Search Results (114)

This study presents an experimental evaluation of the thermal and exergetic performance of an air-to-air heat pipe heat exchanger using a cobalt oxide (Co₃O₄)-based non-Newtonian nanofluid, with the additional incorporation of carbon black (CB). Nanofluids were synthesized via a two-step method and tested under turbulent flow conditions across varying Reynolds numbers. The results demonstrated that increasing the Co₃O₄ nanoparticle concentration and adding CB substantially improved both the thermal and exergetic performance compared to deionized water. Specifically, maximum thermal efficiency improvements of 62.7% and 75.4% were recorded for nanofluids containing 1% and 2% Co₃O₄, respectively. The addition of CB further enhanced the thermal efficiency, achieving a maximum improvement of 79.2%. Furthermore, the maximum reduction in thermal resistance reached 61.4% with CB incorporation, while the 2% Co₃O₄ nanofluid achieved a maximum decrease of 50.2%. The use of nanofluids led to a significant reduction in exergy loss, with exergy-saving efficiencies reaching up to 33.6%. These findings highlight the considerable potential of Co₃O₄- and CB-based hybrid nanofluids in advancing waste heat recovery technologies and enhancing the thermodynamic performance of air-to-air heat pipe heat exchanger systems. Full article

The steady shear rheology of suspensions of mixtures of rod-shaped cellulose nanocrystals (NCC) and spherical starch nanoparticles (SNPs) was investigated experimentally over a broad range of NCC and SNP concentrations. The NCC concentration varied from about 1 to 6.7 wt% and the SNP concentration varied from 5 to 30 wt%. The suspensions of mixtures of NCC and SNPs were pseudoplastic (shear-thinning) in nature. The viscous behavior of suspensions of mixtures of NCC and SNPs could be described adequately using the power-law model. The power-law parameters, that is, consistency index and flow behavior index, were dependent on the concentrations of both NCC and SNPs. The consistency index increased substantially with increases in NCC and SNP concentrations. The flow behavior index generally decreased with an increase in NCC and SNP concentrations; that is, the suspension mixtures became more shear-thinning with increases in NCC and SNP concentrations. However, the dependence of the consistency index and flow behavior index on NCC concentration was much stronger as compared with the SNP concentration. Full article

The widespread use of mineral cutting fluids in metalworking poses challenges due to their poor wettability, toxicity, and non-biodegradability. This study explores cactus oil-based nanofluids as sustainable alternatives for metal cutting applications. Samples of cactus oil are prepared in plain form and with 0.025 wt.%, 0.05 wt.%, and 0.1 wt.% activated carbon nanoparticles (ACNPs) from recycled plastic waste. Plain cactus oil exhibited a 34% improvement in wettability over commercial soluble oil, further enhanced by 60% with 0.05 wt.% ACNPs. Cactus oil displayed consistent Newtonian behavior with a high viscosity index (283), outperforming mineral-based cutting fluid in thermal stability. The addition of ACNPs enhanced the dynamic viscosity by 108–130% across the temperature range of 40–100 °C. The presence of nano-additives reduced the friction coefficient in the boundary lubrication zone by a maximum reduction of 32% for CO2 compared to plain cactus oil. The physical and rheological results translated directly to the observed improvements in surface finish and tool wear during machining operations on H13 steel. Cactus oil with 0.05 wt.% ACNP outperformed conventional fluids, reducing surface roughness by 35% and flank wear by 57% compared to dry. This work establishes cactus oil-based nanofluids as a sustainable alternative, combining recycled waste-derived additives and non-edible feedstock for greener manufacturing. Full article

Highlighting the importance of artificial intelligence and machine learning approaches in engineering and fluid mechanics problems, especially in heat transfer applications is main goal of the presented article. With the advancement in Artificial Intelligence (AI) and Machine Learning (ML) techniques, the computational efficiency and accuracy of numerical results are enhanced. The theme of the study is to use machine learning techniques to examine the thermal analysis of MHD boundary layer flow of Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder embedded in a porous medium with heat source/sink and viscous dissipation effects. The considered base fluid is water ($H_{2}O$) and hybrid nanoparticles titanium oxide (${TiO}_2$) and Copper oxide ($CuO$). The governing flow equations are nonlinear PDEs. Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. Artificial Neural Networks (ANNs) simulation approach is used to trained the networks to predict the solution behavior. Thermal boundary layer improves with the enhancement in the value of $Rd$. The accuracy and reliability of ANNs predicted solution is addressed with computation of correlation index and residual analysis. The RMSE is evaluated [0.04892, 0.0007597, 0.0007596, 0.01546, 0.008871, 0.01686] for various scenarios. It is observed that when concentration of hybrid nanoparticles increases then thermal characteristics of the Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder. Full article

Nanofluids, with their enhanced thermal properties, provide innovative solutions for improving heat transfer efficiency in renewable energy systems. This study investigates a numerical simulation of bioconvective flow and heat transfer in a Williamson nanofluid over a stretching wedge, incorporating the effects of chemical reactions and hydrogen diffusion. The system also includes motile microorganisms, which induce bioconvection, a phenomenon where microorganisms’ collective motion creates a convective flow that enhances mass and heat transport processes. This mechanism is crucial for improving the distribution of nanoparticles and maintaining the stability of the nanofluid. The unique rheological behavior of Williamson fluid, extensively utilized in hydrometallurgical and chemical processing industries, significantly influences thermal and mass transport characteristics. The governing nonlinear partial differential equations (PDEs), derived from conservation laws and boundary conditions, are converted into dimensionless ordinary differential equations (ODEs) using similarity transformations. MATLAB’s bvp4c solver is employed to numerically analyze these equations. The outcomes highlight the complex interplay between fluid parameters and flow characteristics. An increase in the Williamson nanofluid parameters leads to a reduction in fluid velocity, with solutions observed for the skin friction coefficient. Higher thermophoresis and Williamson nanofluid parameters elevate the fluid temperature, enhancing heat transfer efficiency. Conversely, a larger Schmidt number boosts fluid concentration, while stronger chemical reaction effects reduce it. These results are generated by fixing parametric values as $0.1<\varpi <1.5, 0.1<\mathit{Nr}<3.0, 0.2<\mathrm{Pr}<0.5, 0.1<\mathit{Sc}<0.4, \mathrm{and} 0.1<\mathit{Pe}<1.5.$ This work provides valuable insights into the dynamics of Williamson nanofluids and their potential for thermal management in renewable energy systems. The combined impact of bioconvection, chemical reactions, and advanced rheological properties underscores the suitability of these nanofluids for applications in solar thermal, geothermal, and other energy technologies requiring precise heat and mass transfer control. This paper is also focused on their applications in solar thermal collectors, geothermal systems, and thermal energy storage, highlighting advanced experimental and computational approaches to address key challenges in renewable energy technologies. Full article

Nanofluids have the proven capacity to significantly improve the thermal efficiency of a heat exchanging system due to the presence of conductive nanoparticles. The aim of this study is to simulate the forced convection on a non-Newtonian hybrid with a nanofluid (Al₂O₃-TiO₂-H₂O) in a hexagonal enclosure by the Galerkin finite element method (GFEM). The physical model is a hexagonal enclosure in two dimensions, containing a heated cylinder embedded at the center. The bottom, middle left, and right walls of the enclosure are all considered cold ($T_c$), while the top wall is considered to be moving, and the remaining middle, upper left, and right walls have the adiabatic condition. The Prandtl number ($Pr$ = $6.2$), Reynolds number ($Re$ = 50, 100, 300 and 500), power law index (n = $0.6$, $0.8$, $1.0$, $1.2$ and $1.4$), volume fractions of nanoparticles ($\varphi$ = $0.00$, $0.01$, $0.02$, $0.03$ and $0.04$), and Hartmann numbers ($Ha$ = 0, 10, 20 and 30) are considered in the model. The findings are explained in terms of sensitivity tests and statistical analysis for various $Re$ numbers, n, and $Ha$ numbers employing streamlines, isotherms, velocity profiles, and average Nusselt numbers. It is observed that the inclusion of $\varphi$ improves the convective heat transfer at the surging values of $Re$. However, if the augmenting heat transfer requires any control mechanism, integrating a non-zero $Ha$ number is found to stabilize the system for the purpose of thermal efficacy. Full article

The Reynolds number (Re), introduced in the late 19th century, has become a fundamental parameter in a lot of scientific fields—the main one being fluid mechanics—as it allows for the determination of flow characteristics by distinguishing between laminar and turbulent regimes, or some intermediate stage. Reynolds’ 1895 paper, which decomposed velocity into average and fluctuating components, laid the foundation for modern turbulence modeling. Since then, the concept has been applied to various fields, including external flows—the science that studies friction—as well as wear, lubrication, and heat transfer. Literature research in recent times has explored new interpretations of Re, and despite its apparent simplicity, the precise prediction of Reynolds numbers remains a computational challenge, especially under conditions such as the study of multiphase flows, non-Newtonian fluids, highly turbulent flow conditions, flows on very small scales or nanofluids, flows with complex geometries, transient or non-stationary flows, and flows of fluids with variable properties. Reynolds’ work, which encompasses both scientific and engineering contributions, continues to influence research and applications in fluid dynamics. Full article

This work’s objective is to investigate the laminar steady flow characteristics of non-Newtonian nano-fluids in a developed chaotic microdevice known as a two-layer crossing channels micromixer (TLCCM). The continuity equation, the 3D momentum equations, and the species transport equations have been solved numerically at low Reynolds numbers with the commercial CFD software Fluent. A procedure has been verified for non-Newtonian flow in studied geometry that is continuously heated. Secondary flows and thermal mixing performance with two distinct intake temperatures of nano-shear thinning fluids is involved. For an extensive range of Reynolds numbers (0.1 to 25), the impact of fluid characteristics and various concentrations of Al₂O₃ nanoparticles on thermal mixing capabilities and pressure drop were investigated. The simulation for performance enhancement was run using a power-law index (n) at intervals of different nanoparticle concentrations (0.5 to 5%). At high nano-fluid concentrations, our research findings indicate that hydrodynamic and thermal performances are considerably improved for all Reynolds numbers because of the strong chaotic flow. The mass fraction visualization shows that the suggested design has a fast thermal mixing rate that approaches 0.99%. As a consequence of the thermal and hydrodynamic processes, under the effect of chaotic advection, the creation of entropy governs the second law of thermodynamics. Thus, with the least amount of friction and thermal irreversibilities compared to other studied geometries, the TLCCM arrangement confirmed a significant enhancement in the mixing performance. Full article

Ceramic slurry is the raw material used in stereolithography, and its performance determines the printing quality. Rheological behavior, one of the most important physical factors in stereolithography, is critical in ceramic printing, significantly affecting the flow, spreading, and printing processes. The rheological behavior of SiO₂ slurry used in stereolithography technology is investigated in the current research using different powder diameters and temperatures. The results present the apparent non-Newtonian behavior. The yielding characteristics occur in all cases. For single-powder cases, the viscosity decreases when the powder diameter is increased. When the nano-sized and micro-sized powders are mixed in different proportions, a more significant proportion of micron-sized powders will decrease the viscosity. With an increase in the nano-sized powders, the slurry exhibits the shear thinning behavior; otherwise, the shear thickening behavior is observed. Thus, the prediction model is built based on the use of the pelican optimization algorithm-deep extreme learning machine (POA-DELM), and the model in then compared with the fitted and traditional models to validate the effectiveness of the method. A more accurate viscosity prediction model will contribute to better fluid dynamic simulation in future work. Full article

In this current work, we assume the mathematical modelling of non-Newtonian time-dependent hybrid nanoparticles via a cylindrical stenosis artery. In this work, blood is used as a base fluid, and the nanoparticles (copper and aluminum oxide) of cylindrical shape are inserted inside the artery to combine with blood to form hybrid nanofluid (HNF). The homotopy analysis method (HAM) is deployed for the solution of nonlinear resulting equations. For the validation of this current work, the results of the existing work have been compared with our proposed model results. A comparison of key profiles like velocity, temperature, wall shear stress, and flow rate is also performed at a specific critical height of the stenosis. It is also observed that the thermal conductance of hybrid nanofluids is greater than that of nanofluids. Including the hybrid nanoparticles (copper and aluminum oxide) inside the blood enhances the blood axial velocity. These simulations are applicable to the magnetic targeting treatment of stenosed artery disorders and the diffusion of nanodrugs. Full article

Additives such as nano-silica and fly ash are widely used in cement and concrete materials to improve the rheology of fresh cement and concrete and the performance of hardened materials and increase the sustainability of the cement and concrete industry by reducing the usage of Portland cement. Therefore, it is important to study the effect of these additives on the rheological behavior of fresh cement. In this paper, we study the pulsating Poiseuille flow of fresh cement in a horizontal pipe by considering two different additives and when they are combined (nano-silica, fly ash, combined nano-silica, and fly ash). To model the fresh cement suspension, we used a modified form of the power-law model to demonstrate the dependency of the cement viscosity on the shear rate and volume fraction of cement and the additive particles. The convection–diffusion equation was used to solve for the volume fraction. After solving the equations in the dimensionless forms, we conducted a parametric study to analyze the effects of nano-silica, fly ash, and combined nano-silica and fly ash additives on the velocity and volume fraction profiles of the cement suspension. According to the parametric study presented here, larger nano-silica content results in lower centerline velocity of the cement suspension and larger non-uniformity of the volume fraction. Compared to nano-silica, fly ash exhibits an opposite effect on the velocity. Larger fly ash content results in higher centerline velocity, while the effect of the fly ash on the volume fraction is not obvious. For cement suspension containing combined nano-silica and fly ash additives, nano-silica plays a dominant role in the flow behavior of the suspension. The findings of the study can help the design and operation of the pulsating flow of fresh cement mortars and concrete in the 3D printing industry. Full article

Thermal conductivity and viscosity are important properties for nanofluids as they significantly affect the flow and heat transfer process. To date, the rheological properties of water-based nanofluids have been well studied, while the results are scarce for non-aqueous nanofluids. In this study, the thermal conductivity and rheological properties of two different kinds of oxide nanofluids (CuO and Al₂O₃) in a typical commercial data center focusing on liquid coolants were systematically investigated at different mass fractions and temperatures. The results showed that the addition of nanoparticles can significantly improve the heat conduction capacity of mineral oil coolants. There is an average increase in thermal conductivity of up to 20–25%. The shear rate–shear stress and shear rate–viscosity curves all showed that mineral oil coolant-based oxide nanofluids behaved as Newtonian fluids and that nanoparticles did not cause the increment in viscosity. The effect of temperature on rheological properties was also studied, and the result showed that high temperatures resulted in low viscosity and shear stress. Finally, the effect of particle type was investigated, and it was found that no matter what kind of nanoparticles were added, their effects on the rheological behaviors were the same. Full article

This contribution addresses a fractal numerical scheme that can be employed for handling fractal time-dependent parabolic equations. The numerical scheme presented in this contribution can be used to discretize integer order and fractal derivatives in a given differential equation. Therefore, the scheme and results can be used for both cases. The proposed finite difference scheme is based on two stages. Fractal time derivatives are discretized by employing the proposed approach. For the scalar convection–diffusion equation, we derive the stability condition of the proposed fractal scheme. Using a nonlinear chemical reaction, the approach is also used to solve the Quantum Calculus model of a Williamson nanofluid’s unsteady Darcy–Forchheimer flow over flat and oscillatory sheets. The findings indicate a negative correlation between the velocity profile and the porosity parameter and inertia coefficient, with an increase in these factors resulting in a drop in the velocity profile. Additionally, the fractal scheme under consideration is being compared to the fractal Crank–Nicolson method, revealing that the proposed scheme exhibits a superior convergence speed compared to the fractal Crank–Nicolson method. Several problems involving the motion of non-Newtonian nanofluids through magnetic fields and porous media can be investigated with the help of the proposed numerical scheme. This research has implications for developing more efficient heat transfer and energy conversion devices based on nanofluids. Full article

Non-Newtonian fluids play a crucial role in applications involving heat transfer and mass transfer. The inclusion of nanoparticles in these fluids improves the efficiency of heat and mass transfer processes. This study employs a numerical solution approach to examine the flow of non-Newtonian hybrid nanofluids over a plumb cone/plate surface, considering the effects of magnetohydrodynamics (MHD) and thermal radiation. Additionally, we investigate how heat and mass transfer are affected by a fluid containing microorganisms. The governing nonlinear partial differential equations are transformed into nonlinear ordinary differential equations using a similarity transformation to simplify this complex system. We then use the Keller-box finite-difference method to solve these equations. Along with a table presenting the results for skin friction, Nusselt number, Sherwood number, and microbe density number, we present graphical representations of velocity, temperature, concentration, and microorganism diffusion behavior. Our results indicate that the addition of MHD and thermal radiation improves the diffusion of microorganisms, thereby enhancing the rates of heat and mass transfer. Through a comparative analysis with prior research, we demonstrate the reliability of our conclusions. Full article

Because of the ease with which oxide films form on its surfaces, stainless steel has strong corrosion resistance and excellent processing performance. Electrochemical machining (ECM) is a flexible process that can create microstructures on stainless steel (SS304); however, with traditional masked ECM, the efficiency and accuracy of microstructure machining are low. Proposed here is the use of a non-Newtonian fluid [polyacrylamide (PAM)] as the electrolyte. To date, there have been few papers on the electrochemical dissolution behavior of stainless-steel micromachining with a non-Newtonian fluid as the electrolyte. The aims of the study reported here were to investigate the electrochemical properties of SS304 with PAM and PAM–NaOH as electrolytes, and to explain their electrochemical corrosion mechanisms. The effects of different electrolytes were compared, and the polarization curves of SS304 in PAM and PAM–NaOH electrolyte solutions with different components were analyzed and compared with that in NaNO₃ electrolyte. Then, the effects of the main processing parameters (pulse voltage, frequency, and duty ratio) on the machining performance were investigated in detail. A microhole array was obtained with a good quality comprising an average diameter of 330.11 µm, an average depth of 16.13 µm, and a depth-to-diameter ratio of 0.048. Using PAM to process microstructures on stainless-steel surfaces was shown to be feasible, and experiments indicated that the mixed electrolyte (PAM–NaOH) had not only the physical characteristics of a non-Newtonian fluid but also the advantages of a traditional electrolyte to dissolve processing products, and it effectively improved the processing accuracy of masked ECM for SS304. Full article