Hybrid Nanofluid Flow over a Permeable Non-Isothermal Shrinking Surface

Waini, Iskandar; Ishak, Anuar Mohd; Pop, Ioan

doi:10.3390/math9050538

Cited by 36 publications

(26 citation statements)

References 59 publications

(80 reference statements)

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“…In the last few years, various computational techniques have been utilized for various applications in the engineering research area [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. In this study, ANN has been implemented for flow pattern identification and volume ratio prediction.…”

Section: Artificial Intelligencementioning

confidence: 99%

Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter

et al. 2021

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The increasing consumption of fossil fuel resources in the world has placed emphasis on flow measurements in the oil industry. This has generated a growing niche in the flowmeter industry. In this regard, in this study, an artificial neural network (ANN) and various feature extractions have been utilized to enhance the precision of X-ray radiation-based two-phase flowmeters. The detection system proposed in this article comprises an X-ray tube, a NaI detector to record the photons, and a Pyrex-glass pipe, which is placed between detector and source. To model the mentioned geometry, the Monte Carlo MCNP-X code was utilized. Five features in the time domain were derived from the collected data to be used as the neural network input. Multi-Layer Perceptron (MLP) was applied to approximate the function related to the input-output relationship. Finally, the introduced approach was able to correctly recognize the flow pattern and predict the volume fraction of two-phase flow’s components with root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of less than 0.51, 0.4 and 1.16%, respectively. The obtained precision of the proposed system in this study is better than those reported in previous works.

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Section: Artificial Intelligencementioning

confidence: 99%

Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter

et al. 2021

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“…Note that l < 0 and l > 0 signify the shrinking and stretching sheets, respectively, while l = 0 is for the static sheet. Furthermore, the thermophysical properties are obtained from Oztop and Abu-Nada (2008), Takabi and Salehi (2014); and Waini et al (2021). Besides, the subscripts f and hnf are for the base fluid and the hybrid nanofluid, respectively.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Furthermore, Takabi and Salehi (2014) developed a new thermophysical model for hybrid nanofluid. Moreover, the magnetohydrodynamic (MHD) effects on the hybrid nanofluid flow have been studied by several authors (Aly and Pop, 2019; Faizal et al , 2020; Jamaludin et al , 2020; Khan et al , 2020; Waini et al , 2020a, 2020b, 2021; Zainal et al , 2021). The MHD describes the hydrodynamics of a conducting fluid in the presence of a magnetic field.…”

Section: Introductionmentioning

confidence: 99%

MHD stagnation point flow on a shrinking surface with hybrid nanoparticles and melting phenomenon effects

Pop

Waini

Ishak

2021

HFF

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Purpose This study aims to explore the stagnation flow over a shrinking surface in a hybrid nanofluid consists of Al2O3 and Cu nanoparticles. Here, the flow is subjected to the magnetohydrodynamic (MHD) and the melting phenomenon effects. Design/methodology/approach The similarity variables are used to gain the similarity equations. These equations are solved via the bvp4c solver. The effects of several physical parameters on the flow and the thermal characteristics of the hybrid nanofluid are analysed and discussed. Later, the temporal stability analysis is used to determine the stability of the dual solutions obtained as time evolves. Findings Results show that two solutions are found for the limited range of the stretching/shrinking parameter λ, and then these solutions are terminated at λ=λc. The rise of the melting parameter Me from 0 to 2 contributes to enhance 109.63% of the local Nusselt number Rex-1/2Nux and 3.30% of the skin friction coefficient Rex1/2Cf. Contrarily, the values of Rex-1/2Nux and Rex1/2Cf decline by 25.04% and 5.58%, respectively, as the magnetic parameter Mg increases from 0 to 0.3. Additionally, Al2O3-Cu/water has the highest values of Rex1/2Cf and the lowest values of Rex-1/2Nux. Lastly, it is found that the first solution is physically stable as time evolves. Originality/value This paper considers the MHD stagnation point flow of a hybrid nanofluid over a shrinking surface with the melting phenomenon effects. Most importantly, it is shown that there exist dual solutions within a specific range of the physical parameters. Besides, the temporal stability of the solutions is also reported in this study. The finding can contribute to foresee the flow and thermal behaviours in industrial applications. Also, the suitable values of parameters can be determined to avoid misjudgement in flow and heat transfer analysis.

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“…Meanwhile, the flow between two parallel plates with the squeezing effect was reported by Salehi et al [32] and Muhammad et al [33]. Apart from that, Waini et al [34] and Khan et al [35] considered the flow towards a shrinking surface. For further reading, the review papers on hybrid nanofluid can be found in Refs.…”

Section: Introductionmentioning

confidence: 95%

Flow towards a Stagnation Region of a Curved Surface in a Hybrid Nanofluid with Buoyancy Effects

2021

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This paper examines the impact of hybrid nanoparticles on the stagnation point flow towards a curved surface. Silica (SiO2) and alumina (Al2O3) nanoparticles are added into water to form SiO2-Al2O3/water hybrid nanofluid. Both buoyancy-opposing and -assisting flows are considered. The governing partial differential equations are reduced to a set of ordinary differential equations, before being coded in MATLAB software to obtain the numerical solutions. Findings show that the solutions are not unique, where two solutions are obtained, for both buoyancy-assisting and -opposing flow cases. The local Nusselt number increases in the presence of the hybrid nanoparticles. The temporal stability analysis shows that only one of the solutions is stable over time.

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Hybrid Nanofluid Flow over a Permeable Non-Isothermal Shrinking Surface

Cited by 36 publications

References 59 publications

Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter

Application of Feature Extraction and Artificial Intelligence Techniques for Increasing the Accuracy of X-ray Radiation Based Two Phase Flow Meter

MHD stagnation point flow on a shrinking surface with hybrid nanoparticles and melting phenomenon effects

Flow towards a Stagnation Region of a Curved Surface in a Hybrid Nanofluid with Buoyancy Effects

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