Heat Transfer Rate Research Articles

Numerical simulation of an impinging jet array in a square channel covered by a porous layer

AbstractIn many heat transfer applications, the design of the flow field should warrant high heat transfer rates and, meanwhile, reduce the thermal stresses so that hot spots along the heat transfer surface be avoided. A combination of multiple jets impinging on a channel bed together with the surface covered by a porous layer is proposed to satisfy both objectives in the current study. A three‐dimensional numerical simulation using a finite volume method with the second‐order discretization has been applied to visualize the multiple‐impinging jet flow behavior. The impacts of the porous medium parameters, including the thickness, permeability, and porosity, on the magnitude and distribution of the heat transfer along the channel bed have been evaluated. It is shown that the overall heat transfer performance of the proposed flow is significantly improved in comparison with the conventional case of the fluid flowing parallel to the channel bed. The presence of the porous layer leads to a more even spread of the fluid on the target surface, which reduces the thermal stresses and prevents the large differences between the highest and lowest values of heat transfer coefficients. They also found that both the porosity and particularly the permeability of the porous layer enhance the effect of the crossflow along the flow associated with the multiple‐impinging jet setup. For a certain thickness of the porous layer, it is possible to reduce the amplitude of the Nusselt number oscillations effectively, while keeping the overall Nusselt number desirably high.

Subcooled flow boiling characteristics and CHF in an eccentric annulus at low pressure conditions

Controlled flow boiling conditions enhance the heat transfer rate in various industrial applications such as heat exchangers, fuel rod bundles etc. In nuclear industry, the presence of mixing vanes, spacers, channel creep deformation etc., may lead to the formation of narrow and wide zones around the fuel rods. The asymmetry in the cross-sectional flow area around the fuel rod can be modelled as eccentricity which may cause an irregular coolant flow distribution affecting the heat transfer rate. In the present study, the eccentricity (e) is defined as the ratio of offset (s) to the difference in radii of inner and outer cylinders (Ro−Ri). The current study introduces a framework that involves calibrating the departure size of vapour bubble (D) in the EMF model framework which enables the accurate prediction of subcooled flow boiling characteristics and CHF power in an annulus (0.0≤e≤0.50) at low operating pressure conditions. The developed framework is validated with experimental data and a very good match is noticed. It is observed that eccentricity causes a decrease in coolant peak velocity magnitude by 12.8% in the narrow zone for e=0.50. In the subcooled region, the accumulation of vapour bubbles impedes further heat transfer to the liquid coolant, and thus the peak heated wall temperature (≈380.88K) is observed in the narrow zone for e=0.50. Eccentricity causes early coolant phase change which in turn results in early occurrence of CHF (q=522KWm−2) in the narrow zone of e=0.50. A quadratic relationship is also established to predict the CHF power in terms of eccentricity (e) within 5% variation.

Electroosmotic effect on the flow of hybrid nanofluid containing para and ferri-magnetic nanoparticles through the micro-channel implementing Darcy law

This study investigates the flow of an incompressible electroosmotic hybrid nanofluid through a micro-channel. The hybrid nanofluid consists of paramagnetic (Ta) and ferrimagnetic (Fe3O4) nanoparticles suspended in ethylene glycol. The Darcy model is applied to the porous media in the momentum equation, and its effects are also considered in the temperature equation, accounting for frictional and Joule heating effects. The micro-channel is influenced by both pressure and magnetic flux. The study derives an exact solution for the proposed model and evaluates key engineering parameters, such as the heat transfer rate. The findings show that a higher particle volume fraction reduces the velocity distribution, while an increased Darcy parameter decreases the rate of heat transfer. Additionally, the heat transfer rate diminishes with increasing Darcy parameter and electric flux. Notably, the ferrimagnetic nanofluid exhibits better thermal conductivity than the paramagnetic nanofluid.

Thermal analysis on Ferro Casson nanofluid flow over a Riga plate with thermal radiation and non-uniform heat source/sink

Ferro hybrid nanofluids can be used in electronics and microelectronics cooling applications to reduce heat accumulation and efficiently remove surplus heat. These nanofluids aid to maintain optimum operating temperatures and reduce device overheating by enhancing the heat transfer rate. With this motivation, the aim of the present numerical analysis is to study the three-dimensional incompressible hybrid nanofluid flow over a slippery Riga surface by combining the Casson fluid model. Mathematical modeling is constructed with nanoparticles as Fe3O4 and CoFe2O4 with base fluid as water. The non-uniform heat source/sink and thermal linear radiation effects are taken into account with the Hamilton–Crosser thermal conductivity model. A system of nonlinear PDEs is produced by the proposed problem and then the relevant similarity variables are implemented to transform the set of partial differential equations and their accompanying boundary conditions into the coupled nonlinear differential equations with one independent variable. These modified ordinary differential equations (ODEs) were then successfully solved with the Runge–Kutta fourth-order method by combining via the shooting technique. With the aid of graphical representations, the effects of various influencing parameters were presented and analyzed comprehensively. Furthermore, the impacts of relevant parameters on heat transfer rates and shear stress are concisely discussed and illustrated in tabular forms. The significant findings include the enhancement of the radiation parameter increases the thermal boundary layer thickness and the thickness increases whenever surface experiences slippery conditions. The axial and transverse momentum of the fluid are controlled with the Casson parameter. An effective connection is noticed once the current numerical solutions are verified under particular conditions that were previously described.

Fractional modeling of unsteady flow of Jeffrey fluid using active and passive control strategies

The current work is focused on the analysis of heat and mass transfer in a magnetohydrodynamics Jeffrey nanofluid flows across a vertical plate because of these possible uses. Free convection, magnetic effect, and thermo-diffusion properties are all applied to the flow considered here. The modeling also takes into account the passive and active control of the Jeffrey nanofluid. The constant proportional Caputo fractional operator which was recently introduced is used in this work together with generalized Fick’s and Fourier’s law. Using suitable nondimensional variables, ordinary differential equations are obtained from the modeling equations, and the Laplace transform method is used to solve these modeled equations. The concentration and temperature profiles are rising functions of the fractional and thermophoresis parameters, and they drop more quickly as the values of the Schmidt, Prandtl, and Nb (Brownian motion parameters) rise. The constant proportional Caputo (CPC) fractional derivative is the best choice for achieving more stable concentration, temperature, and velocity than conventional fields. Raising the values of α will increase the rate of heat transfer and skin friction coefficient. Additionally, as compared to the classical model, the constant proportional Caputo derivative model shows more decay nature. Consequently, compared to the classical model, the constant proportional Caputo differential model has a superior memory function.

Numerical analysis of heat transfer and fluid flow structures of jet impingement on a flat plate with different shapes of roughness elements

Jet impingement is a heat transfer technique utilized in different applications in industry. It is used for cooling the turbine blade and the combustor wall because of its high cooling rate. The heat transfer (HT) and flow structure of a circular air-impinging jet over a flat target plate with a circular row of 48 roughness elements are numerically investigated using renormalization group k–ε turbulence model. Different shapes of roughness elements, namely cylindrical roughness elements (CREs), droplet roughness elements (DREs), and hemispherical roughness elements (HREs), are examined. The effects of Reynolds number changed from 7,000 to 35,000, and the roughness elements location relative to jet diameter ( s / d ) of 1.5, 2, 2.5, and 3 at a constant jet-to-target plate distance ( H / d ) of 2 are studied. Temperature distribution, local Nusselt number ( Nu ), average Nusselt number (Nuavg ), average Nusselt number ratio (Nuavg,r ), velocity distribution, turbulence kinetic energy, streamline contours, and static pressure ( p ) over the roughness elements are evaluated and discussed. The results showed that the existence of roughness elements has a significant effect on the thermal and hydraulic characteristics. The Nuavg,r for the CREs, DREs, and HREs is up to 1.61, 2.02, and 1.2, respectively. All roughness element shapes increase the flow velocity in the narrow area between the elements and increase the wetted area. CREs augment the HT rates by increasing the turbulence intensity, while DREs reduce the drag force effects.

Numerical simulation of natural convection in a differentially heated cubical cavity with solid fins

Purpose The performance of solid fins inside a differentially heated cubical cavity is numerically studied in this paper. The main purpose of the study is to make an optimization to reach the maximum heat transfer in the enclosure having the solid fins with studied parameters. Design/methodology/approach The considered domain of interest is a differentially heated cube having heat-conducting solid fins placed on the heated wall while an opposite wall is a cooled one. Other walls are adiabatic. Governing equations describing natural convection in the fluid filled cube and heat conduction in solid fins have been written using non-dimensional variables such velocity and vorticity taking into account the Boussinesq approximation for the buoyancy force and ideal solid/fluid interfaces between solid fins and fluid. The formulated equations with appropriate initial and boundary conditions have been solved by the finite difference method of the second of accuracy. The developed in-house computational code has been validated using the mesh sensitivity analysis and numerical data of other authors. Analysis has been performed in a wide range of key parameters such as Rayleigh number (Ra = 104–106), non-dimensional fins length (l = 0.2–0.8), non-dimensional location of fins (d = 0.2–0.6) and number of fins (n = 1–3). Findings From numerical methods point of view the used non-primitive variables allows to perform numerical simulation of convective heat transfer in three-dimensional (3D) regions with two advantages, namely, excluding difficulties that can be found using vector potential functions and reducing the computational time compared to primitive variables and SIMPLE-like algorithms. From a physical point of view, it has been shown that using solid fins can intensify the heat transfer performance compared to cavities without any fins. Fins located close to the bottom wall of the cavity have a better heat transfer rate than those placed close to the upper cavity surface. At high Rayleigh numbers, increasing the fins length beyond 0.6 leads to a reduction of the average Nusselt number, and one solid fin can be used to intensify the heat transfer. Originality/value The present numerical study is based on hybrid approach for numerical analysis of convective heat transfer using velocity and vorticity that has some mentioned advantages. Obtained results allow intensifying the heat transfer using solid fins in 3D chambers with appropriate location and length.

Hybrid Nanofluid Flow over a Shrinking Rotating Disk: Response Surface Methodology

For efficient heating and cooling applications, minimum wall shear stress and maximum heat transfer rate are desired. The current study optimized the local skin friction coefficient and Nusselt number in Al2O3-Cu/water hybrid nanofluid flow over a permeable shrinking rotating disk. First, the governing equations and boundary conditions are solved numerically using the bvp4c solver in MATLAB. Von Kármán’s transformations are used to reduce the partial differential equations into solvable non-linear ordinary differential equations. The augmentation of the mass transfer parameter is found to reduce the local skin friction coefficient and Nusselt number. Higher values of these physical quantities of interest are observed in the injection case than in the suction case. Meanwhile, the increase in the magnitude of the shrinking parameter improved and reduced the local skin friction coefficient and Nusselt number, respectively. Then, response surface methodology (RSM) is conducted to understand the interactive impacts of the controlling parameters in optimizing the physical quantities of interest. With a desirability of 66%, the local skin friction coefficient and Nusselt number are optimized at 1.528780016 and 0.888353037 when the shrinking parameter (λ) and mass transfer parameter (S) are −0.8 and −0.6, respectively.

Effect of Jet-to-Target Spacing on Flow and Heat Transfer Characteristics for Swirling Impinging Micro-Slot Jets

The influence of jet-to-target spacing on flow and heat transfer behaviors for swirling impinging micro-slot jets has been extensively studied. In this study, two complete revolutions of the generated helix under the slot nozzle thickness of 1.0 mm constrained the total spiraling length to 290 mm. The range of jet-to-target spacing varied from 1 to 6. The turbulent kinetic energy-epsilon model was employed to make predictions at Reynolds numbers from 5000 to 20000. The results showed that the heat transfer enhancement on the target wall depended on the pacing between the jet and the target. This is the jet flow structure exhibited a notable intensity of high-velocity vortices at the low jet-to-target spacing, whereas the jet flow impingement was abruptly reduced at the high jet-to-target spacing. The heat transfer rate also tended to increase as the Reynolds number increased. In addition, when the jet-to-target spacing was at 1, the average heat transfer value was between 32.9% and 54.2% higher than in other conditions due to high fluid acceleration.

Heat dissipation and temperature control method for quantum cascade lasers in external cavity spectral beam combining systems

The thermal effects of quantum cascade lasers (QCLs) can cause wavelength locking instability and reduce output power in external cavity spectral beam combining (EC-SBC) systems. We propose a micro-channel structure (MCH) for heat dissipation and temperature control that rapidly stabilizes the QCL at 20.159°C, showing a linear relationship with the controlled temperature. Experimental comparisons demonstrate that MCH enhances the heat transfer rate within the structure, reducing the time required to stabilize and control QCL temperature. The output power and locked wavelength remain stable in the EC-SBC system under high currents. This study provides technical support for heat dissipation QCL arrays.

Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system

The development of lithium-ion battery technology has ensured that battery thermal management systems are an essential component of the battery pack for next-generation energy storage systems. Using dielectric immersion cooling, researchers have demonstrated the ability to attain high heat transfer rates due to the direct contact between cells and the coolant. However, feedback control has not been widely applied to immersion cooling schemes. Furthermore, current research has not considered battery pack plant design when optimizing feedback control. Uncertainties are inherent in the cooling equipment, resulting in temperature and flow rate fluctuations. Hence, it is crucial to systematically consider these uncertainties during cooling system design to improve the performance and reliability of the battery pack. To fill this gap, we established a reliability-based control co-design optimization framework using machine learning for immersion cooled battery packs. We first developed an experimental setup for 21700 battery immersion cooling, and the experiment data were used to build a high-fidelity multiphysics finite element model. The model can precisely represent the electrical and thermal profile of the battery. We then developed surrogate models based on the finite element simulations in order to reduce computational cost. The reliability-based control co-design optimization was employed to find the best plant and control design for the cooling system, in which an outer optimization loop minimized the cooling system cost while an inner loop ensured battery pack reliability. Finally, an optimal cooling system design was obtained and validated, which showed a 90% saving in cooling system energy consumption.

Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system

The development of lithium-ion battery technology has ensured that battery thermal management systems are an essential component of the battery pack for next-generation energy storage systems. Using dielectric immersion cooling, researchers have demonstrated the ability to attain high heat transfer rates due to the direct contact between cells and the coolant. However, feedback control has not been widely applied to immersion cooling schemes. Furthermore, current research has not considered battery pack plant design when optimizing feedback control. Uncertainties are inherent in the cooling equipment, resulting in temperature and flow rate fluctuations. Hence, it is crucial to systematically consider these uncertainties during cooling system design to improve the performance and reliability of the battery pack. To fill this gap, we established a reliability-based control co-design optimization framework using machine learning for immersion cooled battery packs. We first developed an experimental setup for 21700 battery immersion cooling, and the experiment data were used to build a high-fidelity multiphysics finite element model. The model can precisely represent the electrical and thermal profile of the battery. We then developed surrogate models based on the finite element simulations in order to reduce computational cost. The reliability-based control co-design optimization was employed to find the best plant and control design for the cooling system, in which an outer optimization loop minimized the cooling system cost while an inner loop ensured battery pack reliability. Finally, an optimal cooling system design was obtained and validated, which showed a 90% saving in cooling system energy consumption.

Unsteady MHD‐radiative thin film flow with heat transfer over a stretching surface in porous media

AbstractThis study conducts a computational analysis to explore how magnetic fields, radiation, heat, and mass transfer collectively influence a horizontal stretching sheet within a porous medium. The research focuses on elucidating the dynamics of thin film flow through the formulation of time‐dependent equations and subsequent transformation of fluid flow equations into ordinary differential equations via similarity transformation. The numerical solution is attained employing the Runge–Kutta fourth‐order method coupled with a shooting technique. MATLAB software is utilized to generate graphs and numerical values, offering a detailed representation of engineering‐relevant physical quantities in tabular form. The investigation revealed notable trends associated with varying parameters. Increasing unsteadiness parameters lead to a reduction in velocity, temperature, and concentration fields, while the temperature distribution demonstrates a positive correlation with radiation parameters. Moreover, elevated Prandtl numbers and unsteadiness parameters correspond to augmented heat and mass flux, respectively. Of particular significance is the observed heightened heat transfer rate during the transition from a Prandtl number of 1 (representing air) to 2 (representing oil), alongside an increased mass transfer rate with the escalation in Schmidt number from 0.62 (representing hydrogen) to 0.78 (representing ammonia). A comparative analysis of the numerical findings with existing literature demonstrates excellent agreement, affirming the validity and relevance of the present study. These insights offer valuable implications for understanding and optimizing heat and mass transfer processes in porous media, with potential applications in various engineering and scientific domains.

Suction influence on magneto-convective fluid flow embedded in a permeable media under internal friction

This work examines the natural convection flow of an incompressible, viscous, and electrically conducting fluid down a vertical flat plate in the presence of conduction, as well as the effects of suction, magnetic field, viscous dissipation, porous medium, and heat generation. The governing momentum and energy equations have numerical solutions. The impacts of suction, heat production, magnetic, porosity, and viscous dissipation parameters on two-dimensional flow are discussed. Graphical representations of the velocity profile, temperature distribution, skin friction, rate of heat transfer, and surface temperature distribution are shown. The presence of porous media and improving suction values improves the friction drag but diminishes the energy transfer. The thermal production parameter raises the energy inside the flow but diminishes the heat transfer coefficient. This work attempts to offer important insights into these intricate processes by examining the effects of controlling factors including magnetic fields, porous medium, and suction parameters. This research conclusion may find applications in coolers, heat exchangers, and environmental remediation technologies that are more effective, advancing engineering and sustainable practices.

Suction influence on magneto-convective fluid flow embedded in a permeable media under internal friction

This work examines the natural convection flow of an incompressible, viscous, and electrically conducting fluid down a vertical flat plate in the presence of conduction, as well as the effects of suction, magnetic field, viscous dissipation, porous medium, and heat generation. The governing momentum and energy equations have numerical solutions. The impacts of suction, heat production, magnetic, porosity, and viscous dissipation parameters on two-dimensional flow are discussed. Graphical representations of the velocity profile, temperature distribution, skin friction, rate of heat transfer, and surface temperature distribution are shown. The presence of porous media and improving suction values improves the friction drag but diminishes the energy transfer. The thermal production parameter raises the energy inside the flow but diminishes the heat transfer coefficient. This work attempts to offer important insights into these intricate processes by examining the effects of controlling factors including magnetic fields, porous medium, and suction parameters. This research conclusion may find applications in coolers, heat exchangers, and environmental remediation technologies that are more effective, advancing engineering and sustainable practices.

Intelligent computing for the electro-osmotically modulated peristaltic pumping of blood-based nanofluid

The study delves into a novel application of artificial neural networks within the biomedical realm, specifically focusing on the peristaltic pumping of ionized blood-infused nanofluid using the Casson model. The investigation takes into account the impacts of electrokinetic forces, chemical reaction, thermal radiation and variable thermal conductivity. The endorsed nanofluid model encompasses both thermophoretic and Brownian diffusions. The Nernst-Planck and Poisson equations are used to characterize electroosmotic process. The mathematical model is then numerically solved using NDSolve in Mathematica. The variation in relevant hemodynamic characteristics concerning key flow parameters is explored through numerous graphical representations. Two distinct artificial neural networks have been developed to estimate values for rates of mass and heat transfer. The Levenberg-Marquardt algorithm is used as the training algorithm in network models with multi-layer perceptron architecture. Graphical inspection of the results demonstrates a decrease in blood flow with an elevated Helmholtz-Smoluchowski velocity. A lower pressure gradient is recorded with a higher electroosmotic parameter. Furthermore, an augmentation in the thermal conductivity parameter leads to a reduction in heat transfer rate at the wall. The concentration profile demonstrates an increase with a rise in the chemical reaction parameter. The results obtained from the neural network models exhibit an ideal harmony with the target values. The developed neural network models demonstrated the ability to predict rates of heat and mass transfer values with average deviations of −0.01% and 0.004%, respectively.

Multiple shape factor effects of nanofluids on marangoni mixed convection flow through porous medium

This study explores the effects of multiple shape factors on nanofluids within Marangoni mixed convection flows through porous media. Nanofluids, containing nanoparticles in a base fluid, show unique thermal properties, making them valuable in cooling systems, energy storage, and medical devices. Marangoni mixed convection, driven by surface tension gradients, adds complexity to fluid dynamics and heat transfer in porous media. Analytical and numerical analyses examine how various particle geometries, nanoparticle volume fractions, and porous medium configurations influence transport phenomena. Entropy analysis calculates thermodynamic irreversibilities. Findings reveal relationships between shape factors, heat transfer rates, velocity profiles, temperature distribution, and entropy generation rates, offering insights for optimizing nanofluid-based systems. The study also investigates magnetic forces, heat source/sink effects, and viscous dissipation on thermal energy transfer in Graphene oxide/water and Molybdenum disulfide/water nanofluids. Using similarity transformations, Partial Differential Equations are converted into Ordinary Differential Equations, solved with HAM and NDSolver by using the Wolfram tools. Results graphically depict velocity, temperature, entropy, and skin friction values, providing practical insights for engineering applications.

Silicon-based microscale-oscillating heat pipes for high power and high heat flux operation

Microscale-oscillating heat pipes (micro-OHPs) have recently drawn interest for electronic cooling applications due to their compact size and passive operating mechanism. The occurrence of dryout in OHPs, however, at which the working liquid no longer wets the evaporator, limits the maximum operating cooling power, preventing their integration for direct cooling of high heat flux semiconductor chips. Here, we report on high power and high flux operation of silicon-based OHPs by using microchannels with hydraulic diameters of ∼200 μm. Particularly, a micro-OHP with 100 μm channel height is shown to effectively operate at 210 W using a dielectric working fluid, corresponding to an unprecedented cooling power density of 145 W/cm2, without dryout. A distinctive oscillating mode with highly periodic bulk circulations occurs at high heating power and can provide efficient heat dissipation. The flow speed of the liquid under this bulk circulation mode can be as high as 10 m/s. The empirical relationships between the heat transfer rate, oscillating frequency, and device temperatures are studied.

Regression analysis of MHD conjugate natural convection of ferrofluid filled within a porous annular enclosure with inner heat generating solid cylinder using response surface methodology

Utilizing response surface methodology, this work gives a thorough numerical evaluation of ferrofluid’s conjugate magnetohydrodynamic (MHD) natural convective flow within a porous annular chamber. The system is made up of an inner solid cylinder that generates heat and is subjected to an external magnetic field, which causes Joule heating effects. To explain the conservation equations for momentum and energy, the research uses a finite element method and systematically changes important parameters. By adjusting these factors, we may study how changes affect thermal performance, flow patterns, and the Nusselt number. The findings show a complex interplay between magnetohydrodynamics, Joule heating, and the effects of porous media, offering important clues for improving thermal management and energy efficiency in state-of-the-art MHD systems. Incorporating a response surface methodology (RSM) is a significant innovation in this work. Results reveal that the increment in the thermal conductivity of the solid wall upsurges the fluid velocity and the rate of convective heat transfer. There is a significant difference in the value of the local Nusselt number as the values of the thermal conductivity of the solid wall increase. Adding nanoparticles to the dusty fluid makes the flow stronger, but also improves heat transmission significantly.

Optimizing heat transport in a permeable cavity with an isothermal solid block: Influence of nanoparticles volume fraction and wall velocity ratio

Abstract This study examines the influence of wall velocity ratio on mixed convective heat transport in a permeable cavity containing an isothermal solid block at its center. The analysis considers the characteristics of various flow variables, i.e., Darcy number, wall velocity ratio, Richardson number, and volume fraction of suspended nanoparticles, on heat transport and material flow characteristics. The principal equations are solved implementing the semi-implicit method for pressure linked equations algorithm, and the outcomes are compared with existing literature. The study shows that rising estimations of Darcy number, velocity ratio, Richardson number, and nanoparticles volume fraction lead to improved heat transfer rates. For example, at high Richardson number (100) and solid volume fraction (0.05), increasing the velocity ratio from 0.5 to 1.5 results in a 6% (5%) upsurge in heat transport rate. Conversely, at smaller Richardson number (0.01), the heat transport rate upsurges by 29% (28%). Similarly, at high Darcy numbers and low wall velocity ratios, a 3% (4%) escalate in heat transport rate is observed with an increase in nanoparticles concentration from 0 to 0.05, while a 9% (8%) increase in thermal performance is achieved at low Darcy numbers. The study emphasizes the importance of optimizing the combination of nanoparticles volume fraction, Darcy number, velocity ratio, and Richardson number to maximize thermal performance in the porous cavity.