Energy and entropy generation analyses of a nanofluid-based helically coiled pipe under a constant magnetic field using smooth and micro-fin pipes: Experimental study and prediction via ANFIS model

Safarzadeh, Sajjad; Niknam-Azodi, Mahdi; Aldaghi, Alireza; Taheri, Amin; Passandideh-Fard, Mohammad; Mohammadi, Majid

doi:10.1016/j.icheatmasstransfer.2021.105405

Cited by 19 publications

(1 citation statement)

References 39 publications

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“…Finally, it was concluded that the optimal values of Re, average flow temperature, and particle diameter were 4000, 363 K, and 100 nm, respectively. Safarzadeh et al [26] experimentally studied entropy generation of Fe 3 O 4 -DI (deionized) water nanofluid flow through a helically coiled pipe under a constant magnetic field. They predicted entropy generation using an adaptive neuro-fuzzy inference system (ANFIS) model.…”

Section: Introductionmentioning

confidence: 99%

Modelling, Analysis and Entropy Generation Minimization of Al2O3-Ethylene Glycol Nanofluid Convective Flow inside a Tube

et al. 2022

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Entropy generation is always a matter of concern in a heat transfer system. It denotes the amount of energy lost as a result of irreversibility. As a result, it must be reduced. The present work considers an investigation on the turbulent forced convective heat transfer and entropy generation of Al2O3-Ethylene glycol (EG) nanofluid inside a circular tube subjected to constant wall temperature. The study is focused on the development of an analytical framework by using mathematical models to simulate the characteristics of nanofluids in the as-mentioned thermal system. The simulated result is validated using published data. Further, Genetic algorithm (GA) and DIRECT algorithm are implemented to determine the optimal condition which yields minimum entropy generation. According to the findings, heat transfer increases at a direct proportion to the mass flow, Reynolds number (Re), and volume concentration of nanoparticles. Furthermore, as Re increases, particle concentration should be decreased in order to reduce total entropy generation (TEG) and to improve heat transfer rate of any given particle size. A minimal concentration of nanoparticles is required to reduce TEG when Re is maintained constant. The highest increase in TEG with nanofluids was 2.93 times that of basefluid. The optimum condition for minimum entropy generation is Re = 4000, nanoparticle size = 65 nm, volume concentration = 0.2% and mass flow rate = 0.54 kg/s.

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Section: Introductionmentioning

confidence: 99%

Modelling, Analysis and Entropy Generation Minimization of Al2O3-Ethylene Glycol Nanofluid Convective Flow inside a Tube

et al. 2022

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Analysis of entropy generation and nonlinear convection on unsteady flow of MHD Prandtl fluid with Soret and Dufour effects

Asad

Riaz

2022

Arab. J. Math.

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Here the assessment of entropy generation with Soret and Dufour impact in flow of MHD Prandtl fluid along an unsteady stretching surface has been measured. Nonlinear mixed convection and convective conditions for heat/mass transfer are imposed at the surface. The outcome of viscous dissipation and radiation is considered in heat transfer features. The obtained system of nonlinear PDEs is converted to ODEs by consuming dimensionless variables. Resulting systems are solved for the convergent solutions. Impacts of Prandtl fluid parameters, unsteadiness parameter, Soret and Dufour numbers, magnetic parameter, nonlinear thermal and concentration parameter, Prandtl number, radiation parameter, thermal and concentration Biot numbers, ratio of concentration to thermal buoyancy, Eckert number and Schmidt number are addressed. Skin friction coefficient, local Nusselt and Sherwood numbers are analyzed graphically. Unsteady parameter $${ \epsilon }$$ ϵ has reverse behavior on the velocity and temperature profiles, velocity declines while temperature raises. Prandtl fluid parameter $${ \alpha }$$ α and $${ \beta }$$ β boost the velocity field. Mixed convection parameter le and N* (ratio of concentration and buoyancy force) enhance the velocity field and resultant boundary layer thickness. Magnetic parameter change its behavior on $$f(\eta )$$ f ( η ) $$\theta (\eta )$$ θ ( η ) and . Soret/Dufour number enhances the energy flux due to mass transfer rate and mass flux which radically increases the temperature. Far away from the wall entropy generation grows rapidly for greater values of a and b. Magnetic and radiation parameter increase the entropy generation while radiation parameter decreases.

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Recent advances in machine learning research for nanofluid heat transfer in renewable energy

Said

Sohail

Tiwari

2022

Advances in Nanofluid Heat Transfer

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Energy and entropy generation analyses of a nanofluid-based helically coiled pipe under a constant magnetic field using smooth and micro-fin pipes: Experimental study and prediction via ANFIS model

Cited by 19 publications

References 39 publications

Modelling, Analysis and Entropy Generation Minimization of Al2O3-Ethylene Glycol Nanofluid Convective Flow inside a Tube

Modelling, Analysis and Entropy Generation Minimization of Al2O3-Ethylene Glycol Nanofluid Convective Flow inside a Tube

Analysis of entropy generation and nonlinear convection on unsteady flow of MHD Prandtl fluid with Soret and Dufour effects

Recent advances in machine learning research for nanofluid heat transfer in renewable energy

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