Entropy Generation and Natural Convection Heat Transfer of (MWCNT/SWCNT) Nanoparticles around Two Spaced Spheres over Inclined Plates: Numerical Study

A numerical study is conducted to evaluate the steady natural convective heat transfer problem and entropy generation of both single wall (SWCNT) and multi wall (MWCNT) nanoparticles with water as a base liquid over two spaced spheres. The isothermally heated spheres are located between two plates of short length. The cooled plates are maintained at different inclination angles. A numerical approach based on the finite volume method and multigrid acceleration was used to solve the governing equations. The effects of nanoparticle type, volume fraction, the inclination angle of the plates and the Rayleigh numbers are well-considered. Results reveal that there is a remarkable enhancement of the average Nusselt number over the plates for MWCNT nanoparticles with 63.15% from the inclination angle 0° to 30°. Furthermore, optimal heat transfer rates over the plates for MWCNT nanoparticles equates to 1.9, which is obtained for the inclination 30° and a Rayleigh number of 10$^{6}$. However, for SWCNT nanoparticles, the same equates 0.9, which is obtained for the inclination 90° and a Rayleigh number of 10$^{6}$. The comprehensive analysis is presented under some well-defined assumptions which show the reliability of the present investigation

Heat Transfer Attributes of Gold–Silver–Blood Hybrid Nanomaterial Flow in an EMHD Peristaltic Channel with Activation Energy

The heat enhancement in hybrid nanofluid flow through the peristaltic mechanism has received great attention due to its occurrence in many engineering and biomedical systems, such as flow through canals, the cavity flow model and biomedicine. Therefore, the aim of the current study was to discuss the hybrid nanofluid flow in a symmetric peristaltic channel with diverse effects, such as electromagnetohydrodynamics (EMHD), activation energy, gyrotactic microorganisms and solar radiation. The equations governing this motion were simplified under the approximations of a low Reynolds number (LRN), a long wavelength (LWL) and Debye–Hückel linearization (DHL). The numerical solutions for the non-dimensional system of equations were tackled using the com-putational software Mathematica. The influences of diverse physical parameters on the flow and thermal characteristics were computed through pictorial interpretations. It was concluded from the results that the thermophoresis parameter and Grashof number increased the hybrid nanofluid velocity near the right wall. The nanoparticle temperature decreased with the radiation parameter and Schmidt number. The activation energy and radiation enhanced the nanoparticle volume fraction, and motile microorganisms decreased with an increase in the Peclet number and Schmidt number. The applications of the current investigation include chyme flow in the gastrointestinal tract, the control of blood flow during surgery by altering the magnetic field and novel drug delivery systems in pharmacological engineering.This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Project No. AN00052)

Role of copper and alumina for heat transfer in hybrid nanofluid by using Fourier sine transform

The convection, thermal conductivity, and heat transfer of hybrid nanofluid through nanoparticles has become integral part of several natural and industrial processes. In this manuscript, a new fractionalized model based on hybrid nanofluid is proposed and investigated by employing singular verses and non-singular kernels. The mathematical modeling of hybrid nanofluid is handled via modern fractional definitions of differentiations. The combined Laplace and Fourier Sine transforms have been configurated on the governing equations of hybrid nanofluid. The analytical expression of the governing temperature and velocity equations of hybrid nanofluid have been solved via special functions. For the sake of thermal performance, dimensional analysis of governing equations and suitable boundary conditions based on Mittage-Leffler function have been invoked for the first time in literature. The comparative analysis of heat transfer from hybrid nanofluid has been observed through Caputo-Fabrizio and Atangana-Baleanu differential operators. Finally, our results suggest that volume fraction has the decelerated and accelerated trends of temperature distribution and inclined and declined profile of heat transfer is observed copper and alumina nanoparticles

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

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.This work was funded by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Project No. GRANT331). The authors also acknowledge the financial support received for the research project entitled “Performance Improvement of Solar Thermal Systems using Magnetic Nanofluids” funded by the Department of Science and Technology (DST), Govt. of India under India-South Africa Joint Science and Technology Research Collaboration vide Sanction no.: DST/INT/South Africa/P-08/2021 dtd. 16 September 2021

Selection of Best Suitable Eco-Friendly Refrigerants for HVAC Sector and Renewable Energy Devices

This paper investigates the selection of the best suitable eco-friendly organic and in-organic refrigerants for heating, ventilation, and air conditioning (HVAC) and renewable energy devices. Inorganic and organic refrigerants are used to cool renewable energy devices, such as solar cells, photovoltaics, and electronic devices. Owing to the renewable energy community’s importance, development in this area has rapidly improved over the past few years. R134a, R404, and R717 have become the most used refrigerants in the HVAC sector and supermarkets across the globe for both cooling and frozen food refrigeration. R134a and R404A have two significant drawbacks: (a) they do not attain optimal energy efficiency in many applications, and (b) they have a large global warming potential (GWP). Hence, optimization experiments were performed to select low global potential refrigerants for replacing R134a and R404A from the HVAC sector and supermarkets using multi-criteria making (MCDN) tools. The techniques used for investigation involved (i) the technique for order of preference by similarity to ideal solution (TOPSIS), (ii) evaluation based on distance from average solution (EDAS), and (iii) multi-objective optimization based on ratio analysis (MOORA). The assessment criteria of optimization involved (i) thermo–physical properties of refrigerants, (ii) environmental aspects of refrigerants, and (iii) economic status of refrigerants. Out of 27 refrigerants chosen for the study, R290 (PROPANE) aced the selection by all the three techniques, i.e., TOPSIS, EDAS, and MOORA, with assessment scores of 0.6056, 0.6761, and 0.466, respectively. R41 (FLUOROMETHANE) is the least preferred refrigerant by EDAS (assessment score—0.3967) and MOORA, while R407C is the least preferred by TOPSIS (assessment value—0.5123). The likelihood of making a bad refrigerant decision may be reduced by the effective evaluation of the MCDM analysis. In conclusion, the suggested MCDM technique provides a practical tool and systematic way for reducing the number of options and may be utilized to identify the ideal refrigerant

Heat and Fluid Flow Analysis and ANN-Based Prediction of A Novel Spring Corrugated Tape

A circular tube fitted with novel corrugated spring tape inserts has been investigated. Air was used as the working fluid. A thorough literature review has been done and this geometry has not been studied previously, neither experimentally nor theoretically. A novel experimental investigation of this enhanced geometry can, therefore, be treated as a new substantial contribution in the open literature. Three different spring ratio and depth ratio has been used in this study. Increase in thermal energy transport coefficient is noticed with increase in depth ratio. Corrugated spring tape shows promising results towards heat transfer enhancement. This geometry performs significantly better (60% to 75% increase in heat duty at constant pumping power and 20% to 31% reduction in pumping power at constant heat duty) than simple spring tape. This paper also presented a statistical analysis of the heat transfer and fluid flow by developing an artificial neural network (ANN)-based machine learning (ML) model. The model is evaluated to have an accuracy of 98.00% on unknown test data. These models will help the researchers working in heat transfer enhancement-based experiments to understand and predict the output. As a result, the time and cost of the experiments will reduce. The results of this investigation can be used in designing heat exchangers

Heat Transfer Characteristics of Fractionalized Hydromagnetic Fluid with Chemical Reaction in Permeable Media

This manuscript optimizes the conjugate heat transfer and thermal-stress analysis for hydromagnetic Brinkman fluid with chemical reaction in permeable media. The governing equations of non-Newtonian Brinkman fluid have been traced out and then fractional derivative approach, namely, Caputo–Fabrizio, is invoked, subject to the exponential boundary conditions. The Fourier Sine and Laplace transforms are applied on governing partial differential equations for generating the analytical results of temperature, concentration and velocity. A comparative study of velocity field is investigated for the sake of long memory and hereditary properties. The analytical investigation of temperature, concentration and velocity field have strong effects on chemical reaction. The graphical depiction of vibrant characteristics of hydromagnetic Brinkman fluid with chemical reaction in permeable media is exhibited for disclosing the sensitivities of different embedded rheological parameters of fluid flow. The results suggested that temperature distribution for smaller and larger Prandtl number has disclosed quick and thicker heat diffusivity.This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Project No. GRANT233]

Simulation of natural convective heat transfer and entropy generation of nanoparticles around two spheres in horizontal arrangement

Herein, laminar convective heat transfer from two horizontally arranged spheres has been evaluated by using numerical models inside water-based fluids incorporated with alumina (Al2O3), copper oxide (CuO), and copper (Cu) nanoparticles. The problem was simulated for different Rayleigh numbers ranging from 103 to 106 and various volume fractions including 2, 4, 6, and 8%. The evaluation process included the perspective of both first and second thermodynamic laws. In-house FORTRAN code was provided to solve the equations based upon the finite volume method as well as the Multigrid acceleration. According to the obtained results, the average Nusselt number enhanced by 57.4% for both the spheres and plates with increment of the Rayleigh number from 103 to 106 for the constant volume fraction of 2%. In addition, nanoparticle type played a significant role on the heat transfer rate and generated entropy. Moreover, introduction of the Al2O3 nanoparticles into the water-based fluid resulted in approaching to the highest Bejan number of 0.98. Furthermore, the ecological coefficient of performance of CuO nanoparticles decreased by increment of the volume fraction at all Rayleigh numbers. In the volume fraction of 2%, it raised from 2.89 to 7.8 by increasing of the Rayleigh number from 103 to 106

A Stochastic Bayesian Regularization Approach for the Fractional Food Chain Supply System with Allee Effects

This motive of current research is to provide a stochastic platform based on the artificial neural networks (ANNs) along with the Bayesian regularization approach for the fractional food chain supply system (FFSCS) with Allee effects. The investigations based on the fractional derivatives are applied to achieve the accurate and precise results of FFSCS. The dynamical FFSCS is divided into special predator category P(η), top-predator class Q(η), and prey population dynamics R(η). The computing numerical performances for three different variations of the dynamical FFSCS are provided by using the ANNs along with the Bayesian regularization approach. The data selection for the dynamical FFSCS is selected for train as 78% and 11% for both test and endorsement. The accuracy of the proposed ANNs along with the Bayesian regularization method is approved using the comparison performances. For the rationality, ability, reliability, and exactness are authenticated by using the ANNs procedure enhanced by the Bayesian regularization method through the regression measures, correlation values, error histograms, and transition of state performances