Purpose Nanofluids flow containing microorganisms are widely used in targeted drug delivery systems and biomedical devices. Based on these recent applications, the current study aims to explore the unsteady bioconvective flow driven by gyrotactic microorganisms of a Williamson–Buongiorno nanofluid through a rotating porous channel. Special attention is provided to the effects of thermal radiation, Soret effect, Dufour effect, chemical reaction and active–passive control of nanoparticles flux strategies. Design/methodology/approach The governing nonlinear partial differential equations are properly non-dimensionalized and then tackled numerically using an implicit finite-difference scheme of the Crank-Nicolson method. Alongside, Taguchi–analysis of variance (ANOVA) optimization is implemented to quantify the relative dominance of the governing parameters to the rate of bioconvection. Findings The passive control of nanoparticles flux showcases more significant impact over all the profiles in comparison to active control. Thermal radiation is observed to increase the heat transfer rate within the system, whereas the presence of chemical reaction affects the nanoparticles distribution and changes the bioconvective flow pattern. Taguchi–ANOVA confirms the dominance of the chemical reaction parameter followed by bioconvection Peclet number, over the bioconvection rate for both actively and passively controlled nanoparticles flux. Originality/value Bioconvective flow of Williamson–Buongiorno nanofluid with active–passive control of nanoparticles flux in a porous channel is the uniqueness of this study. In addition, this research demonstrates an advanced blend of numerical and optimization approach towards nanofluid dynamics.
Purpose This paper aims to explore a new collocation technique using the Chebyshev polynomial to investigate the magnetohydrodynamic Jeffrey–Hamel blood flow through an arterial tube. Applying the Chebyshev Collocation Method to the reduced one-dimensional third-order differential equation yields a system of nonlinear algebraic equations, which is solved numerically. The impact of the transverse magnetic field intensity on the flow parameters is examined, and the numerical results are validated against those obtained using the Bernstein collocation method. The present study confirms that the proposed method ensures both accuracy and computational efficiency. Furthermore, the product of the plate angle (a) and Reynolds number (Re) enhances the flow velocity, whereas a strong magnetic field significantly modifies the flow behavior. Design/methodology/approach This work investigates the steady Jeffrey–Hamel blood flow model through arterial geometry and presents an accurate numerical solution using the Chebyshev collocation technique. Findings The influence of key physical parameters on the flow characteristics is systematically analyzed to evaluate their relative dominance in shaping the velocity distribution. Originality/value This study advances the numerical analysis of biofluid dynamics by proposing an efficient spectral framework that can be extended to nonlinear flow problems involving magnetic fields. The proposed methodology broadens the applicability of collocation methods in computational fluid dynamics.
Purpose This study aims to predict the response in a fiber-reinforced thermodiffusive medium with rotation and temperature-dependent material characteristics on account of mechanical load. A mathematical framework of the governing equations is obtained by using three-phase-lag theory and space–time nonlocal elasticity. Design/methodology/approach An analytical solution of the complex system is obtained using normal mode analysis approach yielding the distributions of the field quantities. Findings Numerical simulations of the theoretical model are performed using MATLAB software and demonstrated in graphical form. A comparative analysis of the results is done to account the effects of various material parameters, followed by some concluding remarks. Originality/value The present research work is original, as it proposes a novel theoretical model which integrates spatiotemporal nonlocal elasticity and thermodiffusion theory with three-phase-lag. Furthermore, a comprehensive analytical–numerical scheme is provided to analyze the fiber-reinforced response in the current scenario with rotation and temperature-dependent properties, which has not been discussed yet in the earlier studies.
Purpose Using artificial intelligence to model two-phase flow could significantly impact the field of computational science. In this study, neural networks are used to simulate two-phase flow. A new neural network architecture is proposed for two-phase flow simulations, and the evolution of a droplet within a channel under pressure-driven flow is investigated. The neural networks are trained solely using the governing equations along with the initial and boundary conditions. The purpose of this study is to simulate a droplet dynamics in channel using the neural network. Design/methodology/approach The physics-informed neural networks (PINNs) method is used to simulate droplet evolution in channel. Computational fluid dynamics (CFD) is also used to simulate droplet evolution for comparison with the PINNs results. Two connected neural networks are used to simulate the two-phase flow. Different Reynolds numbers are investigated. The velocity and pressure contours obtained from PINNs are compared against CFD, and the interface evolution is analyzed. Findings The PINNs results show good agreement with the CFD study. The findings demonstrate that PINNs are capable of simulating two-dimensional, two-phase flow in a channel. The results for intermediate Reynolds numbers closely match the CFD predictions. The PINNs method satisfies mass conservation and accurately captures the interface dynamics. Both pressure and velocity fields are predicted with acceptable accuracy. Originality/value This study highlights the potential of the PINNs method for simulating two-phase flow phenomena. It represents an initial step in the development of artificial intelligence–based modeling approaches. The findings demonstrate that the PINNs framework can provide a new perspective and methodology for more complicated two-phase flow simulation.
Purpose Aiming to address the drastic amplification of micro-pressure waves (MPWs) produced as 600 km/h high-speed maglev trains pass through tunnels, this study develops a mathematical model focused on the pressure relief space angle (θ) via the asymptotic linear method (ALM) for tunnel hood vented hole design, which provides theoretical and engineering support for relevant aerodynamic optimization. Design/methodology/approach First, the pressure relief space angle (θ) is clearly defined, which unifies geometric parameters including vented hole open ratios, position and quantity into a spherical projection area ratio. Then, by coupling the three-dimensional compressible unsteady Navier–Stokes equations with the k-ε turbulence model and combining the sliding mesh technique, the evolution characteristics of the initial compression wave (ICW) and MPW under different vented hole designs are numerically simulated. Findings A linear relationship between pressure relief space angle integral S and gas emission mass GE, and a negative linear relationship between GE and ICW first pressure gradient peak PF are established. The optimal θ criterion is proposed, and Case 3 reduces MPW amplitudes by 18.95% and 17.52% at 20 and 50 m from the tunnel exit, enabling rapid inverse design and saving computing resources. Originality/value This study innovatively defines the pressure relief space angle to unify multiple vented hole geometric parameters, constructing a novel mathematical model between pressure gradient and θ based on ALM. It realizes rapid inverse design from target MPW mitigation rate to vented hole parameters, significantly saving computing resources and providing a new theoretical tool and engineering basis for aerodynamic optimization of 600 km/h maglev tunnel hoods.
Purpose Cardiovascular diseases caused by arterial stenosis significantly disrupt blood circulation and thermal transport, posing major challenges for biomedical applications such as hyperthermia, targeted drug delivery and thermal therapy. This study aims to develop accurate mathematical models that capture the complex rheological behavior of blood and is therefore essential for improving the design and effectiveness of these treatments. Design/methodology/approach In this study, a fractional-order mathematical model is developed to investigate the thermal performance of a magnetized blood-based hepta-hybrid nanofluid flowing through a stenosed artery under heat generation and absorption conditions. The model incorporates seven nanoparticles, namely gold, copper, silver, zinc oxide, magnesium oxide, titanium oxide and alumina, while the Caputo fractional derivative is used to account for the memory and hereditary characteristics of blood flow that are neglected in conventional integer-order models. The transformed governing equations are solved analytically using the Laplace transform technique to examine the influence of the fractional-order parameter, magnetic field strength, stenosis severity, nanoparticle loading and heat source/sink on the velocity and temperature fields. The results demonstrate that the incorporation of hepta-hybrid nanoparticles substantially enhances the thermal transport capability of blood, while heat generation significantly increases the fluid temperature and heat absorption effectively suppresses the thermal field. Findings Furthermore, increasing the magnetic field strength increases flow resistance and modifies the temperature distribution, whereas the fractional-order parameter provides improved control over both momentum and thermal transport by incorporating memory effects into the flow. These findings indicate that fractional-order modeling provides a more realistic representation of blood-based nanofluid transport in stenosed arteries than classical integer-order approaches. Originality/value The novelty of this work lies in the integration of a Caputo fractional-order framework with a magnetized blood-based hepta-hybrid nanofluid model for stenosed arteries under heat source/sink conditions. Unlike previous studies that primarily considered mono-, hybrid- or ternary nanofluids using conventional formulations, the present model simultaneously captures the coupled effects of seven nanoparticles, magnetic forces, arterial constriction and fractional-order memory behavior, thereby providing a more comprehensive framework for analyzing bio-thermal transport in cardiovascular systems with potential applications in advanced thermal therapies and targeted biomedical treatments.
Purpose This study aims to develop an analytical model for laser-induced photo-thermoelastic wave propagation in a porous semiconductor medium. The main objective is to examine the coupled effects of thermal relaxation, plasma carrier diffusion, elastic deformation and void volume fraction on the transient response of the material. Design/methodology/approach The medium is modeled as an isotropic, homogeneous, elastic and porous semiconductor within the framework of generalized photothermoelastic theory. The governing equations for temperature, displacement, carrier density, void volume fraction and stress are formulated in a one-dimensional dimensionless form. The Laplace transform is applied to convert the coupled time-dependent equations into the transformed domain, and the eigenvalue approach is used to obtain analytical solutions. Numerical inversion is then performed to recover the physical fields in the time domain. Parametric studies are conducted to evaluate the effects of thermal relaxation time, pulsed heat-flux characteristic time and photo-generated carrier lifetime. Findings The results indicate that the coupled field variables are strongly affected by the relaxation and carrier-related parameters. Increasing the thermal relaxation time and the pulsed heat-flux characteristic time reduces the amplitudes of the thermal, mechanical, plasma and porosity responses, demonstrating a clear attenuation effect on the induced waves. The photo-generated carrier lifetime has a pronounced influence on carrier-density distribution and modifies the associated temperature, displacement, void volume fraction and stress fields. The results further show that all field responses are most significant near the boundary and gradually decay with increasing distance. Originality/value This work provides a comprehensive analytical treatment of laser-induced photo-thermoelastic interactions in porous semiconductor materials by incorporating thermal relaxation, plasma transport and porosity effects in a unified model. The proposed formulation and results offer useful insight into wave attenuation, penetration depth and coupled transport behavior, which may support the theoretical analysis and design of semiconductor-based photothermal, optoelectronic and microelectronic systems.
Purpose This study aims to investigate the behavior of doubly stratified micropolar-Casson fluid (CF) flow over a stretching sheet in a porous medium, focusing on heat and mass transfer characteristics in non-Newtonian systems. This work uses deep autoregressive exogenous neural networks optimized via the Levenberg-Marquardt method (DARX-NNs-LMT) to model and predict the underlying nonlinear dynamics. By transforming governing partial differential equations into ordinary differential equations and analyzing the effects of key physical parameters, this study seeks to provide an accurate and efficient computational framework for understanding complex fluid behavior in biomedical and industrial applications.Design/methodology/approach The governing partial differential equations describing the doubly stratified micropolar-CF flow are transformed into a nonlinear system of ordinary differential equations using appropriate similarity transformations. A data set is generated by systematically varying key physical parameters, including Prandtl number, Casson parameter, stratification effects and permeability. A DARX-NNs-LMT is used to model the system. The model performance is evaluated through training, validation and testing phases using error analysis, regression plots and mean squared error to ensure accuracy and convergence.Findings The results of this study demonstrate that the proposed DARX-NNs-LMT model achieves excellent agreement with reference solutions, with errors ranging from 10-2 to 10-9, confirming its accuracy and robustness. Convergence analysis through mean squared error, regression and error histograms validates the predictive capability of the model. This study reveals that increasing the material (micropolar) parameter significantly enhances both the velocity and micro-rotation profiles. Furthermore, variations in stratification, permeability and thermal parameters exhibit notable influences on heat and mass transfer characteristics, highlighting the effectiveness of the proposed computational framework in capturing complex fluid behavior.Research limitations/implications The model relies on simulated data sets and does not incorporate experimental validation. Additionally, the analysis assumes constant physical properties and neglects three-dimensional and time-dependent effects. Despite these limitations, this study provides a reliable computational framework, offering significant implications for extending the model to more complex geometries, variable properties and real-life applications in fluid dynamics and engineering systems.Practical implications The proposed DARX-NNs-LMT framework provides an efficient and accurate tool for predicting heat and mass transfer in complex non-Newtonian fluid systems. In biomedical engineering, it can assist in understanding blood flow behavior under varying thermal and compositional conditions. In industrial applications, the model offers practical value in optimizing polymer processing, chemical transport and thermal management processes. Its computational efficiency reduces reliance on costly numerical simulations, enabling faster design and analysis. The approach can be extended to support real-time monitoring and control in engineering systems involving stratified fluid flows.Social implications This study contributes to societal well-being by advancing the understanding of complex fluid behaviors relevant to biomedical applications, particularly blood flow and related physiological processes. Improved modeling of heat and mass transfer in such systems can support better diagnosis, treatment planning and medical device design. Additionally, the optimization of industrial processes enhances energy efficiency and reduces resource consumption, contributing to environmental sustainability. The integration of artificial intelligence in modeling promotes technological innovation, supporting the development of smarter and more efficient engineering solutions with broader societal benefits.Originality/value This study presents a novel integration of doubly stratified micropolar-CF modeling with a DARX-NNs-LMT. Unlike conventional numerical approaches, the proposed framework efficiently captures complex nonlinear dynamics with high accuracy and fast convergence. The simultaneous consideration of multiple physical effects, including thermal and solutal stratification, micropolarity and porous media, enhances the model's realism. This work offers a valuable computational paradigm that bridges advanced fluid dynamics and artificial intelligence, providing a reliable and scalable approach for solving complex engineering problems.
Purpose Crude oil remains a cornerstone global energy resource, and its rheological and flow characteristics are critical to the efficiency and safety of extraction and pipeline transportation. Existing studies have largely relied on empirical correlations which often fail to capture the underlying physicochemical mechanisms and significant uncertainties arise when operational conditions deviate from the original data range. The purpose of this study is to analyze the rheological and heat transfer characteristics of crude oil to solve a series of problems in engineering applications caused by its complex nature.Design/methodology/approach In this study, a combined experimental and simulation approach is well used. Rheological experiments are conducted on four African crude oil samples using an Anton Paar MCR302 rotational rheometer under different temperatures and shear rates. Three constitutive models (Power-law, Bingham and Herschel-Bulkley) are compared via R 2 to determine the optimal model and parameters (K, n). The fitted results are then applied in Computational Fluid Dynamics (CFD) simulations of a horizontal straight pipe model to analyze velocity distribution, frictional resistance (f), Nusselt number (Nu) and heat transfer coefficient (h).Findings Four crude oil samples exhibit significant shear-thinning behavior and temperature dependence, belonging to pseudoplastic non-Newtonian fluids. The power-law model achieves the highest goodness of fit (R 2 = 0.9). The simulation results show that the power-law index (n) has a significant impact on flow and heat transfer. As the value of n increases, both the central velocity and the friction coefficient increase, while the Nu and h exhibit a decreasing trend, confirming that the shear-thinning behavior can enhance heat transfer efficiency. Viscosity decreases with rising temperature and stabilizes at high shear rates.Research limitations/implications For experiments, this study focuses on four crude oil samples from the only African region, and lacks of study on the complexity and diversity of crude oil in other regions. In numerical simulation, this study only conducted simulation analysis on straight pipes without simulation on complex pipes.Practical implications Through a combination of experimental measurements and numerical simulations, this study effectively reveals the rheological behavior, as well as the flow and heat transfer characteristics of crude oil, which can provide a solid theoretical basis for the efficient transportation of crude oil in pipelines.Social implications Efficient transportation of crude oil is beneficial for economic stability and daily life by ensuring a reliable supply of energy and derived products.Originality/value This study combines rheological experiments with CFD simulations using directly fitted power-law parameters from real crude oil samples. It quantifies how the power-law index n affects f, Nu and h, confirming that the flow and heat transfer characteristics of crude oil can be enhanced in shear-thinning performance. The results of this study provide a theoretical basis for flow assurance of crude oil in a pipe.
Purpose - This paper aims to investigate coupled buoyancy-Marangoni convection in open trapezoidal cavities filled with nano-encapsulated phase change material (NEPCM) suspensions. Design/methodology/approach - A comprehensive numerical investigation is conducted using the Galerkin finite element method with a penalty formulation to eliminate pressure. The dimensionless governing equations are solved for three distinct geometries: trapezoidal with negatively sloped hot wall (trap-), square and trapezoidal with positively sloped hot wall (trap+). The NEPCM suspension is modeled via an apparent heat capacity method capturing latent effects within a prescribed fusion temperature range. Parametric studies span Marangoni numbers (- 5000 <= Ma <= 8000), NEPCM concentrations (0.0 <= phi <= 0.05), Prandtl numbers (0:054 <= Pr <= 6.2) and fusion temperatures (0.05 <= Theta(F) <= 0.3). Findings - The trap + geometry uniquely optimizes coupling between buoyant and thermocapillary forces, sustaining the strongest circulation at high Marangoni numbers and promoting the most extensive phase change region. NEPCM concentration significantly boosts heat transfer in square and trap + cavities at moderate Rayleigh numbers, yet its effect diminishes in trap- geometries and under strong Marangoni dominance. Research limitations/implications - The present findings are applicable to steady-state, laminar flow regimes, providing a foundational understanding for low-to-moderate Reynolds number applications such as small-scale solar receivers and open-channel micro-coolers. However, several limitations must be acknowledged: the numerical model assumes a two-dimensional domain, which neglects potential three-dimensional end-wall effects and vortex stretching that may occur in wider industrial cavities. Practical implications - The findings provide design guidance for open-cavity thermal systems such as solar receivers. Originality/value - By analyzing the interaction between surface-tension-driven flow and buoyancy forces, this work provides a detailed physical interpretation of how interfacial transport mechanisms govern thermal storage density. Unlike conventional enclosed configurations, the combination of an open boundary, trapezoidal geometry and NEPCM suspensions introduces a distinct hydrodynamic environment in which Marangoni-induced shear at the free surface significantly alters particle dynamics. This study presents the first comprehensive analysis of coupled buoyancy-Marangoni convection in such systems, while also identifying optimal operating conditions for enhanced heat transfer.
Purpose This study aims to investigate the effect of cavity inclination on thermosolutal mixed convection in a three-dimensional porous enclosure filled with a Cu-Al2O3/water hybrid nanoliquid. The objective is to evaluate the enhancement of mass and heat transmission performance compared to conventional nanofluids and pure water under different flow conditions, with particular emphasis on the effect of cavity inclination in aiding and opposing flow situations.Design/methodology/approach The three-dimensional porous container is differentially heated and concentrated, where the two vertical walls move in opposite directions at a constant velocity, while the remaining walls are fixed and adiabatic. The steady dimensionless governing equations are solved numerically using the finite volume method, and the porous structure is modeled using the Darcy-Brinkman-Forchheimer formulation. The analysis focuses on several governing parameters, including the buoyancy ratio, Darcy number, inclination angle, nanoparticle volume fraction, and Richardson number. The findings are presented in terms of the average Nusselt and Sherwood numbers as well as velocity profiles, while the isotherms, isoconcentration, and streamline contours are illustrated through both two-dimensional and three-dimensional representations.Findings The findings show that the hybrid nanofluid achieves better mass and heat transport performance compared to the single nanofluid. Furthermore, the effect of cavity inclination is shown to depend on the type of flow situation; for the aiding flow case (Br = 2), both Nuavg and Shavg increase with the inclination angle up to 30 degrees for pure water and up to 45 degrees for both types of nanofluids, beyond which a gradual reduction is observed, while the opposing flow case (Br = -2) exhibits the opposite trend. Moreover, the addition of nanoparticles to the clear water deteriorates heat transmission for particular Darcy and Richardson numbers, even yielding lower performance than pure water, due to the increase in viscosity outweighing the enhancement in thermal conductivity.Originality/value To the best of the authors' knowledge and based on the available literature, no study has addressed thermosolutal mixed convection in an inclined three-dimensional porous enclosure using hybrid nanofluids with two-sided lid-driven boundary conditions. Therefore, the current work offers new and valuable insights into the combined effects of cavity inclination and hybrid nanoliquid on mass and heat transmission characteristics.
Purpose The purpose of this study is to investigate the combined effects of stenosis geometry and hematocrit (Hct)-dependent blood rheology on coronary hemodynamics. While geometric asymmetry and viscosity variation individually influence flow behavior, their coupled impact remains insufficiently characterized. Clarifying this interaction is important for improving the relevance of patient-specific numerical hemodynamic analyses in clinical diagnostic contexts, where variations in vascular structure and Hct can significantly affect disease progression.Design/methodology/approach A patient-specific left coronary artery with 70% luminal narrowing was reconstructed from computed tomography imaging and analyzed for concentric and eccentric (Type I and II) lesions. Pulsatile flow was simulated using a finite-element incompressible Navier-Stokes framework with a Carreau non-Newtonian viscosity model at Hct levels of 25%, 45% and 65%. The model was validated against established experimental and numerical simulation data, and key hemodynamic and energetic metrics were evaluated over the cardiac cycle.Findings Eccentric Type II lesions produced the greatest flow disruption, characterized by strong post-stenotic separation, elevated oscillatory shear and increased pressure losses. Hct regulated flow stability, with reduced viscosity enhancing inertial effects and residence time and increased viscosity amplifying dissipative losses. Geometric asymmetry caused uneven momentum redistribution, generating skewed jets and persistent secondary vortices that promoted transitions from coherent pulsatile flow to vortex-dominated dynamics.Originality/value This work presents a patient-specific computational framework that integrates lesion eccentricity with Hct-driven non-Newtonian blood behavior. By isolating the coupled effects of morphology and rheology, this study provides a physically grounded basis for interpreting coronary flow disturbances and supports improved non-invasive cardiovascular risk assessment.
Purpose Magnetically controlled ferrofluid convection is central to advanced thermal technologies such as electronic cooling, microfluidic actuators, magnetic energy systems and smart heat exchangers, where precise heat transfer control is required. This study aims to numerically investigate ferrohydrodynamic and magnetohydrodynamic buoyancy-driven convection of a ferrofluid inside an enclosure equipped with internal crescent-shaped heaters, considering the combined effects of magnetic forces and nonlinear thermal radiation. Design/methodology/approach The governing equations are solved using the finite element method, and the impacts of the Rayleigh number, Hartmann number, radiation parameter, Eckert number, corrugated cooler’s length and heater configuration are systematically examined. In addition, a Multilayer Perceptron Artificial Neural Network (ANN) is developed and validated to anticipate heat transfer features, offering a reliable surrogate model for parametric exploration and optimization. Findings The results show that increasing buoyancy and thermal radiation strengthens circulation cells and enhances heat transfer, while strong magnetic fields suppress flow intensity and shift the transport mechanism toward conduction-radiation dominance. Heater arrangement is found to play a decisive role in shaping flow topology, with vertically aligned heaters generating stronger vortices and higher Nusselt numbers than other configurations. An ANN is developed and validated against numerical data, demonstrating high predictive accuracy and providing an efficient surrogate tool for rapid prediction and optimization of magneto-thermal systems. Originality/value The current work presents a detailed ANN-assisted numerical study of coupled FHD and MHD buoyancy-driven convection within a ferrofluid-loaded octagon-shaped enclosure comprising internal crescent-shaped heaters under nonlinear thermal radiation effects, which has received limited attention in the literature.
Purpose The purpose of this study is to investigate the start-up (0-3 s) transient conjugate cooling behavior in a confined cylindrical cavity driven by annular-plenum multi-jet impingement. Although jet impingement cooling has been extensively studied under steady-state conditions, existing research has primarily focused on single-jet configurations or simplified open domains, with limited attention paid to the start-up thermal response of confined multi-jet systems. In practical high heat-flux applications, however, the transient cooling capacity during the initial operating stage is often critical for preventing local overheating and thermal failure. To address this gap, a normalized cooling index (NCI) is induced to transient cooling for evaluating both mean cooling and hot-spot suppression.Design/methodology/approach A three-dimensional transient conjugate heat-transfer model is developed using unsteady Reynolds-averaged Navier-Stokes (URANS) simulation with the SST turbulence model. An initial-temperature treatment is introduced for the solid domain to effectively capture the start-up thermal evolution of the coupled fluid-solid system. Grid independence and model reliability are validated against a benchmark case of a circular impinging jet. The influence of Reynolds number (),), inlet temperature () and geometric height ratio () are systematically investigated. The proposed NCI is defined by combining the average solid temperature and the maximum local temperature (), allowing simultaneous evaluation of mean cooling performance and local thermal non-uniformity.Findings The start-up cooling process exhibits a two-stage behavior. The early stage is convection-dominated and characterized by stagnation impingement, wall-jet development and cavity recirculation, whereas the later stage is increasingly limited by solid thermal capacitance and internal conduction. Increasing improves both mean cooling and hot-spot suppression; however, the enhancement becomes progressively weaker due to confinement effects, jet interaction and crossflow interference. Variations in mainly affect the absolute temperature level and show little influence on NCI within the range of 283-303 K. A moderate geometric height ratio ( 0.5) provides the best overall cooling performance by balancing jet impingement intensity and flow recirculation. The optimal operating condition is identified as = 40 m/s, = 283 K and = 0.5.Originality/value This study extends conventional impingement-cooling research from steady-state analysis to start-up transient conjugate cooling in a confined cylindrical cavity with annular multi-jet impingement. It clarifies the stage-dependent cooling mechanisms governing transient thermal evolution and introduces NCI as a unified dimensionless metric for assessing overall cooling performance and hot-spot mitigation. The results provide theoretical support and design guidance for thermal management in confined high heat-flux systems requiring rapid and reliable start-up cooling.
Purpose The purpose of this study is to investigate surface conditions that improve flow and thermal transport properties, which are essential for engineering systems, industrial processes and electronic cooling systems. Tetra hybrid nanofluids find applications in multiple industries due to their effective management of flow and heat transport.Design/methodology/approach A system of nondimensional partial differential equations is obtained from the original set of multidimensional, nonlinear PDEs by applying suitable non-similarity transformations. The oscillatory changes in wall velocity induced by surface roughness are illustrated as a sinusoidal waveform at the nominal mean surface.Findings Both graphical and tabular representations are used to provide an exhaustive analysis of key parameters related to flow dynamics and thermal performance. The rough surface of the cylinder induces sinusoidal variations in the skin friction coefficient, with the amplitude of these variations increasing with growing values of n. The rate of heat transfer through the wall in the presence of a rough surface exhibits a more pronounced oscillatory decrease along the wall length. The sinusoidal changes have a greater impact due to a periodic magnetic field (M). The present outcomes are validated through comparison with earlier results, indicating complete consistency with previous studies.Originality/value This research presents a numerical solution of Newtonian tetra hybrid nanofluid flow over a slender cylinder, accounting for surface roughness and a periodic magnetic field. The tetrahybrid nanofluid is composed of Ag-Au-Cu-TiO2 nanoparticles that enhance heat transfer due to their high thermal conductivity.
Purpose This study aims to explore an investigation of stagnation-point flow and thermal transport characteristics of a radiative ternary hybrid nanofluid, consisting of engine oil as the base fluid, supplemented with nanoparticles of , Cu and . It addresses the flow on a stretching/shrinking surface, accounting for the effects of velocity slip and melting.Design/methodology/approach The corresponding partial differential equations are then converted into self-similar equations and are solved using MATLAB's bvp4c algorithm. Since the model has two solution branches, a linear stability analysis is conducted to select the physically relevant flow regime. The high level of statistical regression indicates the strength of the model, as evidenced by the significant F-statistic, low p-value and high coefficient of determination.Findings The findings indicate that a higher rate of melting and high rates of slip amplify momentum and thermal boundary layers, resulting in better heat transfer performance, and a decreased value of the parameters causes dual-solution behaviour and a delay in the boundary-layer separation.Originality/value Due to these features, the applications of the findings, in terms of polymer extrusion, storage of thermal energy, cooling of phase changes, the nano-lubrication systems and a sophisticated manufacturing process with high thermal loads, show high applicability.
Purpose The present study aims to develop a comprehensive multi-physics model to analyze heat transfer and coupled thermo–mechanical–carrier behavior in a mechanically damaged semiconductor medium with triple porosity, incorporating memory-dependent heat conduction and Klein–Gordon (KG)-type nonlocal effects. Design/methodology/approach A unified theoretical framework is formulated by integrating memory-dependent modified Lord–Shulman (MDMLS) heat conduction models with nonlocal elasticity and carrier transport in a triple-porous semiconductor medium. The governing coupled partial differential equations are reduced using normal-mode analysis, leading to a system of algebraic equations. The characteristic equation is solved analytically to obtain the displacement, temperature, carrier concentration, void volume fraction and stress fields. Numerical simulations based on silicon material parameters are performed to study the effects of memory, nonlocality and mechanical damage. Findings The results reveal that thermo-mechanical and transport responses are strongly localized within a near-surface interaction zone governed by decaying eigenmodes. Memory-dependent heat conduction significantly alters the amplitude and attenuation of field variables. Research limitations/implications The analysis is restricted to a linearized, two-dimensional half-space configuration and assumes idealized boundary conditions. Experimental validation and extension to nonlinear, transient or three-dimensional configurations are not considered and may be addressed in future work. Practical implications The proposed model provides insights into heat transfer and wave propagation in semiconductor materials with complex microstructures. The findings are relevant for the design of micro/nano-electronic devices, thermal management systems, porous coatings and semiconductor components subjected to coupled thermal and mechanical loading. Originality/value This work presents the first unified formulation combining triple porosity, mechanical damage, memory-dependent heat conduction and KG-type nonlocality in semiconductor media. The study offers new physical insights into boundary-dominated multiphysics interactions and provides a novel analytical–numerical framework for advanced heat transfer modeling in complex porous materials.
Purpose This study aims to examine unsteady axisymmetric magnetohydrodynamic flow and heat transfer above a permeable disk stretching radially. Design/methodology/approach The accounted model incorporates nonlinear thermal radiation, viscous dissipation, Joule heating and the Cattaneo–Christov heat-flux relation. A TiO2–CoFe2O4/H2O hybrid nanofluid is represented through commonly used effective-property formulas. By means of a similarity transformation, the governing boundary-layer equations are reduced to a coupled nonlinear ordinary differential system, which is then solved with MATLABbvp4c. Findings The calculations indicate that thermal relaxation changes the near-wall temperature response and, for the parameter range studied here, produces a slight increase in the reduced Nusselt measure NuRe−1/2. The Fourier result is recovered smoothly as Λ→0. Radiation and viscous heating raise the temperature field and modify entropy production, whereas magnetic forcing slows the flow and changes the irreversible behavior through Joule dissipation. Suction narrows the boundary layer and improves wall heat removal. The results also show that increasing hybrid nanoparticle loading does not translate into a proportionally larger heat-transfer gain, because the rise in conductivity is accompanied by changes in effective heat capacity and momentum resistance. Originality/value This study clarifies how thermal relaxation, radiation, magnetic forcing, wall mass transfer and hybrid loading act together in heat transfer and entropy generation over a stretching disk.
Purpose This study aims to present an analytical–numerical investigation of wave propagation in a magneto-thermoelastic double-porosity medium within the framework of the dual-phase-lag (DPL) heat conduction model, incorporating the Thomson effect. Design/methodology/approach The governing equations are formulated and solved using the normal mode technique to obtain analytical expressions for the principal physical fields. Numerical simulations for copper are performed to examine the influence of the Thomson parameter, relaxation times and time on temperature, displacement, stress and concentration distributions. Findings The principal conclusion is that the Thomson effect and DPL heat conduction have a pronounced impact on wave propagation in magneto-thermo-elastic double-porosity media, leading to reduced amplitudes, altered wave speeds and different thermo-mechanical responses compared with traditional generalized thermo-elastic theories. The DPL framework offers a more realistic model for materials exhibiting microstructural heat-transfer delays and coupled thermal–mechanical–magnetic interactions. Originality/value The results show noticeable variations in the amplitudes and propagation behavior of the physical quantities under different parameter values, highlighting the strong coupling between thermal, mechanical and diffusive effects. A comprehensive quantitative evaluation, including numerical values, is presented in the numerical analysis section.
