Turbulent Flow Heat Transfer through a Circular Tube with Novel Hybrid Grooved Tape Inserts: Thermohydraulic Analysis and Prediction by Applying Machine Learning Model

Bhattacharyya, Suvanjan; Vishwakarma, Devendra Kumar; Chakraborty, Shramona; Roy, Rajdip; Issakhov, Alibek; Sharifpur, Mohsen

doi:10.3390/su13063068

Cited by 27 publications

(5 citation statements)

References 95 publications

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“…Chen et al (2017) and Park et al (2021) investigated the impact of different groove layouts on heat transmission and pressure drop. They emphasized the significance of determining the ideal groove dimensions to maximize heat transmission while reducing pressure drop and fluid-structure interaction [8]. VIV can be reduced by using cylinders with staggered groove configurations, leading to overall reductions of 37% in peak transverse amplitude and around 25% in mean drag coefficient compared to the plain cylinder equivalent.…”

Section: Introductionmentioning

confidence: 99%

Fluid-elastic Instability Effect of Groove Cylinder in Heat Exchanger

Qadeer¹,

Akhtar²,

Pasha³

2023

ICAENS

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The fluidelastic instability impact of groove cylinders in heat exchangers are investigated in this study, and explores associated phenomena of flow-induced vibration and fluidelastic instability. The primary focus is on investigating the performance of various rows of tubes in the tube bundle, with a particular emphasis on the largest instability identified in the third row. The analysis also considers the impact of a triangular arrangement of tubes within the tube bundle. The addition of groove tubes in the heat exchanger proved to greatly delay the onset of fluidelastic instability, lowering the possibility of flow induced vibration. Despite the improved impact of groove cylinders, the study found that the third row of tubes in the tube bundle had a higher degree of instability than the other rows. This result emphasizes the significance of tube location and arrangement throughout the design phase in reducing fluidelastic behavior. Overall, this study shows that groove tubes may delay fluidelastic instability and reduce the frequency of flow-induced vibration in heat exchangers. The design may significantly improve the operating efficiency and reliability of the heat exchanger by using groove cylinders and carefully studying tube designs and optimize heat exchanger performance.

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Section: Introductionmentioning

confidence: 99%

Fluid-elastic Instability Effect of Groove Cylinder in Heat Exchanger

Qadeer¹,

Akhtar²,

Pasha³

2023

ICAENS

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“…The method is cumbersome and cannot solve complex problems involving highly nonlinear or large-scale combinatorial processes. Because the experiment consumes a significant amount of financial, material, and time resources, it is critical to employ machine learning approaches to forecast the thermophysical properties of nanofluids. − The cost method has been gradually applied in many fields such as material discovery, structural analysis, property prediction, reverse design, etc., and has shown amazing potential in materials research.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Predicting the Thermophysical Properties of Nanofluids Using Machine Learning Methods

Wang

Chen

2022

Ind. Eng. Chem. Res.

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Nanofluids are often used as heat transfer fluids due to their good thermal and flow properties. Nanofluids are widely used in energy systems such as solar collectors, heat exchangers, and heat pipes. The thermophysical properties of nanofluids can significantly affect their performance in engineering systems. According to current research in this field, machine learning is a very attractive method to predict the thermophysical properties of nanofluids. We believe that, compared with experiments, machine learning methods are more efficient, rapid, accurate, and practical. The accuracy of the model is affected by factors such as the input variables, the data set selected during the modeling process, and the applied algorithm. This is a comprehensive review that describes the use of different machine learning methods to predict the thermophysical properties of nanofluids (conventional and hybrid nanofluids). This is very useful for researchers, scientists, and engineers in the field of nanofluids.

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“…In conventional size devices, a heat transfer enhancement can be achieved by increasing the heat-transfer surface area, by using ribs, tapes, turbulators, and vortex generators, etc. [1][2][3][4][5][6][7][8]. In addition to extracting the heat from such compact devices, very high efficiency cooling systems are being developed throughout the world.…”

Section: Introductionmentioning

confidence: 99%

Effect of Magnetic Baffles and Magnetic Nanofluid on Thermo-Hydraulic Characteristics of Dimple Mini Channel for Thermal Energy Applications

et al. 2022

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The combined effect of a magnetic baffle and a dimple turbulator on the heat transfer and pressure drop is investigated computationally in a mini channel. Fe3O4 magnetic nanofluid is used as a working fluid. The Reynolds number (Re) is varied from 150 to 210 and the magnetic field intensities range from 1200 G to 2000 G. Finite-volume based commercial computational fluid dynamics (CFD) solver ANSYS-Fluent 18.1 was used for the numerical simulations. A laminar viscous model is used with pressure-velocity coupling along with second-order upwind discretization and QUICK scheme for discretizing the momentum and energy equations. The results show that there is an increase of 3.53%, 10.77%, and 25.39% in the Nusselt numbers when the magnetic fields of 1200 G, 1500 G and 2000 G, respectively, are applied at x = 15 mm, as compared to the flow without a magnetic field when the pitch = 10 mm. These values change to 1.51%, 6.14% and 18.47% for a pitch = 5 mm and 0.85%, 4.33%, and 15.25% for a pitch = 2.5 mm, when compared to the flow without a magnetic field in the respective geometries. When the two sources are placed at x = 7.5 mm and 15 mm, there is an increase of 4.52%, 13.93%, and 33.08% in the Nusselt numbers when magnetic fields of 1200 G, 1500 G, and 2000 G are applied when the pitch = 10 mm. The increment changed to 1.82%, 8.16%, and 22.31% for a pitch = 5 mm and 1.01%, 5.96%, and 21.38% for a pitch = 2.5 mm. This clearly shows that the two sources at the front have a higher increment in the Nusselt numbers compared to one source, due to higher turbulence. In addition, there is a decrease in the pressure drop of 10.82%, 16.778%, and 26.75% when magnetic fields of 1200 G, 1500 G, and 2000 G, respectively, are applied at x = 15 mm, as compared to flow without magnetic field when the pitch = 10 mm. These values change to 2.46%, 4.98%, and 8.54% for a pitch = 5 mm and 1.62%, 3.52%, and 4.78% for a pitch = 2.5 mm, when compared to flow without magnetic field in the respective geometries. When two sources are placed at x = 7.5 mm and 15 mm, there is an decrease of 19.02%, 31.3%, and 50.34% in the pressure drop when the magnetic fields of 1200 G, 1500 G and 2000 G are applied when the pitch = 10 mm. These values change to 4.18%, 9.52%, and 16.52% for a pitch = 5 mm and 3.08%, 6.88%, and 14.88% for a pitch = 2.5 mm. Hence, with the increase in the magnetic field, there is a decrease in pressure drop for both the cases and the pitches. This trend is valid only at lower magnetic field strength, because the decrease in the pressure drop dominates over the increase in pressure drop due to turbulence.

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Turbulent Flow Heat Transfer through a Circular Tube with Novel Hybrid Grooved Tape Inserts: Thermohydraulic Analysis and Prediction by Applying Machine Learning Model

Cited by 27 publications

References 95 publications

Fluid-elastic Instability Effect of Groove Cylinder in Heat Exchanger

Fluid-elastic Instability Effect of Groove Cylinder in Heat Exchanger

A Comprehensive Review of Predicting the Thermophysical Properties of Nanofluids Using Machine Learning Methods

Effect of Magnetic Baffles and Magnetic Nanofluid on Thermo-Hydraulic Characteristics of Dimple Mini Channel for Thermal Energy Applications

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