Regeneratively cooled scramjets using hydrocarbon fuels require high-performance heat exchangers to limit structural temperatures and manage the thermodynamic complexity of supercritical coolants. Additive manufacturing can improve the manufacturability of airframe components and cooling infrastructure but also introduces increased wall roughness. The influence of wall roughness on heat transfer to supercritical hydrocarbons remains insufficiently characterised, particularly in numerical simulations. In this study, heat transfer to supercritical n-decane in rough-walled heat exchangers is investigated using computational fluid dynamics and validated against experimental measurements. Reynolds-averaged Navier–Stokes simulations are performed using the renormalisation group k – ε and shear stress transport k – ω turbulence models. Wall roughness is represented using three approaches: numerical roughness via wall-function, statistically generated roughness, and an idealised sawtooth geometry. The renormalisation group k – ε model coupled with geometrically resolved roughness provides the closest agreement with experimental data, with mean errors of 5–10% for wall temperature and 13–26% for Nusselt number. The shear stress transport k – ω model generally overpredicts wall temperature when combined with geometric roughness but shows improved accuracy when a numerical roughness treatment is employed. A parametric study examines the effects of roughness, heat flux, and pressure on heat transfer. Roughness levels typical of additive manufacturing increase the Nusselt number by up to 320% relative to a smooth tube and reduce peak wall temperature by as much as 300 K. A new Nusselt number correlation incorporating wall roughness and supercritical thermophysical property variation predicts 89% of experimental data within ±30% error, outperforming conventional correlations. • The main conclusions of the study are RNG k–ε with geometrical roughness yields the lowest heat-transfer prediction error. • SST k–ω shows improved accur acy when roughness is modelled numerically. • Maximum thermal performance occurs for roughness in the range ε r = 0.005–0.025. • Increasing reduced pressure attenuates both heat-transfer deterioration and enhancement. • The proposed Nusselt correlation outperforms classical models for rough supercritical flow.

Experimental research on heat transfer enhancement and pressure drop in tube fitted with foam copper on the shape of twisted tape

Enhancing heat transfer across metal/diamond interfaces with a graphene interlayer

Enhancing heat transfer in porous media with nanosolutions: A comprehensive review of mechanisms, models, and applications

Numerical study on structural optimization of a sinusoidal corrugated tube metal hydride hydrogen storage reactor

In this paper, our aim is to investigate the effect of gravity modulation on thermal convection in a rotating horizontal porous medium with vertical heterogeneity. A machine learning technique is employed to numerically compute and predict the heat transfer rate under constant, linear, quadratic, and exponential heterogeneity models. Both linear and weakly nonlinear stability analyses are conducted to determine the onset of convection under the combined influence of vertical heterogeneity, Coriolis force, and gravity modulation. The critical Darcy–Rayleigh number is obtained using the Galerkin method, revealing that rotation and vertical heterogeneity significantly affect the stability thresholds. Furthermore, a feedforward artificial neural network (ANN) approach is developed to predict the Nusselt number, enabling a data-driven assessment of nonlinear heat transport across varying physical parameters. The ANN is trained and validated using numerical data derived from the weakly nonlinear analysis, demonstrating high prediction accuracy and strong generalizability. The key novel findings are as follows: (1) the Taylor number exhibits a stabilizing effect on the system, promoting stationary convection and (2) gravity modulation suppresses convection at higher modulation frequencies while enhancing heat transfer at lower frequencies. This hybrid analytical and ANN approach provides a robust framework for analyzing complex convective phenomena in a porous medium.

Taylor-Couette (T-C) flow commonly occurs in the annular gaps of rotating machinery, and improving its heat transfer performance is essential for effective thermal management. However, existing empirical correlations often have limitations in both efficiency and accuracy. To address this, this study integrates machine learning with optimization algorithms to refine T-C flow configurations that incorporate elliptical slits, aiming to develop a more efficient and precise optimization approach. Four machine learning methods are compared against a predictive correlation to assess their prediction accuracy for T-C flow. The particle swarm optimization (PSO) algorithm is subsequently applied to determine the optimal slit parameters. The results indicate that the Genetic Algorithm-Back Propagation Neural Network (GA-BPNN) model is the most suitable model, showing the highest agreement between predicted and simulated values. By incorporating the PSO algorithm, the optimal slit width of 11.33 mm, slit depth of 12.48 mm, and slit number of 12 are obtained. The predicted results agree well with experimental data, exhibiting a relative error of only 2.99%. Compared to the rectangular slit model, the optimized elliptical slit enhances the Nusselt number by 17%. The methodology and findings presented in this study provide a methodological and technical reference for optimizing and enhancing T-C flow systems.

A numerical investigation of hydrodynamic and heat transfer characteristics in liquid-solid fluidized beds was conducted using a coupled CFD-DEM approach combined with a thermal model. Simulations were carried out for a range of particle and column diameters with varying inlet fluid velocities under isothermal wall boundary conditions. The model was capable of simulating the simultaneous effects of conductive particle-particle heat transfer and convective particle-fluid heat transfer. The accuracy of the coupled model was established by validating the results against experimental data in the literature on hydrodynamic characteristics and thermal behavior. It has been observed that the results obtained from the CFD-DEM simulation have a good agreement with the experimental data, and the average deviation is within the range of 6-8%. From the results, it was evident that the smaller particles improved the heat transfer performance. Enhancements of convective heat transfer and a decrease of temperature gradients in the bed with increasing inlet fluid velocity were found, especially in the column with the wider diameter. Results from the simulations elucidated the conductive heat transfer through contacts between particles as well as the convective heat transfer between fluid and particles, and showed that the interplay between particle size, column diameter, and fluid velocity determines the performance of heat transfer. The novelty in this research is the quantification of conduction and convection heat transfer interactions using a fully resolved CFD-DEM model for heat transfer. This research also gives practical guidelines on how to improve heat transfer in liquid-solid fluidized.

This study investigates heat transfer enhancement in a thin film flow over an unsteady stretching sheet by employing ternary nanofluids comprising three different nanoparticles suspended in water. Recognizing the limitations of conventional nanofluids, this research explores the synergistic effects of these nanoparticles to optimize heat transfer efficiency. Considering the significance of radiation in high-temperature applications, the study incorporates radiation heat transfer effects for accurate temperature predictions. Using similarity transformations, the governing equations are converted into a system of ordinary differential equations, which are then numerically resolved using Matlab's bvp4c solver. Response Surface Methodology (RSM) is used to examine the combined effects of radiation, magnetic fields, and nanoparticle composition on heat transfer properties in order to further improve heat transfer. By analyzing the impact of key parameters such as radiation, film thickness, nanoparticle volume fraction, suction/injection, magnetic field, and unsteadiness on skin friction, local Nusselt number, velocity, and temperature profiles, the study identifies optimal conditions for maximizing heat transfer efficiency. The findings suggest that thermal field of ternary nanofluid improves via radiation, stretching and Alumina nanoparticle parameters. Results also show that the optimized heat transfer involves a minimum Alumina nanoparticle parameter at the highest stretching and radiation parameters. This research provides valuable insights into the design and development of efficient thermal management systems in various applications, including aerospace, energy, and industrial sectors.

Boiling heat transfer enhancement using deformable composite surfaces integrated with shape memory alloys

Study on the heat transfer enhancement of hydro-turbine thrust bearing with nano-oil

Enhancing heat transfer performance in heated corrugated channels has become a main focus of investigation because of its crucial role in an extensive range of thermal systems. In the current study, a numerical investigation is carried out to examine the influence of laminar pulsating flow and SWCNT-water nanofluids on the flow behavior and heat transfer characteristics in a heat channel with nonequilateral triangle corrugations. Two different approaches are applied for nanoparticles motion such as homogenous single-phase model (HPM) and two-phase Eulerian–Lagrangian model (ELM). Governing equations are solved using the finite volume method. The computational fluid dynamics (CFD) simulations include Reynolds number, pulsation frequency and amplitude, volume concentration of SWCNT nanoparticles within the range of 250≤ Re≤1250, 1 ≤ f ≤ 4, 0.5≤ A ≤ 1, 0% ≤φ≤ 4% respectively. According to results, it can be said that while increasing pulsation amplitude, A always yields higher mean Nusselt number, Numean and heat transfer enhancement ratio, η pulsating flow is more effective at lower pulsation frequencies, such as f=0.5 and Numean and η deteriorates with subsequent increment in f. For instance, at Re=500, the mean Nusselt number increases from Numean=13.519 to Numean=15.282 when the pulsation amplitude is changed from A=0.5 to A=0.75 at f=0.5. This corresponds to a 13.04% enhancement in Numean. But this proportion is only observed as 0.378% increment in Numean for the change in pulsation amplitude from A=0.5 to A=0.75 at Re=500 and f=2. Furthermore, it was observed that Numean increases when the nanofluid model is changed from HPM to ELM especially at higher φ. At the optimal condition (Re = 1250, f = 0.5, A = 1, φ = 4%), Numean augmented by approximately 88% with HPM and 91% with ELM compared to the steady flow case, f=0. The outcomes provide design insights for compact heat exchangers in applications such as microchannel coolers, automotive radiators, and electronic thermal management systems demonstrating that low pulsation frequencies and high pulsation amplitudes can remarkably improve heat transfer performance without changing exchanger dimensions.

Numerical study on heat transfer enhancement of LBE flow in semicircular-fin fuel bundles

Abstract Based on the large-eddy simulation (LES) method, this study investigates the heat transfer characteristics of vortex rings generated by a starting jet impinging on a coaxial isothermal cylindrical wall, revealing the regulatory mechanism of the stroke ratio ( L/D ) on the heat transfer performance of the vortex ring. The results show that when L/D ≤3, increasing the stroke ratio enhances the entrainment and impingement intensity of the primary vortex ring, leading to higher peak values of the averaged Nusselt number and total heat transfer power, but a shorter effective duration. A critical L/D =3 threshold is identified where vortex rings reach formation saturation, transitioning from unsteady to quasi-steady jet behaviour. For L/D >3, further increasing the stroke ratio only increases the total heat transfer, while the heat transfer efficiency per unit jet medium tends to stabilize. Overall, the stroke ratio governs the formation and detachment characteristics of the vortex ring and serves as a key parameter for regulating its heat transfer enhancement performance. The findings of this study provide theoretical guidance for the structural design and parameter optimization of synthetic jet systems in compact electronic thermal management applications.

Robust jumping-droplet condensation.

Processing iridium foil targets for the production of radioplatinum isotopes.

Performance enhancement of a shell-and-tube latent heat thermal energy storage system using inclined straight and nozzle-shaped tubes

Preparation of methyl stearate phase change emulsion and its application in the thermal management system of a lithium-ion battery pack

This study presents an experimental analysis of thermal energy storage (TES) system at high temperatures combined with a parabolic trough solar collector. The system utilizes solar salt (NaNO₃–KNO₃ eutectic) for thermal storage and a graphene–TiO₂/ethylene glycol hybrid nanofluid as the heat transfer medium. The main aim is to assess the impact of the hybrid nanofluid on the charging and discharging performance in outdoor solar operating conditions. A 100-L TES tank with 360 sealed solar saltmodules was charged with an average thermal input of 2.3 kW provided by the solar collector. The temperature changes along the axis during charging and discharging were tracked with several thermocouples. The findings demonstrate enhanced heat transfer during charging, decreased thermal layering close to the melting point of solar salt, and prolonged heat-release time during discharging with the application of the hybrid nanofluid. The system's charging efficiency, discharging efficiency, and round-trip efficiency were 48.6%, 81.6%, and 39.6%, respectively. The results indicate the capability of hybrid nanofluid-assisted heat transfer to improve the thermal performance of molten-salt-based TES systems used in concentrated solar powerapplications.

Abstract Aiming at the limitations of conventional flat heat pipe structures in investigating loop working fluid flow and overall heat transfer performance, a visualized experimental system for a separated thermosyphon-thermoelectric coupling system was designed and constructed. This system spatially separates the evaporator and condenser sections, forming a circulation loop, to primarily investigate the effects of different heating surface structures (flat surface, vertical grooves), filling ratios (32.2%, 64.5%, 96.7%), and heat flux on the system’s heat transfer and thermoelectric performance. Experiments were conducted using both constant and variable heating modes, systematically analyzing key parameters such as the boiling/condensation heat transfer coefficients, superheat, system thermal resistance, and temperature stability. The results indicate that the vertical groove structure significantly enhances heat transfer performance; a 64.5% filling ratio is the optimal operating condition for the system; increasing the heat flux improves heat transfer efficiency, but the temperature stability exhibits opposite trends under different heating surfaces; the variable power heating mode demonstrates the system’s excellent adaptability to fluctuating heat sources.