Heat Transfer Rate Research Articles

Numerical Study on Conjugate Heat and Mass Transfer Characteristics Around Thermosolutal Exchangers: Effect of Flow Parameters and Solid Block Arrangement

Abstract The effect of airflow characteristics within a slot-ventilated enclosure is carried out numerically to optimize the heat and contaminants’ removal rate where cold air is injected via an inlet port. The contaminated air is expelled by the chimney outlet port positioned along the left side of the top wall. Based on the structure dynamics, the flow governing equation is dealt with the Navier–Stokes equations coupled with the energy equation, where the maximum cooling efficiency is evaluated. A finite volume-based semi-implicit method for pressure-linked equations (SIMPLEs) method is utilized to deal with the nonlinear coupled partial differential equations to evaluate the flow variation with changing various physical parameters. Different thermosolutal block orientations are considered to investigate the effective interpretation of heat and mass transfer in a natural chamber. The effects of the inclination angle of the chimney, Richardson and Reynolds numbers on the average heat and mass transfer rate, average temperature, average Bejan number, and performance evaluation criterion (PEC) inside the system are evaluated. Boundary layer analysis is performed to examine the transient behavior of the boundary layer flow dominated by natural convection near the wall heater on the enclosure’s left wall and results are found to agree with our numerical results.

A Novel Capacitive Model of Radiators for Building Dynamic Simulations

This study addresses the critical challenge of performing a detailed calculation of energy savings in buildings by implementing suitable actions aiming at reducing greenhouse gas emissions. Given the high energy consumption of buildings’ space heating systems, optimizing their performance is crucial for reducing their overall primary energy demand. Unfortunately, the calculations of such savings are often based on extremely simplified methods, neglecting the dynamics of the emitters installed inside the buildings. These approximations may lead to relevant errors in the estimation of the possible energy savings. In this framework, the present study presents a novel 0-dimensional capacitive model of a radiator, the most common emitter used in residential buildings. The final scope of this paper is to integrate such a novel model within the TRNSYS 18simulation environment, performing a 1-year simulation of the overall building-space heating system. The radiator model is developed in MATLAB 2024b and it carefully considers the impact of surface area, inlet temperature, and flow rate on the radiator performance. Moreover, the dynamic heat transfer rate of the capacitive radiator is compared with the one returned by the built-in non-capacitive model available in TRNSYS, showing that neglecting the capacitive effect of radiators leads to an incorrect estimation of the heating consumption. During the winter season, with a heating system turned on from 8 a.m. to 4 p.m. and from 6 p.m. to 8 p.m., the thermal energy is underestimated by roughly 20% with the commonly used non-capacitive model.

Solar Thermal Collector Roughened with S-Shaped Ribs: Parametric Optimization Using AHP-MABAC Technique

The current examination used a multi-criteria decision-making (MCDM) approach to optimize the roughness parameters of S-shaped ribs (SSRs) in a solar thermal collector (STC) duct using air as the working fluid. Different SSRs were tested to identify the combination of parameters resulting in the best performance. Geometrical parameters such as relative roughness pitch (PR/eRH) varied from 4 to 12, relative roughness height (eRH/Dhd) from 0.022 to 0.054, arc angle (αArc) from 30° to 75°, and relative roughness width (WDuct/wRS) from 1 to 4. The Nusselt number (NuRP) and friction factor (fRP), findings which impact the STC performance, rely on SSRs. The performance measurements show that no combination of SSR parameters lead to the best enhancement heat transfer rate at low enhancement in the friction. So, a hybrid multi-criteria decision-making strategy using the Analytical Hierarchy Process (AHP) for criterion significance and Multi Attributive Border Approximation Area Comparison (MABAC) for alternative ranking was used to determine which combination of geometrical parameters will result in the optimum performance of a roughened STC. This work employs a hybrid MCDM technique to optimise the effectiveness of an STC roughened with SSRs. To optimize the SSR design parameters, this study used the hybrid AHP-MABAC technique for analytical assessment of a roughened STC. The optimization results showed that the STC roughened with SSRs achieved the optimum performance at PR/eRH = 8, eRH/Dhd = 0.043, αArc = 60° and WDuct/wRS = 3.

Ultrafast Thermal Conduction of Phase Change Fiber Enabled by Sheath Confinement-Induced Ordered Orientation of Hydroxylated BNNs.

Phase change fibers (PCFs) are increasingly popular in thermal storage and release applications, such as temperature management. However, a simple but effective integration of thermal conductive materials into PCFs to deliver ultrafast thermal conduction remains a big challenge. Herein, a facile one-pot coaxial wet spinning strategy based on sheath-confinement-induced orientation arrangement of hydroxylated boron nitride nanosheets (BNNs-OH) is proposed to fabricate the high-performance PCFs. For the core-sheath PCFs, the cellulose nanofiber (CNF)-reinforced paraffin (CNF/PW) emulsions serve as the phase change core, while the dissolved cellulose and well-dispersed BNNs-OH act as the sheath precursor. By increasing the extrusion speed of the liquid core, the contraction of the fiber sheath is gradually finalized to induce the alignment of BNNs-OH based on the confinement effect. Consequently, the highly oriented BNNs-OH nanosheets in fiber sheath (f=0.8) endow PCFs with high phase transition enthalpy (125.1 Jg-1), excellent thermal conductivity (10.15 W m-1K-1), rapid heat transfer rate (1.6 cms-1); moreover, the as-prepared PCFs show good tensile strength (11.21 MPa) and leakage-proof (0.13%). The as-prepared PCFs are combined with thermochromic dyes for functional fabrics or applied as thermal management for a phone, demonstrating excellent thermal conduction and heat dissipation.

Neuro-computing simulation for heat transfer rate on radiative hybrid nanofluid (MoS2 + SiO2–EG) through a shrinking surface using Gharesim viscosity model

Neuro-computing simulation for heat transfer rate on radiative hybrid nanofluid (MoS2 + SiO2–EG) through a shrinking surface using Gharesim viscosity model

The Effect of Freezing and Thawing on Mozzarella Cheese: Insights from Industrial-Scale Experiments and Mathematical and Digital Analysis

Abstract Freezing can assist the distribution of low-moisture Mozzarella cheese, but the impact of freezing under industrial conditions in a pallet is not well understood. Heat transfer during the freezing and thawing of 96 blocks of 10 kg cheese was slower than observed for smaller masses of cheese (0.70–0.87 °C day−1 for freezing and 0.80–6.00 °C day−1 for thawing). The rate of heat transfer also differed between inner and outer blocks, particularly during thawing. Block temperature was predicted with a maximum root mean square error of 3.60 °C, using heat and mass transfer simulations. While several changes in physicochemical properties were observed, the impact on cheese functionality appeared small. Large reversible salt migration was observed by simulation, causing local concentrations of up to 33% salt in free moisture in outer blocks at the end of freezing. Intact casein was 3–4% lower after thawing compared to in refrigerated control cheese but the microstructural, textural, and functional properties were similar, except for the appearance of a greater number of calcium crystal complexes in inner blocks. The microstructural, textural, and functional properties of inner and outer blocks were also similar, despite differing rates of heat transfer. Linear regression could predict the concentration of soluble nitrogen in thawed samples using data for refrigerated samples. Machine learning methods were also applied to predict non-linear behavior while minimizing the need for experimental data. A linear multi-fidelity Gaussian process model best predicted soluble nitrogen by combining historical data from refrigerated samples with limited experimental data from thawed samples. This study increases our understanding of freezing and thawing of cheese in an industrial setting and offers tools for optimizing these processes to minimize proteolysis in order to reduce the impact on product quality.

A novel study on thermal enhancement in the flow of magnetized ternary hybrid nanofluid toward an elastic surface with nonlinear heat generation

AbstractTernary hybrid nanofluids are excellent at efficiently transferring heat for solar systems, electronics, and industrial operations because they combine three nanoparticles in a base fluid. Their diverse range of uses includes biomedical therapies, oil recovery, catalysis, and thermal energy storage. Recently, ternary hybrid nanofluids have replaced more traditional hybrid nanofluid flows in an effort to improve heat transmission. In the present study, the thermal performance of magnetized ternary hybrid nanofluid flow toward an elastic porous surface has been investigated in the presence of thermal radiation and nonlinear heat generation. The effects of an induced magnetic field have also been taken into account. The ternary hybrid nanofluid is made up of the suspension of three different nanoparticles that is, copper , silicon dioxide , and iron oxide in base fluid Kerosene oil. The leading PDEs of the proposed model have been altered to ODEs by introducing suitable similarity variables. The obtained system of ODEs along with the boundary conditions has been numerically solved by using a bvp4c solver. The motion of ternary hybrid nanofluid declines in the presence of the magnetic field. The induced magnetic parameter and reciprocal magnetic Prandtl number weaken the induced magnetic profile. The existence of thermal radiation and nonlinear heat generation is significant in enhancing the thermal performance of ternary hybrid nanofluid. The volume fraction of solid nanoparticles boots up the heat transfer rate. A novel thermal enhancement is observed in the flow of ternary hybrid nanofluid as compared to hybrid nanofluid. The use of ternary hybrid nanofluid is quite advantageous in achieving desired heat transmission rates rather than hybrid nanofluid.

Experimental Study of Condensation Characteristics on a Vertical Plate Covered with Metal Foam

Metal foam (MF)-coated plate possesses the advantage of big surface area, thus it has great potential for improving the plate condensers' condensation Heat Transfer (HT). In the current research, the pores density influences of Copper Foam (CF) upon a Flat Plate (FP) with (CF) attached have been studied experimentally. And, the CF pore density conceals the utilized plate structure, which ranges from 10 PPI to 20 PPI, and the porosity of 90%. The feature of flow water steam in CF coated plate is presented by using coefficient method of unit mass efficacy. Also, the pore's density influences of CF size, rate of the mass flow of inlet steam water, and rate of the mass flow of cold water upon the HT and Pressure Drop (PD) have been tested and analyzed. The correlations of HT and for a vertical Flat Plate (FP) with fixed CF are determined the curve-fitting of the investigational values. Additionally, the result elucidated that the CF introduction improves the HT despite causing a bigger . A (10 PPI) sized CF reveals a higher performance. It is also observed that the higher pressure of inlet steam, the higher rate of the mass flow of steam and the lower temperature of cold water will result in the increase of the average Heat Transfer Rate (HTR).

Modeling Coupled Heat and Mass Transfer in Laminar Forced Convection in a Vertical Channel: Influence of the Fluid's Relative Humidity

The heat and mass exchanges between fluids and walls that accompany two-phase flows in channels are of immeasurable interest in many fields such as energy, food processing, fire engineering, biomedical etc. The aim of the present study is to explore numerically the effect of the relative humidity of an upward laminar forced convection airflow in a channel on heat and mass transfer. The walls of the channel are damp and interact with the outside environment. Based on simplifying assumptions, the flow, whose thermo-physical properties depend on temperature and relative humidity, was modeled by the Navier Stokes equations and the flow conservation equation. The finite volume method was used to discretize the equations, and the resulting systems of algebraic equations were solved using the Thomas and Gauss algorithms. A numerical calculation code written in FORTRAN and validated by comparing our numerical results with those in the literature was used to run the simulations. These numerical simulations, carried out with a relative humidity range of 60 to 90%, a Reynolds number of 500 and a fluid temperature of 323.15K for an ambient temperature of 298.15K, enabled a detailed study of the heat and mass exchanges taking place between fluid and wall. A sensitivity study of the numerical results to the mesh was carried out to demonstrate the stability of the mesh. The numerical results obtained, presented in the form of axial and radial profiles of temperature, mass concentration, Nusselt and Sherwood numbers, reveal the important role of relative fluid humidity in heat and mass transfer in a vertical channel. The heat and mass transfer rates obtained at the leading edge of the channel and at the outlet are different. Keywords: Heat and mass transfer, relative humidity, Nusselt and Sherwood numbers, vertical channel.

Peristaltic flow of electromagnetic tri-hybrid Carreau nanofluid using backpropagated Levenberg–Marquardt technique: an entropy generation analysis in blood cells

ABSTRACT The present research concentrates on examining entropy generation during the flow phenomenon of a three-dimensional peristaltic motion of a magnetized tri-hybrid nanofluid within a curved rectangular duct using a machine learning technique called backpropagated Levenberg–Marquardt (BLMT). The Carreau constitutive model is used for base liquid (blood). To obtain the most accurate solutions for the governing equations, an analytical tool called the Homotopy Perturbation Method (HPM) is utilized along with a machine learning methodology ANN-BLMT method on MatLab. The data of HPM and machine learning are also compared to assess how the framework of partial differential equations (PDEs) occurring in the problem can be improved. It shows the highest correlations between output and prediction of ANN-BLMT method. The convergence analysis reveals that for two scenarios, velocity exhibits the best validation performance values around 7.3117 × 10 − 11 and 1.0082 × 10 − 10 . A detailed comparison between blood and nanofluid has been presented graphically to enhance the benefits of ternary hybrid nanoparticles in a simple base fluid. It is also found that the velocity of the blood can be slowed by the curvature increase and because of the increment of tri-hybrid nanoparticles in pure blood. It is also noted that the rate of heat transfer for ternary hybrid nanofluids is greater than that of a simple blood. Research findings have obvious implications for comprehending and enhancing peristaltic dynamics in biological processes such as the intestinal tract.

Influence of air velocity on enhancing heat transfer rate in phase change materials for efficient device temperature control

Influence of air velocity on enhancing heat transfer rate in phase change materials for efficient device temperature control

The total heat transfer rate in the evaporating thin film: A new analytical solution

The total heat transfer rate in the evaporating thin film: A new analytical solution

Walters B’ hybrid nanofluid flow with Marangoni convection

Walters B’ hybrid nanofluid flow with Marangoni convection

The performance evolution of Xue and Yamada-Ota models for local thermal non equilibrium effects on 3D radiative casson trihybrid nanofluid

The proposed study investigates the characteristics of Stefan blowing and activation energy on MHD Casson Diamond-based trihybrid nanofluid over a sheet with LTNECs (local thermal non-equilibrium conditions) and permeable medium. The significance of Marangoni convection as well as heat generation are considered. In order to examine the properties of heat transmission in the absence of local thermal equilibrium conditions, this paper makes use of a simple mathematical model. Local thermal non-equilibrium situations typically result in two discrete and crucial temperature gradients in both the liquid and solid phases. In systems where material qualities and heat transfer efficiency are crucial, the utilization of Xue model and Yamada-Ota model and to assess the thermal conductivity of the nanofluid adds a comparison dimension and enables optimized design. The controlling partial differential equations are reduced to non-linear ordinary differential equations using an appropriate similarity transformation. The Bvp4c technique is used to resolve the resulting equations numerically. Applications in modern thermal management systems, especially those requiring precise heat transfer control (e.g., electronic cooling, medicinal devices, energy systems), will benefit greatly from this work. The model is especially applicable to processes where chemical reactions and internal heat sources are important, like in catalytic reactors and combustion systems, because it takes into account activation energy and heat generating effects. The findings indicate that when the value of the interphase heat transmission factor increases, the solid phase’s temperature profile and liquid phase heat transfer rate drop.

Evaporation characteristics of heat pipes with sub-critical nanopores

This study explores heat transfer mechanisms in heat pipes with sub-critical nanopores using coarse-grained molecular dynamics (CGMD) simulations, aiming to enhance thermal management in nanoscale applications. With the increasing need for efficient cooling solutions in microelectronics and high-performance computing, nanoporous heat pipes have gained attention due to their high thermal conductivity and passive operation. This research evaluates the effects of pore size, temperature gradients, and water fill ratios on the heat transfer efficiency of heat pipes with 2 and 3 nm diameter nanopores. The results indicate that larger temperature gradients significantly enhance heat transfer rates, while filled heat pipes perform better than medium-filled ones, primarily due to more effective phase change and fluid flow dynamics. Notably, the 2 nm filled models show improved performance over the 3 nm models, suggesting an optimal balance between capillary action and fluid resistance at smaller pore sizes. The study also reveals that in sub-critical nanopores, surface-driven flows are more effective than traditional wicking, underscoring the role of surface interactions in optimizing heat transfer. These findings provide critical insights for designing and optimizing nanoporous heat pipes, offering practical guidance for developing more efficient thermal management systems in electronics cooling and other applications.

Central composite design in predicting heat transfer rate on the time-dependent flow of Williamson nanofluid with chemical reaction: A response surface methodology

Central composite design in predicting heat transfer rate on the time-dependent flow of Williamson nanofluid with chemical reaction: A response surface methodology

A statistically predictive heat transfer rate model in a radiative magnetized hybrid nanofluid flow with dissipation over a sheet elongating exponentially: Combined RSM & ANOVA

A statistically predictive heat transfer rate model in a radiative magnetized hybrid nanofluid flow with dissipation over a sheet elongating exponentially: Combined RSM & ANOVA

Optimizing magnetic-natural convection using anisotropic porous media: A local thermal non-equilibrium approach

Purpose: Applying external magnetic fields and employing porous media are both common approaches to control the heat transfer characteristics of magnetic fluids. To optimize such control strategies, the present study proposes the use of anisotropic media with structured design in the heat transfer domain and assesses its impact. In particular, the natural convection of a magnetic fluid through an anisotropic porous medium under a non-uniform magnetic field is investigated. Design/methodology/approach: In order to model the phenomena at play, the governing partial differential equations including mass, momentum, and conservation laws for the anisotropic porous medium taking into account the use of local thermal non-equilibrium approach are developed and solved employing the finite volume technique. Findings: Different combinations of parameters related to fluid motion and energy transfer performance, like the thermal conductivity ratio, interface heat transfer coefficient, permeability ratio and orientation angle for the permeability tensor within the anisotropic porous cavity, are evaluated. The results indicate that the most important factors to manage heat transfer and flow structures are changes of thermal conductivity ratio and interface heat transfer coefficient. The influence of permeability tensor is found to be essential for flow structures, but its influence on heat transfer rates remains weak.

Deep learning investigation of water-based tetra hybrid nanofluid across a shrinking cylinder for variable electrical conductivity with thermal radiation

Deep learning investigation of water-based tetra hybrid nanofluid across a shrinking cylinder for variable electrical conductivity with thermal radiation

Featuring Hall effect on gravity-driven hybrid nanofluid flow induced by rotating cylinder

The progressive nature of hybrid nanomaterials makes them highly valuable in both engineering and industry. Hybrid nanofluids offer a great deal of potential for use in heat transport applications such as vehicle cooling and solar energy systems. This study considers the Hamilton-Crosser’s model to examine the electrical and thermal conductivities of copper and aluminum oxide nanoparticles drenched in water, which acts as a base fluid. The study examines mixed convection with linear radiation and Hall effect. The similarity transformations convert the governing equations into dimensionless ordinary differential equations. These equations are then solved numerically in MATLAB’s built-in technique namely, bvp4c by variation of physical parameters. The novelty of the study includes investigation of the thermal behavior of hybrid nanofluids by integrating nanoparticles into base fluid to attain enhanced heat transfer rate, along with the analysis of mixed convection and Hall effect over a rotating cylinder. Graphical illustrations show the behavior of various parameters over fluid flow, temperature profile, drag fraction, and heat transfer rate.