Narrow Results

The structure of nanoparticles and their thermophysical characteristics potentially affect the performance of nanofluids. The thermal conductivity model termed as Hamilton–Crosser’s model accommodates the influence of nanoparticles shapes for thermal enhancement applications. Hence, this research aims to analyze the thermal transport in ternary nanofluids using Hamilton–Crosser’s model. The problem is formulated for stagnation point flow using the similarity variables in the governing laws. The traditional nanofluid problem is modified for ternary nanofluids with additional physical aspects of heat generation, thermal radiations, thermal slip effects over the convectively heated domain, and dissipation effects. Then, the numerical scheme (shooting method coupled with RK technique) is implemented for the results. The physical outcomes revealed that stronger unsteady effects $({\alpha }_2=0.1,0.8,1.5,2.2)$ increased the movement of the fluid while nanoparticles concentration $({\varphi }_1=0.01,0.02,0.03,0.04)$ abstain the fluid motion. The thermal transport in spherical-type nanoparticles is observed dominant when the Biot number varies $(B_1=0.1,0.2,0.3,0.4)$. However, the increasing transient effects $({\alpha }_2=0.1,0.2,0.4)$ slow down the model efficiency. Addition of platelet nanoparticles is observed as good for cooling of the nanofluidic system followed by the hexahedron and spherical nanomaterial. Moreover, higher dissipation energy, heat generation, and radiation effects are examined as excellent physical parameters to make the fluidic system more efficient.

This paper presents a novel single-step method for preparation copper nanofluids by electrical explosion of wire in liquid. Three types of fluids were used as a medium of the wire explosion process: deionised water, cetyl trimethyl ammonium bromide (CTAB) solution 0.001 M and ethylene glycol. The X-ray diffraction (XRD), field emission scanning electron microscope (FE-SEM), energy dispersive spectroscopy (EDS) and UV-vis spectroscopy were used to investigate the properties of the nanofluids. Pure copper phase was detected in the nanofluids using ethylene glycol and mixture of copper and oxide phase was observed in the nanofluids using water and CTAB solution. FE-SEM analysis showed that size of particles formed in ethylene glycol was about 90 nm, the smallest in three samples.

In this study, an investigation has been carried out to examine the effects of thermal radiation, heat generation/absorption, viscous dissipation and suction parameter on MHD flow of water-base nanofluid (Ag, Cu, Al₂O₃, CuO and TiO₂). This study also focused on the mixed convective flow of water-base nanofluid due to a vertical permeable plate in the presence of convective boundary condition. Further, heat transfer has been inspected for water-base fluid influenced by heat generation/absorption and viscous dissipation. Moreover, the governing equations are reduced to nonlinear ordinary differential equations via Sparrow–Quack–Boerner local non-similarity method. These nonlinear ODEs are simulated numerically by means of Runge–Kutta–Fehlberg method (RKF-45). The impact of pertinent parameters on the dimensionless velocity, nanofluid temperature, skin friction and local Nusselt number are discussed and displayed. The results match with a special case of formerly available work. The present exploration exhibits that nanoparticle volume fraction increases the velocity and temperature of Cu-water nanofluid. It is also shown that magnetic parameter reduces the heat transfer rate.

Modern biomedical and tribological systems are increasingly deploying combinations of nanofluids and bioconvecting microorganisms which enable improved control of thermal management. Motivated by these developments, in this study, a new mathematical model is developed for the combined nanofluid bioconvection axisymmetric squeezing flow between rotating circular plates (an important configuration in, for example, rotating bioreactors and lubrication systems). The Buongiorno two-component nanoscale model is deployed, and swimming gyrotactic microorganisms are considered which do not interact with the nanoparticles. Thermal radiation is also included, and a Rosseland diffusion flux approximation is utilized. Appropriate similarity transformations are implemented to transform the nonlinear, coupled partial differential conservation equations for mass, momentum, energy, nanoparticle species and motile microorganism species under suitable boundary conditions from a cylindrical coordinate system into a dimensionless nonlinear ordinary differential boundary value problem. An efficient scheme known as differential transform method (DTM) combined with Padé-approximations is then applied to solve the emerging nonlinear similarity equations. The impact of different non-dimensional parameters i.e. squeezing Reynolds number, rotational Reynolds number, Prandtl number, thermophoresis parameter, Brownian dynamics parameter, thermal radiation parameter, Schmidt number, bioconvection number and Péclet number on velocity, temperature, nanoparticle concentration and motile gyrotactic microorganism density number distributions is computed and visualized graphically. The torque effects on both plates, i.e. the lower and the upper plate, are also determined. From the graphical results, it is seen that momentum in the squeezing regime is suppressed clearly as the upper disk approaches the lower disk. This inhibits the axial flow and produces axial flow retardation. Similarly, by enhancing the value of squeezing Reynolds number, the tangential velocity distribution also decreases. More rigorous squeezing clearly therefore also inhibits tangential momentum development in the regime and leads to tangential flow deceleration. Tables are also provided for multiple values of flow parameters. The numerical values obtained by DTM-Padé computation show very good agreement with shooting quadrature. DTM-Padé is shown to be a precise and stable semi-numerical methodology for studying rotating multi-physical flow problems. Radiative heat transfer has an important influence on the transport characteristics. When radiation is neglected, different results are obtained. It is important therefore to include radiative flux in models of rotating bioreactors and squeezing lubrication dual disk damper technologies since high temperatures associated with radiative flux can impact significantly on combined nanofluid bioconvection which enables more accurate prediction of actual thermofluidic characteristics. Corrosion and surface degradation effects may therefore be mitigated in designs.

The aim of this study is to investigate the effects of thermal radiation and chemical reactions on magnetohydrodynamic hyperbolic tangent liquid, which includes nanoparticles on a stretched surface while taking into account Brownian motion and thermophoresis. The nonlinear partial differential equations governing the system are converted into nonlinear ordinary differential equations through suitable similarity transformations. The focus of the study is to elucidate important engineering concepts such as skin friction, Sherwood number, and heat transfer, as well as to understand the effects of various expressions on the different profiles. The Keller-box approach, a sophisticated numerical tool, is used to get the numerical answers to the current enquiry. The generated findings are extensively tested for correctness and dependability. The findings of this study might have far-reaching ramifications for a variety of technical applications, including heat exchangers, chemical reactors, and thermal management systems.The results show that the rate of mass transfer rises with the increment in the factors of chemical reaction, thermal radiation, nanoparticles volume, and Brownian motion.

Nanofluids with peristaltic flows are being studied in depth because they can be used in so many different ways, such as to diagnose and treat diseases. In this paper, the peristaltic flow of a nanofluid with viscosity and electric conductivity that change with temperature is used. There are different base fluids and nanoparticles that are being thought about. First, the governing equations are modeled, and then they are made easier to understand by assuming that the wavelength is long and the Reynolds number is small. To make a dimensionless differential system, the right dimensionless numbers are added. Mathematica’s built-on function NDSolve is used to figure out the numerical solution of the resulting system. To figure out how fast heat moves, researchers compare different combinations of base fluids and nanoparticles.

The miniaturization of electronic devices without compromising their heat dissipation capacities is the main concern due to the rapid evolution in power industries and engineering fields. The conventional methods of cooling or heating the devices are changed and old tactics of using conventional fluids for heat dissipation are replaced with nanofluids of strong thermal efficiency. In the present context, the experimental as well as theoretical studies of nanofluids (Cu–H₂O/Al₂O₃–H₂O) flow inside the wavy and microchannels are elucidated and discussed for different physical conditions. It is found that the use of Cu–H₂O/Al₂O₃–H₂O nanofluid improves the thermal efficiency of heat exchangers. The complex shapes and sizes of heat exchangers such as multilayer heat exchangers, heat exchangers with twisted and square shapes and multijet heat exchangers are considered effective coolants as compared with straight microchannel heat exchangers. The use of Cu–H₂O/Al₂O₃–H₂O nanofluids improves the overall heat transfer efficacy of electronic devices, and it is considered a promising coolant for various applications including aerospace (spacecraft and satellites), automobile (cooling the engines and power management in electric vehicles), renewable energy (solar plants), microelectronic devices (heat dissipation through the microprocessor and cooling the other components of devices) and modern heat exchangers of engineering domains.

Nanofluids, characterized by the dispersion of nanoparticles in a base liquid, have attracted significant attention in recent years due to their exceptional thermal properties. Specifically, the specific heat capacity of nanofluids plays a crucial role in the design and optimization of heat transfer systems. Traditional experimental methods for determining the specific heat capacity of nanofluids are often limited in terms of cost, time, and operating condition ranges. To address these limitations, this research focuses on the development of a novel predictive model for estimating the specific heat capacity of nanofluids. This study aims to develop a machine learning regression model called Gradient Boost Regression (GBR) with Grid Search optimization (GSO) for accurately predicting the specific heat capacity of aluminum nitride (Al₂N₃) nanoparticles that are suspended in both water and an ethylene glycol (EG) solution. The GBR-GSO model capitalizes on the strengths of GBR, which can effectively capture complex relationships, and GSO, a metaheuristic optimization technique inspired by the law of gravity. By integrating these two approaches, we aim to create a robust and accurate predictive model for specific heat capacity in nanofluids. To develop and validate the GBR-GSO model, a diverse dataset based on experimental-specific heat capacity collected from the literature has been designed. The performance of the model has been evaluated by comparing its predictions with experimental data. The GBR-GSO model achieved 99.99% accuracy with the experimental data of specific heat capacity. This research contributes to the advancement of nanofluid-based heat transfer systems by providing an effective tool for predicting the specific heat capacity of nanofluids. The developed model can facilitate the design and optimization of various engineering applications, leading to the development of energy-efficient and sustainable technologies.

This paper focuses on flow structures and thermal fields of the Carreau–Yasuda (CY) nanofluid model through a two-dimensional, wavy, complicated vertical asymmetrical conduit filled with porous elements. Formulations of the viscous dissipation in the case of CY nanofluids are derived and nonlinear radiation flux as well as joule heating are examined. Buongiorno’s nanofluid approach, which involves Brownian motion and thermophoresis aspects is considered. The electrical conductivity of the suspension is considered as a variable where it depends upon the ambient temperature and concentration distributions and the Joule heating impacts are not neglected. The approach of solving the problem is contingent upon converting the system to dimensionless form then the lubrication approach with low magnetic Reynold numbers is applied. Numerical solutions are found for the resultant system, and wide ranges are considered for Weissenberg number We, non-Newtonian parameter n and Darcy number $D_a$, namely, $0\le \mathrm{\text{We}}\le 2$, $-0.5\le n\le 1.5$ and $0\le D_a\le 1.6$, respectively. The major results indicated that gradients of the pressure are higher in case of shear thickening $(n>1)$ comparing to in the instance of shear thinning $(n<1)$. Also, the velocity is enhanced, close to the channel’s lowest portion, as the Weissenberg number is growing. The variable electrical conductivity gives a higher mass transfer rate compared to the constant property.

In the food industry, electrical conductivity is essential for heating processes. The dependence on temperature conductivity of electricity on the outermost layers flow of the nanofluid is the main topic of this paper. Variable electrical conductivity, viscosity, thermo diffusion, thermal radiation and radiation absorption on convective heat and mass transfer flow Cuo and Al₂O₃-water nano-fluids confined in cylindrical annulus. The non-linear governing equations have been solved by finite element technique with quadratic approximation functions. For various parametric adjustments, the temperature, speed, and nanoconcentration have all been examined. Similar to the cylindrical wall, quantitative evaluations have been made of the surface resistance, temperature rate and mass transport. It is discovered that for both types of nanofluids, a higher thermo-diffusion effect leads to a lower concentration and Sherwood digits on the cylinders. An augment in Q1 enriches the rapidity in CuO-water nanofluidic system as well as decreases in Al₂O₃-water nanofluidic. Increased Q1 lowers the real temperature and nanoconcentration in both types of nanofluids.

Application: This study focuses on the analysis of nanofluids, which are suspensions of nanoparticles in standard fluid transfer systems. The investigation specifically examines the behavior of nanoparticles over a deformable surface. Purpose and Methodology: Thermal radiation and magnetohydrodynamic forms are incorporated into the energy and momentum equations, respectively. Basic fluid mechanics principles are employed to derive the governing flow equations. The use of similarity transforms facilitates the transformation of ordinary differential equations into partial differential equations. Nonlinear ordinary differential equations are then reduced to a set of initial value problems using the shooting technique. Core Findings: Numerical results are obtained for the thermal profile. The study indicates thermal optimization through the combined inclusion of water with alumina and polymers with copper oxide and titanium dioxide nanoparticles. Graphical analysis explores the absorption of parameters in velocity and temperature profiles. Future Work: Future research could delve deeper into the optimization of thermal properties and investigate additional nanoparticle combinations. Further exploration of the effects of different surface deformations and variations in fluid properties could also be pursued.