Search Results (46)

This reply presents a point-by-point response to the comments received from Pantokratoras in our previously published research article. The comments highlighted that the values of electrical conductivity assigned to alumina (Al₂O₃), silicon dioxide (SiO₂), and titanium dioxide (TiO₂) nanoparticles were not appropriate and the experimental value of the Prandtl number for blood should remain within the range of 29–32. In response the electrical conductivity values for each nanoparticle were corrected and revised the Prandtl number values accordingly. The recomputed findings revealed that only small changes appeared in quantitative results while the overall trends and insights remained same. Full article

Molten carbonate salt nanofluids have emerged as a promising approach to improve the power generation efficiency of next-generation concentrated solar power (CSP) systems due to their enhanced thermophysical properties at high temperatures. However, corrosion upon salt nanofluids remains a key challenge for the use of cost-effective steels as construction materials in CSP applications. In this work, the corrosion behavior of AISI 301LN stainless steel exposed to molten carbonate salt nanofluids containing 1.0 wt.% SiO₂ nanoparticles with <20 nm and <50 nm has been studied. Corrosion tests were conducted in a static Li₂CO₃-Na₂CO₃-K₂CO₃ molten salt mixture at 600 °C for 1000 h. The oxide scales formed after exposure to the three nanofluids and the base salt were compared. The results revealed that the corrosion rate of AISI 301LN steel on molten salt was reduced by the addition of SiO₂ nanoparticles. The incorporation of SiO₂ nanoparticles into the oxide scale leads to the formation of dense reticulated nanostructures composed of Si-containing oxides, respectively. This increases the hardness of the oxide scale and enhances its protective performance in molten salt, particularly when using SiO₂ nanoparticles with the smallest size (<20 nm). Full article

Effective thermal management is crucial for the performance, thermal safety, and lifespan of lithium-ion batteries in electric vehicles (EVs). Thermal management strategies are essential for preventing overheating, thermal imbalance, and the associated risk of thermal runaway. Nanofluids are emerging and attracting considerable attention as potential coolants for high-power energy storage and electronics systems. This review updates and summarizes the most recent advances in nanofluid-based cooling strategies for battery thermal management systems (BTMSs) over the past five years, emphasizing their implications for battery thermal safety. Three main nanofluid-based cooling strategies have been evaluated in depth, including nanofluid-based indirect liquid cooling, nanoparticle-enhanced PCM cooling, and nanofluid-based heat pipe cooling. Various nanofluid formulations, including mono, hybrid, and ternary nanofluids, have been considered and evaluated for their heat dissipation under high charge/discharge and abuse-relevant conditions. Thermal and hydraulic performance characteristics, including maximum temperature, maximum temperature difference, and pressure drop, have been comprehensively evaluated for different nanofluid-based cooling strategies. The findings demonstrated that nanofluids significantly improved heat transfer rates and enhanced temperature control efficiency. In particular, hybrid and ternary nanofluids exhibit superior thermal performance and effectively suppress the escalation of safety-critical temperatures. Beyond summarizing cooling performance, this review further discusses the role of nanofluid-based cooling strategies as functional thermal-control layers within intelligent BTMS architectures. Particular attention is given to their compatibility with sensing networks, BMS-/VCU-level supervisory control, predictive thermal models, actuator responsiveness, fault-warning algorithms, and long-term reliability under realistic driving and fast charging conditions. Therefore, this review provides architecture-oriented insights for developing safe, energy-efficient, and control-ready BTMSs for next-generation high-power and connected EVs. Full article

A numerical investigation of forced convection heat transfer in a three-dimensional T-shaped bifurcating channel with an upstream rotating cylinder and a downstream vibrating wavy wall is presented. The working fluid is a ternary hybrid nanofluid (Fe₂O₃, CuO, MoS₂ in water) exhibiting Casson rheology under an inclined magnetic field. The novelty of this work lies in the first integrated configuration combining these simultaneous mechanical, magnetic, and non-Newtonian effects. Using COMSOL Multiphysics, 413 parametric combinations of Reynolds number, Hartmann number, Casson parameter, nanoparticle shape and volume fraction, magnetic field angle, cylinder rotation speed, wall amplitude (Am), and period were solved. Average Nusselt and Bejan numbers quantified heat transfer enhancement and thermodynamic irreversibility. To interpret the high-dimensional parameter space and to circumvent the prohibitive computational cost of additional 3D magnetohydrodynamics simulations, machine learning (XGBoost) models were developed to rank feature importance and provide fast, accurate surrogate predictions (R² > 0.99). Cylinder rotation dominates heat transfer, increasing the Nusselt number by over 980% (feature importance 0.42) with a modest entropy penalty. Nanoparticle volume fraction reduces the Nusselt number via viscous damping. Magnetic field parameters negligibly affect heat transfer but strongly influence entropy generation; a perpendicular field recovers up to 97% thermal efficiency at high Hartmann numbers. Full article

The study addresses a selected issue in industrial cooling, that is, how to transport heat more efficiently when the process involves fiber spinning and extrusion, in which conventional fluids usually cannot work. We considered a ternary nanofluid that passed around a porous stretching cylinder and particularly considered the synergistic effect of quadratic thermal buoyancy, and the thermally generated double-diffusive heat and solute (TGDHS) effect. Through the Casson fluid model and considering the magnetic fields, radiations, and nonlinear chemical reactions, we reduced complex PDEs to simple ODEs. The results were evident using the BVP4C numerical method. Although in reality, magnetic fields and thermal radiation become a retarding force, the quadratic thermal buoyancy is the driving force behind accelerating the flow. An important trade-off that we discovered is that a heavier Casson fluid reduces heat and mass transfer. The addition of Nimonic 80A, AA7072, and AA7075 nanoparticles to ethylene glycol consistently enhances heat transfer, outperforming the base fluid by 7.8% even at low concentrations. While AA7072 and AA7075 drive significant increases of over 16%, Nimonic 80A offers a much more marginal contribution of 1.23%. Consequently, the Nusselt number is far more sensitive to the concentration of the aluminum alloys than to the Nimonic 80A. Finally, this work demonstrates that the most significant parameter in intensifying convective heat and mass transfer in such industrial systems is the strong forces of buoyancy. Full article

This study introduces an efficient and accurate two-stage explicit computational scheme for solving partial differential equations (PDEs) containing first-order time derivatives. The suggested method is a modification of the classical Runge–Kutta scheme that introduces a new first-stage formulation. This minimizes numerical error with moderate step sizes while preserving the stability region of the classical method. Spatial discretization is performed using a sixth-order compact finite-difference scheme to obtain high-resolution solutions. The analysis of stability and convergence is strictly determined for both scalar and system forms of convection–diffusion-type equations. To illustrate the suitability of the method, a dimensionless mathematical model of the unsteady, incompressible, laminar flow of a Prandtl-type non-Newtonian nanofluid over a Riga plate is considered, accounting for viscous dissipation, thermophoresis, Brownian motion, and a magnetic field. Here, the Prandtl ternary nanofluid is defined as a non-Newtonian nanofluid that follows the Prandtl rheological model, and it exhibits three critical transport phenomena: heat conduction, viscous dissipation, and nanoparticle diffusion. Representative values of the Prandtl number $P_r=3$ and Reynolds number $R_e=5$ are used to perform the simulation, and other parameters, including but not limited to the Hartmann number $H_a$, Williamson number $W_e$, thermophoresis $N_t$ and Brownian motion $N_b$, are varied to evaluate the flow behavior. Moreover, an artificial neural network (ANN)-developed surrogate model is used to calculate the skin friction coefficient and the local Sherwood number, using five input parameters: the Reynolds number, Prandtl number, Schmidt number, Brownian motion parameter, and thermophoresis parameter. The governing partial differential equations yield high-fidelity numerical data used to train the surrogate model. The data is split into 80% for training, 10% for validation, and 10% for testing. The ANN is tested using regression analysis and error histograms, which demonstrate high accuracy and generalization capacity. Numerical simulation combined with AI-based prediction is a cost-efficient method for real-time estimation of complex non-Newtonian nanofluid systems. Full article

The present study investigates the magnetohydrodynamic (MHD) flow characteristics of a blood-based ternary nanofluid (Au/Cu/Al₂O₃-blood) in stenosed arteries, with a focus on symmetry-inspired modeling rooted in the axial symmetry of arterial geometry and the symmetric distribution of external physical fields (magnetic field, thermal radiation). The findings offer significant insights into the realm of hyperthermia therapy and targeted drug delivery within the domain of biomedical engineering. A mathematical model is established under a cylindrical coordinate system (consistent with arterial axial symmetry), integrating key physical effects (thermal radiation, chemical reactions, viscous dissipation, body acceleration) and fractional-order dynamics via Caputo derivatives—while ensuring the symmetry of governing equations in time and space. The numerical solutions for velocity and temperature profiles are obtained using the Laplace transform and Concentrated Matrix-Exponential (CME) method, a technique that preserves symmetric properties during the solution process. The results of the study indicate the following: The Hartmann number, which is increased, has been shown to reduce axial velocity due to the Lorentz force, thereby maintaining radial symmetry. Furthermore, thermal radiation has been demonstrated to raise fluid temperature, a critical factor in heat-based therapies, with the temperature field evolving symmetrically. In addition, it has been observed that ternary nanoparticles outperform single and binary systems in heat and mass transfer via symmetric dispersion. This work contributes to the existing body of knowledge by integrating symmetry principles into the study of fractional dynamics, electromagnetic fields, and body acceleration modeling. It establishes a comprehensive biomedical flow framework. It is imperative that future research explore pulsatile flow under symmetric boundaries and validate the model through experimental means. Full article

Ternary hybrid nanofluid have been revealed to possess a wide range of application disciplines reaching from biomedical engineering, detection of cancer, over or photovoltaic panels and cells, nuclear power plant engineering, to the automobile industry, smart cells and and eventually to heat exchange systems. Inspired by the recent developments in nanotechnology and in particular the high potential ability of use of such nanofluids in practical problems, this paper deals with the flow of a three phase nanofluid of MWCNT-Au/Ag nanoparticles dispersed in blood in the presence of a bidirectional stretching sheet. The model derived in this study yields a set of linked nonlinear PDEs, which are first transformed into dimensionless ODEs. From these ODEs we get a dataset with the help of MATHEMATICA environment, then solved using AI-based technique utilizing Levenberg Marquardt Feedforward Algorithm. In this work, flow characteristics under varying physical parameters have been studied and analyzed and the boundary layer phenomena has been investigated. In detail horizontal, vertical velocity profiles as well as temperature distribution are analyzed. The findings reveal that as the stretching ratio of the surface coincide with an increase the vertical velocity as the surface has thinned in this direction minimizing resistance to the fluid flow. Full article

Nanoparticle additives are used to increase the cooling efficiency of cutting fluids in machining. In this study, changing dynamic viscosity values depending on the addition of nanoparticles to cutting oils was investigated. Mono nanofluids were prepared by adding hBN (hexagonal boron nitride), ZnO, MWCNT (multi-walled carbon nanotube), TiO₂, and Al₂O₃ as nanoparticles, hybrid nanofluids were prepared by using two types of nanoparticles (ZnO + MWCNT, hBN + MWCNT etc.), and ternary nanofluids were prepared by using three types of nanoparticles. GPR (Gaussian process regression) was used to estimate unmeasured dynamic viscosity values using the dynamic viscosity values measured for different temperatures. Dynamic viscosity results are a precise determination (R² = 1). An augmented dataset was obtained by adding the dynamic viscosity values estimated with high accuracy. A fitness function based on dynamic viscosity and nanoparticle unit costs was proposed for the cost analysis. With the help of the proposed fitness function, it was observed that the best performing nanoparticles were the ZnO and ZnO hybrid mixtures according to different dynamic viscosity and cost effects. The study showed that the most suitable nanofluid selection focused on performance and cost could be made without performing experiments under various operating conditions by increasing the limited experimental measurements with strong GPR estimates and using the proposed fitness function. Full article

This study investigates magnetohydrodynamic (MHD) heat and mass transport in a water-based ternary hybrid nanofluid flowing past an exponentially accelerated vertical porous plate. Two critical scenarios are analyzed: (i) uniform heat flux with variable mass diffusion and (ii) varying heat source with constant species diffusion. The model integrates thermal radiation, heat sink/source, thermal diffusion, and chemical reaction effects to assess flow stability and thermal performance. Governing equations are non-dimensionalized and solved analytically using the Laplace transform method, with results validated against published data and finite difference method outcomes. Ternary hybrid nanofluids exhibit a significantly higher Nusselt number compared to hybrid and conventional nanofluids, demonstrating superior heat transfer capabilities. Magnetic field intensity reduces fluid velocity, while porosity enhances momentum transfer. Thermal radiation amplifies temperature profiles, critical for energy systems. Concentration boundary layer thickness decreases with higher chemical reaction rates, optimizing species diffusion. These findings contribute to the development of advanced thermal management systems, such as solar energy collectors and nuclear reactors, enhance energy-efficient industrial processes, and support biomedical technologies that require precise heat and mass control. This study positions ternary hybrid nanofluids as a transformative solution for optimizing high-performance thermal systems. Full article

The natural convection heat transfer of a trihybrid nanofluid comprising Fe₂O₃, MoS₂, and CuO nanoparticles dispersed in water (Fe₂O₃ + MoS₂ + CuO/H₂O) has been investigated within a cavity exposed to a uniform magnetic field. Three cold fins were strategically positioned on the top, right, and left walls of the enclosure. The study employs numerical simulations conducted using a custom-developed FORTRAN code. The computational approach integrates the finite volume method and full multigrid acceleration to solve the coupled governing equations for continuity, momentum, energy, and entropy generation, along with the associated boundary conditions. Prior to obtaining the results, a meticulous parameterization process was undertaken to accurately capture the fluid dynamics and thermal behavior characteristic of this geometric configuration. The findings underscored the key parameters’ significant impact on the flow structure and thermal performance. The results revealed that natural convection is more dominant at high Rayleigh and low Hartmann numbers, leading to higher Nusselt numbers and stronger dependence on the tilt angle α. Moreover, the optimal heat transfer conditions were obtained for the following parameters: Ha = 25, α = 45°, ϕ = 6%, and Ra = 10⁶ with a rate of 4.985. This study offers valuable insights into achieving a balance between these competing factors by determining the optimal conditions for maximizing heat transfer while minimizing entropy generation. The findings contribute to enhancing the design of thermal systems that utilize magnetic nanofluids for efficient heat dissipation, making the research particularly relevant to advanced cooling technologies and compact thermal management solutions. Full article

Nanofluids have improved thermophysical properties compared to conventional fluids, which makes them promising successors in fluid technology. The use of nanofluids enables optimal thermal efficiency to be achieved by introducing a minimal concentration of nanoparticles that are stably suspended in conventional fluids. The use of nanofluids in technology and industry is steadily increasing due to their effective implementation. The improved thermophysical properties of nanofluids have a significant impact on their effectiveness in convection phenomena. The technology is not yet complete at this point; binary and ternary nanofluids are currently being used to improve the performance of conventional fluids. Therefore, this work aims to theoretically investigate the ternary nanofluid flow of a couple stress fluid in a vertical channel. A homogeneous suspension of alumina, cuprous oxide, and titania nanoparticles is formed by dispersing trihybridized nanoparticles in a base fluid (water). The effects of pressure gradient and viscous dissipation are also considered in the analysis. The classical ternary nanofluid model with couple stress was generalized using the fractal–fractional derivative (FFD) operator. The Crank–Nicolson technique helped to discretize the generalized model, which was then solved using computer tools. To investigate the properties of the fluid flow and the distribution of thermal energy in the fluid, numerical methods were used to calculate the solution, which was then plotted as a function of various physical factors. The graphical results show that at a volume fraction of 0.04 (corresponding to 4% of the base fluid), the heat transfer rate of the ternary nanofluid flow increases significantly compared to the binary and unary nanofluid flows. Full article

The study investigates the performance of fluid flow, thermal, and mass transport within a cavity, highlighting its application in various engineering sectors like nuclear reactors and solar collectors. Currently, the focus is on enhancing heat and mass transfer through the use of ternary hybrid nanofluid. Motivated by this, our research delves into the efficiency of double-diffusive natural convective (DDNC) flow, heat, and mass transfer of a ternary hybrid nanosuspension (a mixture of Cu-CuO-Al₂O₃ in water) in a quadrantal enclosure. The enclosure’s lower wall is set to high temperatures and concentrations (${\mathrm{T}}_{\mathrm{h}}$ and ${\mathrm{C}}_{\mathrm{h}}$), while the vertical wall is kept at lower levels (${\mathrm{T}}_{\mathrm{c}}$ and ${\mathrm{C}}_{\mathrm{c}}$). The curved wall is thermally insulated, with no temperature or concentration gradients. We utilize the finite element method, a distinguished numerical approach, to solve the dimensionless partial differential equations governing the system. Our analysis examines the effects of nanoparticle volume fraction, Rayleigh number, Hartmann number, and Lewis number on flow and thermal patterns, assessed through Nusselt and Sherwood numbers using streamlines, isotherms, isoconcentration, and other appropriate representations. The results show that ternary hybrid nanofluid outperforms both nanofluid and hybrid nanofluid, exhibiting a more substantial enhancement in heat transfer efficiency with increasing volume concentration of nanoparticles. Full article