The impact of D-shaped jaggedness on heat transfer enhancement technique using Al2O3 based nanoparticles

Ahmed, Farid; Abir, Atrehar; Redwan, A.S.M.; Bhuiyan, Arafat A.; Mollah, Abdus Sattar

doi:10.1016/j.ijft.2021.100069

Cited by 26 publications

(9 citation statements)

References 40 publications

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“…In essence, we see that the temperature of the interface is at its maximum when nanoparticles are not dispersed in the base fluid. Similar findings on the capability of Al 2 O 3 nanofluids are reported in literature [46]. The temperature gradient is defined as the change in temperature per unit length.…”

Section: Effect Of Nanoparticle Volume Fraction On Cutting Tool Heat ...supporting

confidence: 78%

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

et al. 2022

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The objective of this study is to numerically investigate the thermal performance of cutting fluids dispersed with nanoparticles for effective heat removal during turning operations. The simulations are performed using Ansys Fluent software, and the problem is modelled as a three-dimensional turbulent incompressible single-phase flow. The computational domain consists of a heated cutting tool and work piece, and nanocoolants are sprayed from a nozzle located above the machining zone. The nanocoolants are prepared by mixing mineral oil with nanoparticles of Al₂O₃ (Aluminium Oxide), Al (Aluminium) and SWCNT (Single Walled Carbon Nanotube). The heat transfer performances of different nanocoolants are compared by varying the nanoparticle volume fraction (φ) and coolant velocity (Uc) in the range of 2% ≤ φ ≤ 8% and 1 m/s ≤ Uc ≤ 15 m/s, respectively. The results indicated a drastic drop in the cutting tool temperature with an increase in the volume fraction of dispersed nanoparticles and coolant velocity. The increase in volume fraction decreases the average cutting tool temperature by 25.65% and also enhances the average heat transfer rate by 25.43%. It is additionally observed that SWCNT nanocoolants exhibited a superior thermal performance and heat removal rate compared with Al and Al₂O₃ nanocoolants. The analysed numerical results are validated and are in good accordance with the benchmark results validated from literature.

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Section: Effect Of Nanoparticle Volume Fraction On Cutting Tool Heat ...supporting

confidence: 78%

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

et al. 2022

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“…The smooth channel was first used for simulation using the exact dimensions of the dimpled model for validating the dimple model 6 . The results of the smooth channel were compared from the results of Stephan's and PreuBer's existing Nu correlations for circular pipes 81,82 .…”

Section: Validation Of the Cfd Modelmentioning

confidence: 99%

“…The long life and dependability of these tools are influenced by several factors. The technology industries need components with compact devices 5,6 . Hwang et al 7 talk about the increasing use of micro‐turbines in industrial applications, which have a smaller efficiency in particular.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of the thermo‐hydraulic performance of water‐based nanofluids in a dimpled channel flow using Al₂O₃, CuO, and hybrid Al₂O₃–CuO as nanoparticles

Ahmed¹,

Abir

Fuad³

et al. 2021

Heat Trans

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In this study, the authors study the impact of spherical dimple surfaces and nanofluid coolants on heat transfer and pressure drop. The main objective of this paper is to evaluate the thermal performance of nanofluids with respect to different Reynolds numbers (Re) and nanoparticle compositions in dimpled channel flow. Water‐based nanofluids with Al 2 O 3, CuO, and Al 2 O 3–CuO nanoparticles are considered for this investigation with 1%, 2%, and 4% volume fraction for each nanofluid. The simulations are conducted at low Reynolds numbers varying from 500 to 1250, assuming constant and uniform heat flux. The effective properties of nanofluids are estimated using models proposed in the literature and are combined with the computational fluid dynamics solver ANSYS Fluent for the analysis. The results are discussed in terms of heat transfer coefficient, temperature distributions, pressure drop, Nusselt number, friction factors, and performance criterion for all the cases. For all cases of different nanoparticle compositions, the heat transfer coefficient was seen as 35%–46% higher for the dimpled channel in comparison with the smooth channel. Besides, it was observed that with increasing volume fraction, the values of heat transfer and pressure drop were increased. With a maximum of 25.18% increase in the thermal performance, the 1% Al 2 O 3/water was found to be the best performing nanofluid at Re = 500 in the dimpled channel flow.

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“…The connection between the nodes and elements over the contact regions and interfaces are maintained through contact meshing. The accuracy was maintained through creating polyhedral meshes using reverse cut cell method over the shell domain region [25][26] [27].…”

Section: Meshing and Grid Generationmentioning

confidence: 99%

Numerical Simulation of Heat Exchanger for Analyzing the Performance of Parallel and Counter Flow

Ahmed¹,

Sumon

Fuad³

et al. 2021

1790-5044

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Heat exchangers are almost used in every industry. Among them, shell and tube heat exchangers are covering around 32% of the total heat exchanger. Numerical simulation of the Computational models is playing an important role for the prototypes including the Heat Exchanger Models for the improvement in modeling. In this study, the CFD analysis of parallel and counter flow shell and tube heat exchanger was performed. Following project, looked into the several aspects and these are the temperature, velocity, and pressure drop and turbulence kinetic energy along with the heat exchanger length. Hot water was placed in tube side and cold water was placed in shell side of the heat exchanger. Shell side cold temperature was increasing along the heat exchanger length. On the other side, tube side hot water temperature was decreasing along the tube length. This effect was more significance in counter flow rather than the parallel flow. Velocity was more fluctuating in the shell side due to presence of the baffles. Also following the same reason, pressure drop was higher in the shell side cold water rather than the tube side hot water. To measure the turbulence effect, turbulence kinetic energy was determined. Turbulence was decreasing first part of the shell and tube heat exchanger. But, it was increasing along through the rest part heat exchanger. All these observations and the outcomes are evaluated and then further analyzed

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The impact of D-shaped jaggedness on heat transfer enhancement technique using Al2O3 based nanoparticles

Cited by 26 publications

References 40 publications

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

Numerical investigation of the thermo‐hydraulic performance of water‐based nanofluids in a dimpled channel flow using Al₂O₃, CuO, and hybrid Al₂O₃–CuO as nanoparticles

Numerical Simulation of Heat Exchanger for Analyzing the Performance of Parallel and Counter Flow

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The impact of D-shaped jaggedness on heat transfer enhancement technique using Al2O3 based nanoparticles

Cited by 26 publications

References 40 publications

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations

Numerical investigation of the thermo‐hydraulic performance of water‐based nanofluids in a dimpled channel flow using Al2O3, CuO, and hybrid Al2O3–CuO as nanoparticles

Numerical Simulation of Heat Exchanger for Analyzing the Performance of Parallel and Counter Flow

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Numerical investigation of the thermo‐hydraulic performance of water‐based nanofluids in a dimpled channel flow using Al₂O₃, CuO, and hybrid Al₂O₃–CuO as nanoparticles