Heat Transfer最新文献

Forced convection and entropy generation through a complex geometry like Cassini oval annuli play a significant role in many applied thermal engineering systems. The novel feature of the present work is a multi-objective and multi-response optimal design of the hydrothermal and entropy performance in a porous Cassini oval annular pipe. This approach integrates the response surface methodology (RSM) CFD simulation for evaluating different key design parameters. The variables studied are the inner twisted pipe pitches (0 ≤ P ≤ 1.5), aspect ratios (0.08 ≤ AR ≤ 0.2), porosity (0.1 ≤ ɛ ≤ 0.9), and pore density (5 ≤ PPI ≤ 35) with different Reynolds numbers (50 ≤ Re ≤ 250). These parameters impact heat transfer rate, fluid mixing, and pressure drop. Optimization results indicate that low inner twisted pipe pitch (p = 0.5), low aspect ratio (AR = 0.08), low pore per inch (PPI = 5), and high porosity (ɛ = 0.9) are favorable for enhancing hydrothermal performance (NuE = 12.23 and PEC = 3.069) with moderate entropy generation (EG = 0.940). Consequently, this study introduces a useful procedure for optimizing the hydrothermal and thermodynamic performance of forced convection in porous Cassini oval annular pipe cooling systems.

Thermally induced fluid motion (thermal convection) is an important phenomenon observed in nature, playing an essential role in the dynamics of the Earth's atmosphere, lakes, oceans, and in the interior of stellar objects. The present study investigates the combined effect of uniform vertical rotation and an electric field on thermal convection in a horizontal layer of viscoelastic dielectric fluid, utilizing the Navier–Stokes–Voigt model for both free and rigid boundary conditions. A linear stability analysis has been conducted to investigate the behavior of a dielectric viscoelastic fluid layer, which is assumed to be heated from either below or above. Thermal Rayleigh number expressions for both stationary and oscillatory convection modes are obtained using exact solutions when both the surfaces are free and series solutions when both the surfaces are rigid. Furthermore, numerical analysis is conducted using the Mathematica software, and the findings are presented through graphical representations. The study reveals that the impact of vertical electric field is to destabilize the system, while rotation exerts a stabilizing influence on both stationary and oscillatory modes of convection. Furthermore, the Kelvin–Voigt viscoelastic parameter is found to delay the initiation of oscillatory instability. It is also observed that when the system is heated from above, there is a marked delay in the onset of instability compared to the case when it is heated from below. The present study of electrothermoconvection in the context of the Navier-Stokes–Voigt model, in particular, has not been reported yet in the literature.

Flat plate collectors (FPCs) are common in solar-based thermal systems, including heat exchangers, heat pipes, water heaters, and dryers, due to their simple construction, improved heat transfer, and reliable operation. However, it has lower thermal efficiency due to uneven thermal distribution and reduced heat dissipation. This study aims to enhance the thermal performance of FPC by integrating a 50:50 nanofluid of magnesium oxide (MgO) and titanium dioxide (TiO₂) and a film-cooling technique at 0.5, 1, and 1.5 velocity ratios. Using Fourier transform infrared spectrometer analysis, the stability of the hybrid (MgO/TiO₂) nanofluid is assessed and found to be better, leading to improved thermal performance of the FPC. The FPC operated with a hybrid nanofluid, achieving a higher fluid temperature of 94.9°C. The film-cooling technique reduced the surface overheat to 50.8°C. A higher velocity ratio led to a more uniform temperature distribution, a higher heat transfer coefficient of 473.9 W/m2K, and an optimum thermal efficiency of 66.1%. These performance metrics are notably better than those of the FPC operated without film cooling.

Thermal resistance (R-value) is a key metric for evaluating the energy performance of building envelopes, particularly in emerging technologies like 3D-concrete pinting (3DCP) buildings. However, conventional methods such as heat flux meters (HFM) face challenges in 3DCP applications due to surface roughness, contact-based limitations, and high costs. This study introduces a novel low-cost, noncontact system integrating an MLX90614 infrared sensor and LM35 temperature sensor with an Arduino-based platform, using the Thermometric Method (THM) to estimate R-values from wall surface, indoor, and outdoor temperatures. A novel feature of the system is a dual-servo mechanism that enables spatial temperature mapping over a 5 × 5 cm grid, improving accuracy by replacing traditional single point measurements with area-based readings. Validation against the UVAL Wireless System (greenTEG) showed a maximum error of 13% under steady-state early morning conditions, increasing to 173% in the afternoon due to thermal instability. The proposed method offers a practical, affordable, and non-destructive solution for thermal diagnostics in 3DCP buildings, supporting the development of standardized evaluation protocols for sustainable construction.

This study examines heat transport in porous media containing an enclosed trapezoidal cavity under a horizontal channel when affected by an inclined magnetic field. The system fluid motion together with thermal behavior responds to the mutual effects of buoyancy forces and magnetic fields and viscosity conditions. The non-dimensionalized governing equations require solution through the FEM Galerkin-weighted residual method. This study performs a complete parametric assessment of four key factors which include magnetic parameter alongside Reynolds' number, Rayleigh number, Darcy number, and magnetic field inclination angle. It was found that heat transfer behaved an increasing function of Rayleigh number, decreasing function of Magnetic parameter and Inverse Darcy numbers. Heat transfer behavior forecasting consumes less computational time through the application of artificial neural network (ANN) models. The training process of these models utilizes simulation results obtained from FEM simulations. The performance of heat transport property capturing by neural networks is examined through a comparison of FEM and two ANN approaches which use either parameters as input points (ANN) or Gauss-Lobatto transformation (ANN-GLT). It is worth mentioning that Gauss-Lobatto scaling yields better prediction results across a wide range of domain data. Therefore, the ANN-GLT model provides more accurate predictions than a standard ANN. The prediction time of FEM simulations which takes several hours exceeds the significantly shorter processing time of ANN models. The results prove ANN models can serve as reliable alternatives to heat transfer analysis to generate fast and precise engineering-focused predictions including thermal management system and energy storage and geophysical processes applications.

This study involves the computational analysis of two-dimensional heat transfer through convective and laminar fluid flow in a circular pipe. The study considers simultaneously developing velocity and temperature profiles and takes into account boundary conditions such as a uniform temperature and constant heat flux. The physical characteristics of this flow are assumed to be constant, incompressible, and of Newtonian type. The governing equations that describe fluid flow, including continuity, momentum, and energy, have been presented in detail. Additionally, simplifying assumptions and associated boundary conditions have been included. These equations which govern the studied phenomenon are nonlinear partial differential equations (PDE). Therefore, we used the finite-difference scheme to integrate these equations by iterations after transforming them into a linear algebraic system. For this purpose, FORTRAN computer code has been well developed to simulate the thermal problem in a circular pipe and obtain the results presented in both cases. This allowed us to evaluate the rate of heat transfer, observe the velocity and temperature contours, and the distribution of Nusselt number, whether local or average. It also helped us determine various factors that affect thermal behavior. The findings indicate that the number of grid points N significantly influences the accuracy of the solution, thus affecting the accuracy of the temperature and velocity profiles. Moreover, the Prandtl number directly impacts the relationship between temperature and radial position. Finally, we conducted a comparative analysis for validation, and our results showed excellent agreement with previous studies. This further strengthens the reliability of the predictive model through simulation.

This study explores a multigeneration system leveraging renewable geothermal energy, featuring components such as a hydrogen liquefaction subsystem, a proton exchange membrane electrolyzer, a cascade organic Rankine cycle, and a geothermal unit. It rigorously evaluates the system's thermodynamic and economic performance, focusing on how key variables affect efficiency. The research introduces a novel heat integration procedure to minimize irreversibility in producing coolant and liquefied hydrogen. The analysis compares various hydrogen generation methods based on production rates, economic viability, and energy efficiency, identifying optimal operating conditions through a two-objective genetic optimization algorithm. The system achieves an energy efficiency of 20% and an exergy efficiency of 54%, with an output power of 7103 kW and hydrogen production of 4.375 kg/h. Financial assessments reveal a total system cost of $52.24/h, a levelized cost of hydrogen production at $16.54/kg, and a levelized cost of electricity generation at 10.03 cents/kWh.

The investigation of temperature-induced and heat-driven diffusion effects on the off-centered stagnation point flow (OSF) of non-Newtonian fluid (NNF) across a rotating disk (RD) has considerable applications in industries, including concurrent heat and mass transfer. The applications include polymer extrusion, chemical vapor deposition, petroleum refining, and heat management systems using NNFs. Inspired by this, the present work investigates the Dufour and Soret consequences on the OSF of Maxwell fluid via an RD. Additionally, the influence of thermophoresis and Brownian motion is considered to assess the mass and heat transport attributes. The governing differential equations are converted into ordinary differential equations by applying the appropriate similarity transformations. Furthermore, the reduced equations are solved numerically by employing the Runge–Kutta Fehlberg fourth–fifth-order approach. Moreover, the fluid's profile is evaluated using the artificial neural network technique. The significant outcomes of the study show that the rotation parameter reduces the azimuthal velocity while enhancing the radial velocity. The velocity profile declines as the Maxwell parameter rises. The thermal profile increases with higher values of the Dufour number, thermophoresis, and Brownian motion parameters. The rise in the thermophoresis parameter and the Soret number increases the concentration profile.

Spiral solid fins are extensively used for the removal of waste heat from exhaust gases. However, they undergo thermal degradation due to high-temperature conditions. This setback is addressed by the use of porous media. Hence, in this study, we used spiral fins made of high-porosity metallic foam samples. The thermal and hydrodynamic performance of these fins was evaluated in a three-dimensional domain using computational fluid dynamics technique. The foam samples were subjected to analysis using the Darcy–Brinkman–Forchheimer and local thermal nonequilibrium models. The foam samples had variable pore densities ranging from 5 to 40 pores per inch (PPI) and differing porosities. The study focused on spiral fin pitch (P_f) between 2.4 and 6.4 mm. Turbulent flow conditions were modeled using the realizable κ–ϵ model in ANSYS Fluent. Samples with variable pore densities were first evaluated for their thermal and flow parameters. Flow streamlines reveal a vortex formation near the fin base that intensifies with fin spacing. The overall performance study recommends the use of a 20-PPI foam sample due to its superior performance compared to others. To study the effect of porosity, samples with porosity varying between 0.9005 and 0.978 were used. It was observed that the resistance offered by a specific foam sample is crucial in determining the pressure drop, while the heat transfer depends on the specific surface area of the porous sample. The overall performance analysis of all foam samples based on the area goodness factor and the ratio of heat transfer per unit temperature difference to the pumping power of the assembly (Z/E) recommends the use of a 20-PPI foam sample with a porosity of 0.9005. On the other hand, the samples with the highest flow resistance and lowest specific surface area are termed undesirable due to their higher pressure drop and lower heat transfer rate.

Roll coating (RC) is a fundamental process in both industrial and decorative applications, including the production of wallpapers, plastic and photographic films, adhesive tapes, magnetic recording media, and packaging materials. In this study, we develop a mathematical model for the flow of Powell–Eyring fluid confined within a narrow gap formed between a moving roll and a fixed substrate. An analytical framework based on the perturbation method is constructed to obtain approximate solutions for the velocity field, temperature distribution, pressure gradient, and pressure profile. A comprehensive comparison between numerical and analytical results is presented, validating the accuracy and reliability of the proposed formulations. Parametric analysis highlights the impact of key material and flow properties on coating thickness, velocity, pressure distribution, temperature variation, separation force, power input, and Nusselt number. The maximum coating thickness attains $��\; ��0.7233��$ at $��\; ��W�\; �e�\; �=�\; �0.9��$, while the minimum value is $��\; ��0.5810��$ at $��\; ��F�\; �=�\; �0.09��$. Nusselt number increases with higher Brinkman number, signifying stronger heat transfer effects. A mechanism for controlling the coating thickness, power input, separation force, Nusselt number, and pressure distribution is provided by the material properties involved, offering practical insights for optimizing RC operations across diverse industrial applications.