Heat Transfer Phenomena Research Articles

Analysis of frost layer growth behavior on cryogenic surfaces in ultralow dew point environments by experimental tests and numerical simulations

Maintaining an ultralow dew point is essential for the operation of transonic cryogenic wind tunnels, as it significantly influences aerodynamic characteristics. Even in extremely dry conditions, minute quantities of frost can form on cryogenic surfaces, which compromises data quality. Conducting experiments on frost desublimation in such ultralow dew point environments poses significant challenges due to the demanding experimental conditions. Therefore, this study aimed to explore the desublimation characteristics of cryogenic surfaces in ultralow dew point environments and to address the challenges of experimental investigations under such extreme conditions. Initially, the study experimentally investigated frost formation by assessing the impact of various factors, such as temperature and water vapor content. It was observed that the type of frost formed depended on the water vapor content, and altering the surface temperature influenced the growth region of the frost crystals. The irregular growth of the frost layer on low-temperature surfaces was evident, as temperature markedly affected both the growth rate and the diffusion direction of frost formation. Moreover, the process of trace water frost formation was simulated using a dispersive multiphase model, predicting the frost layer's thickness. The numerical results suggest that the frost layer is micrometers thick, with a minimum thickness of 20 μm. A nonlinear relationship was identified between frost growth and dew point level. This research lays the groundwork for a deeper understanding of desublimation characteristics in ultralow dew point environments and for further investigation of low-temperature heat and mass transfer phenomena.

Thermodynamic analysis of micropolar-casson fluid flow with PST and PHF heating condition over a curved stretching surface

In this research, we explore the flow dynamics of micropolar Casson fluids over curved surfaces, while incorporating prescribed heat and surface fluxes, as well as heat generation effects. By applying similarity transformation to the governing model, we derive individual differential equations which are then reduced to general differential equations. This transformation yields a mathematical structure conducive to problem analysis. Through the use of numerical methods, we solve ordinary differential equations to investigate the fluid dynamics and heat transfer phenomena in this specific flow configuration. The main aim of this study is to offer a comprehensive understanding of the intricate behavior displayed by micropolar Casson fluids on curved surfaces under the influence of prescribed heat and surface fluxes, along with heat generation. By employing numerical methods, this study aims to contribute to the advancement of theoretical understanding by addressing the complex interactions between fluid dynamics and thermal properties.

Effect of topographical pattern on vortex shedding and heat transfer phenomena in power-law fluid flow around a rotating cylinder

The present numerical investigation studies the momentum and heat transfer phenomena from a heated rotating patterned cylinder in the vortex shedding regime. In particular, the effect of surface patterns ( ω , δ ), fluid behavior ( 0.4 ≤ n ≤ 1.6 ), cylinder rotation speed ( 0.5 ≤ α ≤ 2 ), and Prandtl number ( 1 ≤ Pr ≤ 100 ) at Reynolds number 100 on the force coefficients and Nusselt number are studied. Vorticity and isotherm profiles demonstrate the flow dynamics and heat transfer characteristics. According to the findings of this study, the formation of the vortex (including its size, shape, and number of vortices) and the time period during which the vortex shedding pattern repeats itself demonstrates a dependency on the shape of the cylinder, fluid behavior, and rotating speed. It has been noted that a significant decrease in the frequency of vortex shedding occurs on adding topographical patterns. Additionally, it has been noticed that on increasing rotational speed, vortex shedding can be suppressed for all fluid behaviors. Numerical simulation results reveal that the average drag coefficient ( C ¯ D ) for a rotating patterned cylinder decreases with increasing rotational speed ( α ), and it further reduces on increase in pattern frequency ( ω ) and amplitude ( δ ) compared to a smooth circular cylinder. The shear-thinning fluid behavior helps to dissipate the heat from the cylinder to the surrounding fluid. Conversely, shear-thickening fluid behavior exhibits the opposite trend.

Calculation and numerical modeling of the effect of heat and mass transfer on the properties of pile foundations in seasonally freezing soils

The phenomenon of heat and mass transfer in seasonally freezing soils has a significant impact on the condition of pile foundations. Building structures constructed in such soils experience extremely negative consequences: frost heave, vibration dynamics, moisture mass transfer and soil weakening during the thawing. Seasonally freezing soils occupy most of the territory of Kazakhstan, and in most regions the depth of soil freezing exceeds 1.5 m, there are settlements where the index reaches 1.97 m (Semiyarka, East Kazakhstan region) and in the north of the country - 2.74 m (Arshaly, Akmola region). Arrangement of foundation bases below the frost depth leads to increased construction costs, requires additional costs for thermal insulation, ventilation, other materials and structures, and, in addition, does not always lead to a full levelling of the negative impact of heat and mass transfer on the term and conditions of operation of buildings, structures, railways and roads. Therefore, the efforts of engineers and specialists in the field of thermal physics are aimed at finding effective ways to solve the problems of deformation and destruction of foundations in seasonally freezing soils. In the article an attempt is made to reveal the character of heat and mass transfer influence on pile foundations in seasonally freezing soils on the basis of a thermomechanical model.

Numerical Simulation and Sensitivity Analysis Using RSM on Natural Convective Heat Exchanger Containing Hybrid Nanofluids

This work presents a numerical analysis for exploring heat transfer phenomena in an enclosed cavity using magnetohydrodynamics natural convection. Because of the numerous real-world applications of nanofluids and hybrid nanofluids in industrial and thermal engineering developments, hybrid nanofluids are used as fluid mediums in the fluid field. A hexagonal-shaped heat exchanger is taken with two circular surfaces along the middle part. The upright circular surface acts as a homogeneous heat source, while the lower circular surface functions as a heat sink. The remaining portions of the adjacent walls are thermally insulated. The copper (Cu) and titanium dioxide (TiO2) nanoparticles are suspended into water to make a hybrid nanofluid. For solving the corresponding governing equations, the weighted-residual finite element method is applied. To explain the major outcomes, isotherms, streamlines, and many others 2D and 3D contour plots are involved graphically with a physical explanation for different magnitudes of significant parameters: Rayleigh number 103≤Ra≤106, Hartmann number 0≤Ha≤100, and nanoparticle volume fraction 0≤ϕ≤0.06. The novelty of this work is to apply response surface methodology on the natural convective hybrid nanofluid model, to visualize 2D and 3D effects, and to study the sensitivity of independent parameters on response function. Due to the outstanding thermal properties of the hybrid nanofluid, the addition of Cu and TiO2 nanoparticles into H2O develops the heat transfer rate to 35.85% rather than base fluid. Moreover, a larger magnitude of Ra and the accumulation of mixture nanoparticles result in the thermal actuation of a hybrid nanofluid. With greater magnetic impact, an opposite response is exhibited.

Correlation of pool boiling heat transfer and enhancement by microstructure surfaces at sub-atmospheric pressures

Compared with standard atmospheric pressures (std-ATM), there is a significant difference in heat transfer phenomenon of pool boiling at sub-atmospheric pressures(sub-ATM). The mechanism by which pressure affects the heat transfer capacity of pool boiling cooling remains unknown. In this work, the effect of pressures on pooling boiling heat transfer was investigated and microstructure surfaces were proposed to enhance the heat transfer capacity. The experimental results demonstrate that the decrease of pressure has a suppressing effect on the pool boiling heat transfer capacity. At sub-atmospheric pressures, microstructure surface can improve pool boiling heat transfer, and the improvement increases with the decrease of pressure. The dimensionless correlation for pool boiling considering pressure was fitted, with an average error of 13.1%. A dimensionless correlation for pool boiling considering microstructure surfaces and pressures was fitted, and an average error of 12.5% was verified.

Numerical investigations on the impact of metallic foam configurations on heat transfer in double tube heat exchanger: A parametric approach

In this research, a parametric analysis of partially filled high-porosity metallic foams within a double-tube heat exchanger integrated into a solar flat plate collector is conducted. The primary objective is to comprehensively analyze the thermal and fluid flow behavior in this complex system through numerical simulations employing ANSYS Fluent v2021, with water as the working fluid. The study encompasses three distinct metal foam materials—Nickel, Copper, and Aluminum—each investigated across six cases with varying porosities (ranging from 0.80 to 0.90) and pore densities (ranging from 10 to 30). The investigation also explores changes in the internal diameter of the foams adjacent to the conduit wall and the external diameter of the foam within the tube core, resulting in multiple test cases. Rigorous validation of simulation results against experimental data enhances the credibility of the findings. To simulate fluid flow and heat transfer phenomena within the metal foam heat exchanger’s intricate geometry, the research leverages the Reynolds-Averaged Navier-Stokes (RANS) equations coupled with the k-epsilon model, treating the metal foam as a porous medium. The outcomes reveal intriguing insights, such as the close thermal performance match between 10 PPI aluminum foam and the more costly 10 PPI copper foam. The highest performance factor is observed for 30 PPI aluminum foam, highlighting its efficiency. However, the performance factor exhibits variations, with values of 2.03, 3.15, and 3.73 for 100 PPI, 20 PPI, and 30 PPI foams, respectively, and their corresponding porosities of 0.90, 0.85, and 0.80 in case 1, case 2, and case 3, all at a lower Reynolds number of 3,000. This performance factor decreases progressively with increasing fluid flow rates. Additionally, the research evaluates key parameters, including average wall temperature, average Nusselt number, and Colburn j factor, to identify the optimal performance characteristics within the investigated configurations. This study provides valuable insights into the potential for enhancing the efficiency of heat exchangers in solar flat plate collectors through the strategic utilization of high-porosity metallic foams.

The heat transfer mechanism coupling pyrolysis and flow of hydrocarbon fuel in heated tube under supercritical pressure

The coupling mechanism between pyrolysis and fluid flow of endothermic hydrocarbon fuels plays a crucial role in the design of regenerative cooling systems for advanced aircraft. In this work, the convective heat transfer for HF-1 with pyrolysis including 18 species and 24 reactions is numerically investigated in a horizontal circle tube under supercritical pressure (5 MPa). The results show that the mechanism of small molecule products on different heat transfer phenomena varies. In the inlet heat transfer deterioration region, small molecule products exacerbate the non-uniform radial distribution of fluid density and dynamic viscosity. At the outlet position, it significantly enhances the physical heat sink of the mixture with its high thermal conductivity and specific heat capacity. Additionally, the aromatic hydrocarbons significantly contribute to non-uniformities in thermal conductivity and specific heat capacity due to the low specific heat capacity and thermal conductivity in inlet HTD region. When the radial non-uniformity coefficient of fuel conversion keeps between −0.1 and 0, the pyrolysis of the fuel enhances heat transfer, remarkably.

Nonisothermal analysis of two uniform boundary layer shear flows

AbstractThe heat transfer phenomenon on the multiphase flows plays an imperative role in several biological and industrial processes, like the oil production industries, catalytic reactors, energy losses in several thermal systems, energy storage, paper manufacture, and heat exchanger systems. Therefore, this study scrutinized the heat transfer characteristic between two uniform boundary layer shear flows with different strengths flowing in the same direction. This problem involves the simulation of the convergence of boundary layers with varying shear strengths. The nonlinear differential system is scrutinized and converted into dimensionless ordinary differential equations by employing appropriate dimensionless variables. The resulting set of highly nonlinear ordinary differential equations is resolved numerically utilizing the Matlab solver “bvp4c.” The resulting numerical solutions are used to construct graphs that illustrate and elucidate the impact of numerous physical parameters on flow patterns. For both fluids, results for the Nusselt number and shear stress are also presented graphically for various parameters. The acquired results demonstrate that the velocity profile upsurges for both upper and lower fluids by enhancing the shear parameter. Furthermore, the number of streamlines is enhanced by augmenting the values of the viscosities ratio parameter. The present problem applies to the trailing edge flow over a thin airfoil with camber.

A Digitalized Methodology for Co-Design Structural and Performance Optimization of Battery Modules

In this study, we present an innovative, fully automated, and digitalized methodology to optimize the energy efficiency and cost effectiveness of Li-ion battery modules. Advancing on from today’s optimization schemes that rely on user experience and other limitations, the mechanical and thermal designs are optimized simultaneously in this study by coupling 3D multi-physical behavior models to multi-objective heuristic optimization algorithms. Heat generation at various loading and ambient conditions are estimated with a physics-based, fractional-order battery cell-level model, which is extrapolated to a module that further accounts for the interconnected cells’ heat transfer phenomena. Several key performance indicators such as the surface temperature increase, the temperature variations on the cells, and heat uniformity within the module are recorded. For the air-cooled study case, the proposed coupled framework performs more than 250 module evaluations in a relatively short time for the whole available electro-thermal-mechanical design space, thereby ensuring global optimal results in the final design. The optimal module design proposed by this method is built in this work, and it is experimentally evaluated with a module composed of 12 series-connected Li-ion NMC/C 43Ah prismatic battery cells. The performance is validated at various conditions, which is achieved by accounting the thermal efficiency and pressure drop with regard to power consumption improvements. The validations presented in this study verify the applicability and overall efficiency of the proposed methodology, as well as paves the way toward better energy and cost-efficient battery systems.

Multiscale Modeling of Flow in Rod Bundles: From Direct Numerical Simulation and Subchannel to Coarse-Mesh CFD

Fast and accurate evaluation of flow and heat transfer phenomena in rod bundles is a problem of long-standing interest in nuclear engineering. Computational fluid dynamics (CFD) can provide accurate but relatively time-intensive estimates, such that simulations of very long transients with high spatial detail are infeasible. On the other hand, subchannel codes require relatively low computational time and can provide pin-level estimates, but have substantial empiricism in evaluating aspects such as crossflows and turbulent mixing coefficients. A multiscale method (SC+) for bridging this accuracy/speed gap, based on the Subchannel CFD (SubChCFD) method of Liu et al. [Nucl. Eng. Design, Vol. 355, paper 110318 (2019)], is demonstrated and developed here with a focus on a 5 × 5 square rod bundle geometry. The method has been newly implemented into the commercial code STAR-CCM+ and benchmarked against Liu et al.’s data. The 5 × 5 geometry was chosen in part due to the availability of direct numerical simulation (DNS) data at a relevant Reynolds number of a similar configuration for comparison. The SC+ results are variously compared against results from DNS, large eddy simulation, wall-resolved Reynolds-averaged Navier-Stokes, and coarse-mesh CFD methods. As an expansion to the original SubChCFD approach, a simple Hi2Lo approach is demonstrated using the DNS data as a correction to the original friction factor correlations employed. This is verified to improve the predictions. Additional test cases with geometric perturbations are pursued, illustrating the flexibility of SC+. The potential of this method for modeling the narrow gap vortex instability, which would represent an advancement over standard subchannel approaches, is also assessed. The method is expanded to include transverse flow losses, which was found to improve the results for modeling the gap instability. Initial extensions of SC+ for hexagonal rod bundles are also presented; some inaccuracies for the coarsest meshes prompted a detailed investigation of the mesh convergence behavior of the method. Geometric correction factors were devised that provided substantial improvement on these very coarse meshes, improving the prospects of SC+ for wider usage. Future work plans are to expand the methodology to wire-wrapped rod bundles and to implement the method into Pronghorn, with a unified pipeline via the Cardinal wrapper between the codes NekRS, Pronghorn, and BISON, to solve fuel performance problems of direct interest to industry.

Levenberg-Marquardt technique analysis of thermal and concentration storage in cone-disk apparatus with neural network-enhancement

An artificial intelligence-driven neural network with the Levenberg-Marquardt method (NN-LMM) has been developed to investigate the thermal and mass transfer characteristics of a liquid flowing through the conical gap in a cone-disk apparatus. The disk and cone can either remain static or rotate at changing angular speeds, with discussion for heat transfer influenced by cosmic emission. The Rosseland resemblance is employed to compute heat diffusion in this study. To monitor variations in mass removal on the exterior, thermophoresis effects are appropriated into consideration. By applying appropriate transformations, the partial differential equations (PDEs) governing this problem are converted into typical ones. A reference dataset for NN-LMM is generated, covering various influential model variations, simulating scenarios using the Lobatto III-A numerical method. The purpose of employing the Levenberg-Marquardt technique in the analysis of thermal and concentration storage in a cone-disk apparatus, enhanced by neural networks, lies in optimizing the modeling and prediction accuracy of complex fluid dynamics and heat transfer phenomena. This technique, coupled with neural network enhancement, aims to address challenges associated with traditional analytical methods by offering a robust and efficient approach to modeling intricate processes in fluid dynamics and heat transfer. The novelty of utilizing the Levenberg-Marquardt technique, along with neural network enhancement, lies in its ability to effectively capture and simulate the dynamic interactions between thermal and concentration storage in the cone-disk apparatus. By leveraging the power of neural networks to learn complex patterns and relationships from data, combined with the optimization capabilities of the Levenberg-Marquardt algorithm, this approach offers improved accuracy and predictive capabilities compared to conventional methods. It is analyzed that the mass transport field for Nt decreases as temperature ratios increase. This phenomenon occurs because the thermophoretic force becomes more pronounced at higher temperatures, causing more particles to move towards the apparatus. Further it is seen that stationary cone and a rotating disk exhibit enhanced heat transport with increasing radiation parameter values. This suggests that elevating the radiation parameter leads to more efficient heat transfer in this specific model. Highest flow intensity observed around the cone. This reference data is subjected to testing, validation, and training processes to fine-tune the approximate solution to meet the desired results. The accuracy, stability, capacity, and robustness of NN-LMM are verified through mean squared error (MSE)-based fitness curves, regression plots, error histograms and absolute error assessments. A comparative analysis demonstrates the accuracy of the proposed solver, with absolute errors in the range of 10-9 to 10-6 for all influential parameters results.

Comparative study of copper nanoparticles over radially stretching sheet with water and silicone oil

Abstract Copper nanoparticles are widely used in many sectors and research endeavors owing to their unique properties, including a large surface area, catalytic capabilities, and high thermal and electrical conductivity. The selection of the base fluid for copper nanoparticles should be contingent upon the anticipated application requirements since various fluids exhibit distinct characteristics that could potentially impact the mobility of the nanoparticles. The present investigation analyzes heat transfer phenomena occurring across a radially stretched surface. The research explores the effects of different states of Cu nanoparticles when combined with base fluids, such as water and silicone oil, on the heat transfer process. The momentum and energy equations are transformed into nonlinear ordinary differential equations by applying the similarity transformation. The boundary value problem-fourth-order (BVP4C) method numerically solves the governing ordinary differential equation for the modeled problem. In addition, the influence of various factors such as the slip parameter, solid volume fraction, Eckert number, Prandtl number, and unsteadiness parameter are examined. It has been discovered that blade-shaped nanoparticles transfer heat as quickly as possible via silicone oil and water. However, for platelet-shaped nanoparticles, a minimum heat transfer rate has been noted. The maximum skin friction coefficient is observed in platelet-shaped nanoparticles, while blade-shaped nanoparticles have the lowest skin friction coefficient.

An extended model to assess Jeffery–Hamel blood flow through arteries with iron-oxide (Fe2O3) nanoparticles and melting effects: Entropy optimization analysis

Abstract Nanofluids are utilized in cancer therapy to boost therapeutic effectiveness and prevent adverse reactions. These nanoparticles are delivered to the cancerous tissues under the influence of radiation through the blood vessels. In the current study, the propagation of nanoparticles within the blood in a divergent/convergent vertical channel with flexible boundaries is elaborated computationally. The base fluid (Carreau fluid model) is speculated to be blood, whereas nanofluid is believed to be an iron oxide–blood mixture. Because of its shear thinning or shear thickening features, the Carreau fluid model more precisely depicts the rheological characteristics of blood. The arterial section is considered a convergent or divergent channel based on its topological configuration (non-uniform cross section). An iron oxide ( F e 2 O 3 {\rm{F}}{{\rm{e}}}_{2}{{\rm{O}}}_{3} ) nanoparticle is injected into the blood (base fluid). To eliminate the viscous effect in the region of the artery wall, a slip boundary condition is applied. An analysis of the transport phenomena is preferred using the melting heat transfer phenomena, which can work in melting plaques or fats at the vessel walls. The effects of thermal radiation, which is advantageous in cancer therapy, biomedical imaging, hyperthermia, and tumor therapy, are incorporated in heat transport mechanisms. The governing equation for the flow model with realistic boundary conditions is numerically tickled using the RK45 mechanism. The findings reveal that the flow dynamism and thermal behavior are significantly influenced by melting effects. Higher Re \mathrm{Re} can produce spots in which the track of the wall shear stress fluctuates. The melting effects can produce agitation and increase the flow through viscous head losses, causing melting of the blockage. The maximum heat transfer of 5 % 5 \% is achieved with We {\rm{We}} when the volume friction is kept at 1 % 1 \% . With higher estimation of inertial forces Re \mathrm{Re}\hspace{1em} and same volume friction, the skin drag coefficient augmented to 34 % 34 \% . The overall temperature is greater for the divergent flow scenario.

Prediction of two-phase flow patterns based on machine learning

Due to the advantages of flexibility, security and economy, small modular reactor (SMR) has become a research hotspot in the field of nuclear energy. Gas liquid two-phase flow is one of the most common phenomena for the research and development of SMR. An effective two-phase flow pattern prediction model with high accuracy is very crucial since it will impact the thermal–hydraulic and heat transfer phenomena, and consequently, the safety of SMR. In this paper, support vector machine (SVM), Random Forest (RF) and K-Nearest Neighbor (KNN) algorithm were chosen as the candidates of machine learning (ML) models. we selected 12 databases to train and test ML models. Through the identification of flow pattern feature correlation and the preprocess of dataset, we proposed an ML model for gas–liquid flow pattern prediction based on the improved K-Nearest Neighbor (KNN). its accuracy can reach more than 99%, higher than the traditional methods.

Simulation and experimental study of heat-moisture-solute transfer during drying process of porous media

Fruits and vegetables, being typical porous media, allow for the migration of nutrients (solutes) and the transport of moisture simultaneously during the drying process. To reveal the migration mechanism of heat-moisture-solute during the drying process of porous media, a comprehensive mathematical model was established that accounts for the coupled phenomena of heat and moisture transfer, along with solute migration. The model was simulated using COMSOL to provide insights into these complex interactions. Hot-air drying experiments were conducted using apple slices as the subject to validate the accuracy and reliability of the model. The simulation results and experimental results of temperature, moisture content, and sugar concentration were in good agreement. The findings demonstrate that as the drying process progresses, the interface between temperature, moisture gradients, and sugar concentration shifts from the outer layers toward the inner regions. We investigated the effects of hot air temperature, thickness, and porosity on the heat-moisture-solute transfer in porous media. The results provide support for accurately predicting the migration and transport mechanisms of solutes in porous media.

Unlocking the Thermal Efficiency of Irregular Open-Cell Metal Foams: A Computational Exploration of Flow Dynamics and Heat Transfer Phenomena

An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance.

Special function form solutions of multi-parameter generalized Mittag-Leffler kernel based bio-heat fractional order model subject to thermal memory shocks.

The primary objective of this research is to develop a mathematical model, analyze the dynamic occurrence of thermal shock and exploration of how thermal memory with moving line impact of heat transfer within biological tissues. An extended version of the Pennes equation as its foundational framework, a new fractional modelling approach called the Prabhakar fractional operator to investigate and a novel time-fractional interpretation of Fourier's law that incorporates its historical behaviour. This fractional operator has multi parameter generalized Mittag-Leffler kernel. The fractional formulation of heat flow, achieved through a generalized fractional operator with a non-singular type kernel, enables the representation of the finite propagation speed of heat waves. Furthermore, the dynamics of thermal source continually generates a linear thermal shock at predefined locations within the tissue. Introduced the appropriate set of variables to transform the governing equations into dimensionless form. Laplace transform (LT) is operated on the fractional system of equations and results are presented in series form and also expressed the solution in the form of special functions. The article derives analytical solutions for the heat transfer phenomena of both the generalized model, in the Laplace domain, and the ordinary model in the real domain, employing Laplace inverse transformation. The pertinent parameter's influence, such as α, β, γ, a0, b0, to gain insights into the impact of the thermal memory parameter on heat transfer, is brought under consideration to reveal the interesting results with graphical representations of the findings.

A novel approach for designing efficient and sustainable cooling cycles with low global warming potential refrigerants

With the current legislation on the phase-out of 3rd generation refrigerants, new cooling cycles are expected to operate with 4th generation refrigerants, hence, the need for optimal system performance with these new working fluids. In this study, an innovative optimization approach was applied for the design of cooling cycles with 4th generation refrigerants based on integrating statistical analysis design of experiments (DoE) with molecular modeling using the polar soft-SAFT model. First, a detailed multi-criteria assessment was applied for the selection of 4th generation refrigerants in medium–low temperature applications. Results demonstrated the potentiality of trans-1,3,3,3-tetrafluoroprop-1-ene (R1234ze(E)) or cis-1,2,3,3,3-pentafluoroprop-1-ene (R1225ye(Z)) in terms of environmental, safety, and technical criteria in basic cooling cycles under specific operating conditions. Multi-objective optimization guided using statistical analysis tools were implemented to study potential enhancement in cooling cycle performance using these promising refrigerants in terms of energy and exergy efficiency. This included evaporator and condenser temperature, fluid choice, compression yield, superheating/subcooling degrees, and cycle type. The evaporation and condenser temperature, and the compressor efficiency are shown to monopolize more than three-quarters of the cumulative contribution on system efficiency for those operated with R1234ze(E) in advanced liquid-to-suction line heat exchangers (LL/SL-IHX). Further optimization through examining the effect of heat transfer phenomena assisted in determining optimal operating conditions for new systems operating with low GWP refrigerants, instilling annual cost savings of $1.59 K and reduction in CO2 emissions by 1.02 tCO2-eq compared to the baseline system.

Development of a continuous reheating furnace state-space model based on the finite volume method

This study developed a modeling approach of a continuous steel slab reheating furnace process as a particular case of spatially distributed parameter systems involving radiative heat transfer. The aim of the resulting mathematical model, which is both detailed and computationally tractable, is to serve in prospective advanced process control (APC) and model-based optimization. The two-dimensional state-space model is introduced to accurately simulate the temperature distribution and dynamics, using the finite volume method (FVM) to incorporate essential heat transfer phenomena, including radiation, conduction, convection, advection, and simple combustion. The study presents a novel furnace measurement model that interprets temperature sensor readings (useful for state estimation), a benefit of the FVM treatment of radiative heat transfer. Strategies for linearization and model order reduction, such as balanced truncation, are proposed to facilitate real-time control. The simulation case study demonstrates the targeted capabilities of the model. The accuracy of the model is verified through comparisons with more complex computational fluid dynamics (CFD) software models. The study prioritizes theoretical modeling over empirical validation of a specific furnace unit, omitting experimental validation at this stage.