rice Husk Nanosilica Preparation and Its Potential Application as Nanofluids

Rice Husk Nanosilica Preparation and Its Potential Application as Nanofluids

Analysis of the Effects of Different Nanofluids on Critical Heat Flux Using Artificial Intelligence

Effect of Nanofluids on Boiling Heat Transfer Performance

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