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In this paper, a simulation is performed on nanofluids flow with double-diffusive natural convection. The enclosure is hexagonal, and hot obstacles of various shapes are placed inside it. The partial differential equations governing fluid flow and heat and mass transfer are solved using the finite element method. Mass diffusion, characterized by the Lewis number (Le), is a significant parameter affecting the behavior of two-phase flow. This parameter is the most influential parameter in concentration distribution. Temperature, velocity, and concentration fields inside the enclosure are analyzed using temperature, velocity, and concentration contours. The results of this study show that increasing the Le from 1 to 5 causes a reduction in the Nu ¯ by 11.23%, 11.7%, 11.95%, and 11.03% and an increase in the Sh ¯ by 64.41%, 70.82%, 69.64%, and 69.60% for circular, triangular, rectangular, and rhombus obstacles, respectively. Increasing the aspect ratio (AR) from 0.1 to 0.3 leads to an increase in the Nu ¯ by 49%, 36%, 33.7%, and 45.3% and an increase in the Sh ¯ by 48.8%, 39.4%, 44.3%, and 47.6% for circular, triangular, rectangular, and rhombus obstacles, respectively. The average Be decreases with an increase in the AR and increases with an increase in the Le. Increasing the Le leads to a decrease in fluid entropy generation (ENT) and total ENT but increases the AR, which increases fluid ENT and total ENT. However, the change in both thermal ENTs did not result in any significant change. [ABSTRACT FROM AUTHOR]

Bioconvection research is essential due to its widespread use in the domains of biofuels and bioengineering. This study investigates the numerical behavior of megnetohydrodynamic bioconvection boundary layer flow of motile microorganisms in upper convected Maxwell fluid via a renewed bvp4c-based Lobatto IIIA solver. To stabilize the nanoparticles in suspension, microorganisms are used that cause bioconvection. The flow past stretchable sheets is under the influence of heat and mass transfer, nonlinear thermal radiation, and viscous dissipation. Suitable similarity transformations are adopted to amend PDEs' system of governing equations into ODEs' system. Visualize graphical and numerical presentations that show the influence of physical parameters, such as flow rate, temperature gradient, nanofluid concentration, and gyrotactic motile microorganism concentration. Physical quantities such as skin friction, Nusselt number, Sherwood number, and local density of microorganisms are also taken into consideration. [ABSTRACT FROM AUTHOR]

Iron oxide Fe 3 O 4 and magnesium oxide MgO are important biological agents that have an essential role in medical processes. The deficiency of these biological agents in the human body causes severe diseases like chronic anemia, heartburn, acid indigestion, sour stomach, etc. The existing article is concerned with the study of the mixed convection flow of micropolar Carreau–Yasuda hybrid nanoliquid at a stagnation point past a convectively heated Riga plate. The thermal and mass transport features are enhanced by applying the theory of Cattaneo–Christov thermal and mass flux. For the treatment of the above-mentioned diseases, the blood is considered a base fluid and magnesium oxide MgO and iron oxide Fe 3 O 4 are injected into the blood as nanoparticles. The thermal radiation, chemical reaction, Brownian, and thermal diffusivity influences are taken into account. Further, thermal and solutal stratification effects are implemented on the current flow problem. A higher-order PDE is utilized for the formulation of the existing model. Applicable similarity variables are utilized for the conversion of these nonlinear PDE's into nonlinear ODE's. With the aid of the homotopy analysis method (HAM), the simulation of these ensuing higher-order ODEs is carried out for the analytical outcomes of the existing hybrid nanoliquid model. The fluctuation in different flow profiles is computed under different flow parameters. Drag forces and rate of thermal and mass transport with respect to various pertinent parameters are deliberated in the form of tables. The key result of the existing study is that the temperature rises due to enhancing the estimations of the radiation parameter and nanoparticle's volume fraction. The hybrid nanoliquid's velocity enhances with the enhancement of the Weissenberg number. The hybrid nanofluid velocity declined because of the amplification of the nanoparticle's volume fraction. The hybrid nanoliquid temperature is enhanced for a thermal stratification parameter. The hybrid nanoliquid's concentration diminishes against the enhancing estimations of chemical reaction factor. [ABSTRACT FROM AUTHOR]

In this paper, thermal conductivity prediction of nanofluids is discussed by the RSM and ANN models. The nanofluids contain SiO2 nanoparticles, and their thermal conductivity is measured in the temperature range of 30–60 °C. The effect of SiO2 nanoparticles on thermal conductivity depends on the type of base fluid. For the ethylene glycol (EG) base fluid, SiO2 nanoparticles improve the thermal conductivity by 12%. For glycerol base fluid, thermal conductivity is increased by 6%. The thermal conductivity of both nanofluids depends on temperature and volume fraction so that as the volume fraction and temperature increase, their positive effect on thermal conductivity is enhanced. ANN and RSM models are used to estimate the thermal conductivity ratio of nanofluid to base fluid, i.e., TCR = k nf k bf . Both techniques are well able to predict the amount of TCR for both nanofluids. A cubic function with R 2 = 0.997 and 0.994 is proposed for SiO2-EG and SiO2-G nanofluids, respectively. It is found by trial and error that the neural network with 8 neurons is suitable for both nanofluids. For Ann statistical calculations demonstrate that the R 2 for SiO2-EG nanofluid is 0.995 and for SiO2-G nanofluid is 0.994. The error of both methods is less than 0.3%, which indicates that both methods can well estimate TCR value. [ABSTRACT FROM AUTHOR]

The goal of this numerical investigation is to explore and compare the hydrothermal characteristics of free, mixed, and forced convection of water-copper nanofluid in a cavity using single-phase (SPM) and two-phase (TPM) methods. The top and bottom walls of the cavity are insulated, and the left and right walls are kept at a constant temperature so that the temperature of the left wall is higher than that of the right wall. The impact of volume fraction of nanoparticles (φ ), Rayleigh number (Ra), Richardson number (Ri) and Reynolds number (Re) on the performance features is assessed. In addition, the artificial neural network (ANN) is employed to develop a predictive model of average Nusselt number of nanofluid. The results showed that the TPM was more accurate than the SPM. Additionally, it was observed that increasing the φ , Ra, Ri and Re leads to increasing the average Nusselt number of nanofluid. The maximum heat transfer improvement for the mixed convection and forced convection modes was 28% and 32%, respectively. Furthermore, the ANN modeling revealed the nanoparticle concentration has a negligible role on the results of free convection, while the opposite is true of forced convection. [ABSTRACT FROM AUTHOR]

In the current study, the impact of two-phase water-Al2O3-MWCNT hybrid nanofluid in turbulent flow on exergy efficiency in a solar collector equipped with innovative turbulators is investigated numerically. To simulate two-phase nanofluid, the mixture model was employed, and to simulate radiation and turbulent flow, the surface-to-surface (S2S) method and standard k-ε model were utilized. The study is performed for two-phase water-Al2O3-MWCNT hybrid nanofluid in Reynolds numbers (Re) of 5000–20,000, volume fraction (φ) of 1–3%, torsion ratios of 0.05, 0.15 and 0.25 at heights of 5, 10, 15 and 20 mm made of innovative turbulator. According to the results, exergy efficiency decreases with increasing torsion and height ratio in innovative turbulators. The highest exergy efficiency occurs at the Re = 20,000 and φ = 0.03 at a torsion ratio of 0.05 and a turbulator height of 5 mm. Also, the lowest extrusion efficiency occurs in Re = 5000 and φ = 0.01 in torsion ratio of 0.25 and turbulator height of 19 mm. This is while the exergy efficiency in the solar collector with turbulator with a height of 5 mm and a torsion ratio of 0.25 in Re = 20,000 and φ = 0.03 by 6.04% compared to the solar collector with the same characteristics in the ratio the torsion decreases by 0.05. [ABSTRACT FROM AUTHOR]

In this paper, an exergy analysis is performed on the nanofluid stream of alumina water in a novel heat sink. The study heat sink has a new circular design. A constant heat flux from the work of an electrical component is applied to a part of the heat sink bottom. Nanofluid enters this heat sink in the range of 0–1% with Reynolds 500–1500. The heat sink has two separate entries and is made of aluminum. The maximum and mean temperatures of the electronic device and the output nanofluid temperature of the heat sink were studied. Also out exergy, gain exergy, loss exergy and second thermodynamic law were studied. The results of this paper showed that increasing the amount of Reynolds in the flow input decreases the maximum value and the average temperature of heat sink. With the addition of nanoparticles, this has also occurred. The temperature value of the output is also lowered by increasing the Reynolds number and the volume percentage of nanoparticles. The addition of nanoparticles to the base fluid decreases the amount of exergy at the output and also reduces by around 0.3 percent the efficiency of the second thermodynamics law. By adding nanoparticles to the fluid in the heat sink, the amount of loss exergy is minimized. [ABSTRACT FROM AUTHOR]

In this paper, the natural convection (NC) of the Al2O3–H2O nanofluids (NFs) in a cavity with a heat source in its center is numerically investigated. A two-dimensional simulation of the cavity has been performed for this purpose. The D2Q9 LBM was used for the simulation. Then, the largest Nu was obtained using the artificial neural network (ANN). The ANN has been trained in such a way as to be able to automatically modify the input values and to estimate the largest heat transfer. With an increase in the Ra and nanoparticle volume fraction (NPVF), the heat transfer increases, but it decreases with an increase in the Ha number. In addition, the maximum heat transfer rate occurs for parallel magnetic field (MaF) and the heat transfer rate decreases with an increase in the MaF angle. As the size of the isothermal heat transfer and cold walls increase with a rise in the thermal conductivity coefficient, heat transfer also increases. With an increase in the thermal conductivity coefficient, no significant change was observed in the rate of heat transfer after an initial increase in the Nu. The largest Nu occurs at the largest Ra, largest MaF angle, and weakest MaF. The ANN predicted this value to be 7.0703, which is 2.3% different from the exact value resulting from the predicted computations. [ABSTRACT FROM AUTHOR]

In this paper, the process of natural convection heat transfer (NCHT) and production of entropy (POF) in a portion of a tube has been modeled two-dimensionally. The examined problem is a quarter-tubular enclosure (quarter of a tube) which is filled with water-alumina nanofluid and subjected to a magnetic field (MF) of strength B0 at angle ω relative to horizon. Lattice Boltzmann Method (LBM) is used to simulate this problem. The ranges of parameters used in this investigation are: 0 < ω < 90, 0 < Ha < 60, and 0.1 < L, H < 0.5, and the obtained results include the Nusselt number (Nu), generated entropy, and Bejan number (Be). The results of thermal and dynamic analyses indicate that by growing the Hartmann number (Ha), the NCHT and POF values go up and the Bediminishes. Heat transfer is also improved by increasing the length of the enclosure's hot walls. The highest amount of heat transfer occurs at the MF angle of 60º, and it is 10.3% greater than the amount of heat transfer occurring at horizontal MF. Finally, an artificial neural network was used to simulate the cavity performance based on these parameters. An optimization is performed on the parameters of heat source length and Ha. The optimization is aimed at finding suitable parameter values that lead to the highest heat transfer rate and lowest POF. A table listing a number of optimal points has been presented at the end of the paper. The optimization results indicate a desirability of about 0.56, which is achieved under the best conditions at defined parameter ranges. In this case, the values of Nu and POF are 7.26 and 3.54, respectively. The optimal state occurs at the non-dimensional hot wall length of about 0.5 and Ha of 37.7. [ABSTRACT FROM AUTHOR]

Copper Cu\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\left( {{\text{Cu}}} \right)$$\end{document} and gold Au\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\left( {{\text{Au}}} \right)$$\end{document} nanoparticles have been studied for a variety of applications in a base fluid blood including drug delivery is used as a carrier for drugs, allowing for targeted delivery to specific cells or tissues in the body, as a biosensors to detect specific biomolecules and pathogens in blood. These biosensors can be utilized for medical diagnostics, food safety testing and environmental monitoring. Also, copper and gold nanoparticles in blood are utilized for wound healing, cancer therapy, photothermal therapy and imaging, etc. Due to above applications, copper and gold are immersed as solid nanoparticles in blood (pure fluid) in current investigation. This article's main objective is to scrutinize the mixed convective flow of a hybrid (copper and gold/blood) nanoliquid made of micropolar Carreau–Yasuda fluid. The flow at the stagnant point passes by a Riga plate that has been convectively heated. The features of thermal and mass transportation are greatly boosted by including the model of thermal and mass flux proposed by Cattaneo–Christov. The motile microorganism mechanism is also examined on the flow behavior. The consequences of radiant heat, chemical reactions, Brownian motion, and thermal diffusivity are considered. Additionally, the outcomes of thermal and solutal stratification are applied to problem under consideration. The design of the current model uses higher-order partial differential equations (PDEs) that are shifted to ordinary differential equations (ODEs) by employing appropriate variables and then have been evaluated using homotopy analysis approach (HAM). Several flow parameters are employed to determine the variation in various flow patterns. Tables are used to discuss drag forces, heat and mass transport rates in relation to many relevant parameters. The prime outcomes of the work are that improving the estimates of nanoparticles concentration causes the thermal distribution to rise and velocity distribution to retard. The acceleration of the Weissenberg number elevates the velocity distribution. The raising of thermal stratification factor causes the hybrid nanoliquid temperature to reduce. The microorganism’s outline declines against the amplifying estimates of bioconvection Lewis number and microorganism’s stratification factor. The stretching parameter improves the velocity of nanofluid. [ABSTRACT FROM AUTHOR]

Ag and Al2O3 nanoparticles in a water-based hybrid nanofluid flow on an elongating sheet have several potential applications, particularly in heat transfers, thermal engineering, and material science. Furthermore, enhanced heat transfer, improved cooling systems, heat exchangers, biomedical applications, solar energy systems, textile industries, and oil recovery are the other engineering and biomedical applications. These applications show how versatile and advantageous Ag and Al2O3 nanoparticles can be used in water-based hybrid nanofluids for a range of scientific and engineering applications, especially when it comes to heat transfer and fluid dynamics over the stretching surfaces with mixed convection phenomena. Therefore, in this effort, a comparative analysis of the forced convection and mixed convective flows of a hybrid nanofluid on a stretching sheet is portrayed. Two types of nanoparticles, which include Ag and Al2O3 nanoparticles, are mixed with water to obtain a hybrid nanofluid. The prime focus of this analysis is to examine the hybrid nanofluid flow under two different cases: mixed convection and forced convection. A magnetic field is imposed normal to the direction of flow. A numerical analysis is conducted by using the bvp4c approach. The data of the modeled problem are matched with earlier literature, which authenticates the correctness of the present model. Viscous dissipation, heat source, and Joule heating are employed in current work. The obtained results show that the impression of a magnetic factor on the x-direction velocity profile is more dominant for mixed convective factors than forced convection. However, in the case of y-direction velocity, the opposite impact of the magnetic factor is observed. The results of the rotation factor are more significant along x-direction velocity for forced convection, while this effect is reversed for y-direction velocity. By comparing the results obtained in the present analysis, the impacts of embedded factors on the thermal distribution are more significant and streamlines are closer for forced convection matched to mixed convection. [ABSTRACT FROM AUTHOR]

This correction notice addresses an error in the affiliation details of the second author, Izharul Haq, in an article titled "Analysis of thermally stratified micropolar Carreau–Yasuda hybrid nanofluid flow with Cattaneo–Christov heat and mass flux." The original article incorrectly listed the affiliation as 'College of Sciences and Human Studies (CSHS), Mohammad Bin Fahd University, Al Khobar Dammam, Saudi Arabia,' when it should have been 'College of Sciences and Human Studies (CSHS), Prince Mohammad Bin Fahd University, Al Khobar Dammam, Saudi Arabia.' The correction has been made to the original article. The publisher, Springer Nature, maintains a neutral stance on jurisdictional claims and institutional affiliations. [Extracted from the article]