Convective Heat Transfer Coefficient Research Articles

A Study of the Thermal Management and Discharge Strategies of Lithium-Ion Batteries in a Wide Temperature Range

The performance of lithium-ion batteries is greatly influenced by various factors within their operating environment, which can significantly impact their overall efficiency and effectiveness. In this paper, a multi-physics field electrochemical thermal model is established to measure the physical parameters of a battery module during the charge/discharge process. The effects of working temperature, current rate, and convective heat transfer coefficient are investigated by establishing an electrochemical and thermal model. The results are obtained by conducting numerous parameterized scans to analyze the system’s state across various operating conditions, enabling the determination of its temperature and the selection of appropriate cooling measures accordingly. Based on the internal and external conditions of battery operation, parameter selection corresponding to the operating range is divided into several stages, with thermal management strategies provided for each stage. The existing framework facilitates the design of battery packs equipped with efficient thermal management strategies, thereby enhancing the battery systems’ reliability and performance. Furthermore, it aids in establishing optimal operational and safety boundaries for batteries.

Evaluation of dropwise condensation from a vertical condenser tube impregnated with semisolid lubricant

AbstractThe quest for augmenting dropwise condensation heat transfer performance has been the driving force behind the exploration of innovative techniques and approaches to fulfill the desired objective. Mostly, earlier research on dropwise condensation was devoted to study condensation from horizontal tubes and plates but, rarely, addressed dropwise condensation from vertical tubes. An interesting topic of current research in dropwise condensation is to explore the application of Slippery Liquid Infused Porous Surfaces (SLIPSs) to improve the condensation performance. The aforesaid facts are the motivation behind the topics of interest in the present study. In this study, we explore the applicability of semisolid lubricant‐impregnated porous surfaces in enhancing dropwise condensation performance of a vertical condenser tube. The experiments conducted over a wide range of subcooling (5°C ≤ ΔT ≤ 65°C) in saturated steam environment showed significant improvement in condensation heat transfer coefficient of a vertical condenser tube impregnated with semisolid lubricants when compared to bare vertical condenser tube. The highest enhancement is found to be 280% at a subcooling of 40°C. Furthermore, these surfaces proficiently sustain dropwise condensation over a period of 72 hours without compromising heat transfer performance. The devised fabrication method is simpler, more cost‐effective, and less time‐consuming than earlier techniques used for creating SLIPSs. Additionally, an approach based on numerical optimization by a stochastic global optimization technique, namely, Genetic Algorithm, is proposed to retrieve the coefficients and the exponent in the mathematical expression of overall resistance, that is being used to compute the tube‐side dropwise convection heat transfer coefficient.

Performance analysis of a battery thermal management system based on phase change materials with micro heat pipe arrays

Lithium-ion battery packs generate high-level heat under harsh and rigorous conditions. The inadequate heat dissipation results in high pack temperature above the safe operating range. This study investigates an efficient and cost-effective battery thermal management system based on phase change materials and a micro heat pipe array. The battery is treated as a single domain. A battery pack with six series stacked batteries is analyzed using the Newman-Tiedemann-Gu-Kim model. The thermal performance of a battery thermal management system is analyzed using phase change materials with various melting temperature values, ambient temperature, and convective heat transfer coefficients of micro heat pipe arrays. Results show that the maximum temperature of the cooling system with micro heat pipe arrays and phase change materials is 33.8 °C, which is reduced by 22.3 % and 7.8 % compared to the air-cooled and cooling system with micro heat pipe arrays. At forced convection of 50 W·m−2·K−1, the maximum battery temperature values for the phase change material RT31, RT35, and RT42 are reduced by 11.8 %, 8.9 %, and 5.4 % compared to those at forced convection of 5 W·m−2·K−1. Under short-circuit conditions, the cooling system with micro heat pipe arrays and cooling system with micro heat pipe arrays − phase change materials reduce the maximum battery temperature by 12.4 % and 29.9 % compared to the air-cooled system. Results show that the developed model for the battery thermal management system provides a reference for designing phase change materials with micro heat pipe arrays.

Review on convective and radiation heat transfer between bridges and external environments

The heat exchange between bridges and external environments is the primary cause of the temperature effect on bridges. The complexity of the two-phase (gas–solid) heat transfer mechanism, the diversity of the surface characteristics of bridge materials, and the uncertainties of the environment in which bridges are located make the numerical calculation of the heat exchange between bridges and external environments difficult. Several studies have been conducted by scholars around the world. In this work, the research on convective and radiative heat exchange between bridges and external environments is surveyed, analyzed, and summarized. The influencing factors and calculation methods of bridge temperature are examined, and the convective heat transfer and radiation mechanisms, theoretical calculations, and experimental measurement methods used to investigate the relation between bridges and external environments are summarized and analyzed. The value determination methods for convective heat transfer and radiation absorption coefficients in the calculation of the bridge temperature field are summarized. In addition, the problems and shortcomings of current research are evaluated, and future research directions are identified and discussed.

Numerical and experimental analysis of a cross-finned solar receiver for parabolic dish collectors

A parabolic dish solar collector (PDC) is used to concentrate solar radiation on a receiver to produce hot water or steam for various thermal applications. The solar receiver of the PDC is one of the significant components to improve the overall efficiency of the PDC. The present study is a numerical and experimental investigation of the thermal performance of a solar receiver with vertical fins with and without cross fins. The fin orientation was investigated using 0.056 kg/s, 0.083 kg/s, and 0.111 kg/s water flow rates. COMSOL Multiphysics® was used to simulate the receiver to determine the receiver’s temperature behavior. The thermal performance parameters such as heat gain, heat loss, convective heat transfer coefficient, and thermal, and exergy efficiency were analyzed under various flow conditions. The cross fins effectively prolong the water residence, increasing turbulence, and heat transfer and reducing heat loss to the surroundings. The receiver with cross fins at higher flow rate conditions shows higher thermal performance than lower flow rate and without fins conditions. The solar radiation during the outdoor testing is in a range of 300–950 W/m2 and the ambient temperature varies from 30-37 °C. The peak average thermal and exergy efficiency obtained for the cross-finned receiver at 0.111 kg/s is 64.4 %, and 6.3 %, respectively. Cross-finned receiver operating at 0.111 kg/s reduced CO2 mitigation rate, estimated at approximately 0.29 tons of CO2 per year, along with a lower carbon credit gain at $0.47. Thus, the proposed cross-fin solar receiver demonstrates improved thermoeconomic performance than conventional receiver designs, offering a more cost-effective design with minimal investment.

Impact of fins and cooling fluid on the hydrogenation process in a LaNi5-Based metal hydride reactor for hydrogen storage

This study investigates the influence of different reactors incorporating copper circular fins within the hydride, along with variations in the reactor coolant—specifically water, oil, and nitrogen. Employing user-defined functions in the commercial software Ansys Fluent 15, a 2D numerical model was developed to assess thermal characteristics (temperature, heat flux, etc.) and kinetics of MH-hydrogenation, with a focus on the cooling fluid type. The reactor experiences diverse pressures (5–15 bar), an initial temperature of 298 K, and a coolant speed of 1 m/s. Validation of numerical results was performed against experimental data. The study delves into absorption properties of the storage reactor, examining crucial parameters such as hydrogen concentration, heat transfer coefficient of forced convection, and average temperature within the reactor. The findings reveal that coupling internal fins with water or oil as a coolant yields optimal performance, especially on an industrial scale. Nitrogen, on the other hand, exhibited the least favorable thermal performance, while the addition of fins significantly improved the cooling performance of the storage unit. Results were quantitatively analyzed across various scenarios to enhance understanding of the synergistic role of fins and cooling fluids in the storage performance of H2 within LaNi5 alloy.

Fundamental heat and entropy transfer mechanisms of convection underlying the first and second laws for an unsteady multiport system and their applications in parallel flow heat exchangers

Although thermal convection is ubiquitous in nature and technology, it has long been argued whether convection can be considered as an independent mode of heat transfer. Here, we show that pure convection mode is generally recognized from the classical first and second laws via mass flow by rooting the unsteady mass conservation relation through an equivalent multiport system. The fundamental distinction is made between convection driven by the thermal and entropy potential differences and mass flow accompanied by zero potential difference. The constitutive relations of the convective heat and entropy fluxes and their thermodynamic relationship are developed in terms of their potential differences with the exponential distribution of temperature difference in a compressible flow. In the absence of work transfer, the first and second laws are simply expressed by the standard Maxwell’s electromagnetic type equations via the total heat and entropy flux vectors. The pure convection theory is applied to a parallel-flow heat exchanger and the linear temperature difference distribution is obtained for both streams via the first-law definitions of the convective and overall heat transfer coefficients in an internal flow. The entropy generation rate inside a heat exchanger is recalculated and indicated to be driven by the difference between the reciprocal of outlet temperatures of two streams, from which the entropy generation number between outlets is developed to eliminate the entropy generation paradox. The present linear temperature difference profiles agree well with the experimental data, and the outlet entropy generation number is also justified by comparing with the previous nondimensionalizing entropy generation numbers.

In-flight anti-icing simulation of electrothermal ice protection systems with inhomogeneous thermal boundary condition

Conventional anti-icing computational solvers calculate the convective heat transfer coefficient using a homogeneous thermal boundary condition, assuming a constant temperature across the surface. However, this approach can lead to inaccuracies in regions with significant temperature variations. To address this limitation, the present study proposes a novel approach that utilizes an inhomogeneous thermal boundary condition, which updates the convective heat transfer coefficient based on the transient wall temperature distribution. We developed a unified finite volume framework that efficiently integrates various in-house solvers, including a compressible Navier-Stokes-Fourier (NSF) airflow solver, a Eulerian droplet impingement solver, a PDE-based ice solver, and a multilayer heat conduction solver. Thermal interaction between the different solvers was modeled using the conjugate heat transfer method. The effects of updating airflow on anti-icing results were investigated by comparing the results obtained by coupled and decoupled solvers. While the decoupled solver computes airflow once and remains unchanged, the coupled solver updates the airflow during the anti-icing simulation. Our findings show that the decoupled solver has the highest deviations from the coupled solver in evaporative anti-icing regimes, where dry regions form within the protection limits. Using coupled solvers in designing ice protection systems in evaporative regimes improves temperature prediction accuracy, enabling designers to reduce safety factors and save energy.

Wind-tunnel experiments on cross-ventilative cooling in a generic isolated building with one heated wall: impact of opening size

This paper presents wind-tunnel experiments of cross-ventilative cooling in a generic isolated building with an interior heated side wall. Two different sizes of openings are considered: large and small openings. Particle image velocimetry (PIV) is used to determine velocities in the vertical centerplane. Air temperatures in the vertical centerplane are measured using negative temperature coefficient (NTC) sensors. Surface temperatures on the heated wall are measured using an infrared camera. Surface heat fluxes are obtained using heat flux sensors. In both cases the indoor airflow is dominated by the jet through the openings, with higher velocities in the building with large openings. The air temperatures measured with small openings are up to 7.5% larger than those with large openings. The surface heat fluxes are up to 20% higher in the building with large openings. The interior convective heat transfer coefficients vary considerably across the heated wall for both opening sizes and can be very different (up to 5 times higher) from those obtained by existing internal convective heat transfer coefficient correlations. The measurement results give insight into the complexity of ventilative cooling and can be used to validate computational fluid dynamics (CFD) simulations of cross-ventilative cooling.

Effects of turbulent Prandtl number on supercritical carbon dioxide turbulent flow with high heat flux in vertical round tube

Supercritical carbon dioxide (sCO2) is a promising working medium for coal-fired power plants, high-temperature solar power systems, nuclear reactor systems, and fuel cells owing to its high efficiency and inertness. In these cases, the sCO2 is in a round tube under high temperature and pressure, far from the pseudo-critical point. Here, the thermophysical properties of sCO2 changes, resulting in large prediction errors. In this study, a conjugate heat transfer model with the k-ε turbulent model was created to analyze the tube performance of the sCO2, and the effects of turbulent Prandtl number (Prt) on the sCO2 turbulent flow with high heat flux were examined through experimental and numerical investigations. Prt had a considerable effect on the performance of the sCO2 turbulent flow far from the pseudo-critical point. The mean relative errors of the inner wall temperature and convective heat transfer coefficient were reduced by approximately 13% and 27%, respectively, when Prt was decreased from 1 to 0.55. For the sCO2 turbulent flow with a high heat flux, constant Prt values of 0.55–0.6 were applicable. The findings afford key insights for the development of sCO2 turbulent flow with high heat flux.

The thermo-mechanical coupling method of brake disc based on dynamic convective heat transfer

With the increase of train speed, the brake disk receives more heat input, causing its own temperature to reach a higher level. Due to the complex structure of the brake disk, its convective heat transfer coefficient is difficult to calculate, which makes the analysis of the convective heat dissipation between the brake disk and the air complicated. In this article, based on the software FLUENT and ABAQUS, by combining the fluid-solid coupling method and the thermo-mechanical coupling method, the dynamic convective heat transfer and the transient temperature field of brake disk are simulated. The maximum value of dynamic convective heat transfer coefficient is 483 W/m2 ∙ K at the running speed of 350 km/h. As for the transient temperature field, not only the contact relationship between the brake disk and the brake pad is considered, but also the dynamic convective heat transfer between the brake disk and the surrounding air domain is applied. The simulation results are more in line with the actual situation and the engineering application.

Computational fluid dynamics simulations of the heat transfer properties of graphene-based nanolubricants and application to hydrodynamic lubrication

In this paper, we consider experimental data available for graphene-based nanolubricants to evaluate their convective heat transfer performance by means of computational fluid dynamics (CFD) simulations. Single-phase models with temperature-dependent properties are employed for this purpose. The base fluid is a polyalkylene glycol, and we show the effect of the addition of carbon nanohorns and graphene nanoplatelets (GNPs), in different volume fractions, on the convective heat transfer coefficient between two parallel plates. Then, an application to hydrodynamic lubrication is discussed. The extreme in-plane thermal conductivity of graphene allows a smaller temperature rise of the GNP-based nanolubricant, i.e., a more effective heat removal. To the best of our knowledge, this work represents the first application of single-phase nanofluid models to hydrodynamic lubrication.

Efficient boundary conditions identification in thermal simulation of the spindle system with reduced order model and differential evolution algorithm

The boundary conditions in thermal simulation of the spindle system are very complicated and the empirically calculated ones will usually result in a significant discrepancy between experiment and simulation. Thus, the optimal boundary conditions were identified by treating it as an inverse optimization problem in this paper. Moreover, to advance the optimization efficiency, a reduced order model is established to replace the time-consuming thermal simulation of the spindle system. By superposition of truncated eigenmodes and accurately predicted modal coefficients, the reduced order model can reconstruct the field very similar to thermal simulation. Experimental reconstruction of both the temperature field and thermal deformation field by the reduced order model demonstrated its at least 360 times speedup with 99.8 % accuracy compared to the actual thermal simulation. With the accurate reduced order model as a lightweight digital twin and using the differential evolution algorithm, three types of boundary conditions, i.e., the heat generation rates, the convective heat transfer coefficients and the thermal contact resistances, under the shaft rotation speed of 4,000r/min were identified within 11s. The maximum temperature simulation error was reduced from 85.6 % to 6.6 % and the thermal deformation simulation error was reduced from 60.9 % to 10.8 %.

Computational Fluid Dynamics Heat Transfer Analysis of Double Pipe Heat Exchanger and Flow Characteristics Using Nanofluid TiO2 with Water

A device called a heat exchanger is used to exchange heat transfer between two fluids with different temperatures. Because of its durability and ability to handle high-pressure application, the concentric double pipe heat exchangers are widely utilized for numerous industrial applications. To conserve pumping power energy, many researchers were involved in study of the nanoparticles to be embedded in the fluid, which will enrich the fluid thermal conductivity and surface area. This article demonstrates the flow characteristics and convective heat transfer of nanofluids containing 0.2, 0.4 and 0.6 of vol% TiO2 nanoparticles dispersed in water under turbulent conditions, which mainly can be used for cooling nuclear reactors applications. Reynolds numbers varying from 4000 to 18,000 are examined numerically. The convective heat transfer coefficient results of the nanofluid agree well against experimental data, which are slightly more than that of base water at 1.94%. The results of the numerical model showed that the convective heat transfer coefficient of nanofluids will increase when the Reynolds and volume fraction increases. By increasing the temperature of the annular hot water, the heat transfer rate will increase, showing no major impact to the convective heat transfer coefficient of nanofluids. A generalised solution predicting the convective heat transfer coefficient for extensive nanoparticle materials is proposed. The conclusion of the empirical equation is tested among published data and the results are highly congruent, confirming the strength of the gamma equation.

NUMERICAL SIMULATION OF ENERGY-EFFICIENT SOLUTIONS OF THE ARC FURNACE STEEL MELTING BATH

Numerical modeling of hydrodynamics and heat and mass transfer in the arc furnace (EAF) steel melting bath under pneumatic stirring conditions demonstrates that the introduction of a «deep» bath with a form factor (ratio of diameter to depth) of 2.5 against the traditional 5.0 provides an energy-efficient bubbling mode of purging at higher inert gas flowrate. An increase in the diameter of the porous plug and the volume of the two-phase region in the "deep" bath allows in 150-ton EAF to increase the mixing power and the coefficient of convective heat transfer in liquid steel by 2-2.2 and 1.4 times on average, respectively. In the context of the «flat bath» process, it is shown the possibility of intensifying the convective melting of scrap in the bath by 24% in average and, thus, increasing productivity and, accordingly, improving the energy efficiency of the EAF.

Enhanced convective heat transfer in new triply periodic minimal surface structures: Numerical and experimental investigation

Triply Periodic Minimal Surfaces (TPMS) structures are increasingly recognized for their potential in thermal management due to their unique repetitive and interconnected minimal surfaces. However, a major challenge lies in enhancing the convective heat transfer performance of TPMS structures. This study introduces new TPMS designs and evaluates their thermal characteristics against established structures such as Diamond, Gyroid, SplitP, and Lidinoid employing a combination of numerical simulations and experimental measurements. The results reveal that the newly TPMS designs significantly outperform existing ones in terms of heat transfer performance. Numerically, the new TPMS structures demonstrate improvements in the Nusselt number and convective heat transfer coefficient, ranging from 6% to 13.7% and 4.6% to 20%, surpassing Lidinoid and SplitP, and eclipsing Diamond and Gyroid by 15% to 58% and 37% to 91%, respectively. Experimentally, these findings are complemented with the newly TPMS structures showing increases in convective heat transfer coefficients up to 68% and a 57% rise in Nusselt numbers compared to the Gyroid structure. These enhancements are attributed to their larger fluid-solid contact areas and optimized fluid distribution. However, a trade-off is observed in the form of increased pressure drops in the more complex TPMS structures, particularly in structures with larger circumferences and periodicities. The study also highlights the complex dynamic flow patterns within these structures, establishing a direct link between design complexity and fluid dynamics. This interconnectedness is pivotal for future design optimizations aimed at improving thermal performance. These findings represent a significant step forward in TPMS research, paving the way for further investigations into optimizing these structures for superior heat transfer performance.

Drying kinetics of lemon (Citrus lemon) seeds on forced-air convective processing

The convective drying kinetics of Citrus lemon seeds at different air temperatures (60–160 °C, 0.3 m.s−1), as well as the effect of air velocity (v) and technology (tray and rotary drum (RD) drying), were investigated. Internal seed temperature profiles showed that most of the process would occur under internal mass transfer control. Each drying curve was fitted with a theoretical diffusion model to determine the effective diffusivity (Deff), and with nine empirical models. Deff were 0.65 × 10−10-13.10 × 10−10 m2.s−1 and the activation energy was 19.90 kJ.mol−1. Deff increased by 85% when v was raised by 50%; this effect was partially compensated by seed movement when using RD (62% increment). A two-term exponential model with arrangements over the pre-exponential terms demonstrated the complementarity of both terms in explaining the seed dehydration process. In addition, convective heat transfer coefficients were calculated (0.48–0.65 W.m−2 K−1). Overall, the results provide valuable kinetic parameters to characterize the dehydration process for further design and simulation of drying equipment.

Computational Fluid Dynamics Prediction of External Thermal Loads on Film-Cooled Gas Turbine Vanes: A Validation of Reynolds-Averaged Navier–Stokes Transition Models and Scale-Resolving Simulations for the VKI LS-94 Test Case

Given the increasing role of computational fluid dynamics (CFD) simulations in the aerothermal design of gas turbine vanes and blades, their rigorous validation is becoming more and more important. This article exploits an experimental database obtained by the von Karman Institute (VKI) for Fluid Dynamics for the LS-94 test case. This represents a film-cooled transonic turbine vane, investigated in a five-vane linear cascade configuration under engine-like conditions in terms of the Reynolds number and Mach number. The experimental characterization included inlet freestream turbulence measured with hot-wire anemometry, aerodynamic performance assessed with a three-hole pressure probe in the downstream section, and vane convective heat transfer coefficient distribution determined with thin-film thermometers. The test matrix included cases without any film-cooling injection, pressure-side injection, and suction-side injection. The CFD simulations were carried out in Ansys Fluent, considering the impact of mesh sizing and steady-state Reynolds-Averaged Navier-Stokes (RANS) transition modelling, as well as more accurate transient scale-resolving simulations. This work provides insight into the advantages and drawbacks of such approaches for gas turbine hot-gas path designers.

Analysis and optimization of the heat transfer behavior in the melt-spinning process of Nd-Fe-B ribbons

Heat transfer plays a significant role on the quality of Nd-Fe-B ribbons in the melt-spinning (MS) process. In this paper, the heat transfer behavior in the MS process of Nd-Fe-B ribbons was investigated by experiment and simulation. A full flow channel heat transfer model with high accuracy is established using the “fluid-thermal” coupling method. The temperature distribution of the cooling roller and fluid field in steady-state is obtained. The simulated and experimental results of the outlet temperature are compared and the relative error is within 5%. The microstructures of the free surface and roller-sticking surface of Nd-Fe-B melt-spun ribbons are characterized by FE-SEM, and the refined grains are formed on the roller-sticking surface of Nd-Fe-B ribbons due to rapid solidification caused by the heat transfer from the roller. Moreover, a multi-nozzle structure is proposed for the MS process. The temperature distribution on the surface of the cooling roller in the axial direction is more uniform compared with the original single-nozzle structure, and the average convective heat transfer coefficient is increased by about 1.27 times after the modification of multi-nozzle structure, with a productivity of three times. Finally, the experimental design method of Latin hypercube sampling response surface design is used to obtain the response surface relationships of rotational speed, inlet flow rate, and water inlet temperature on the surface temperature of the cooling roller, respectively. NSGA-II multi-objective genetic algorithm (MOGA) is adopted for multi-objective optimization of process parameters. The optimized combination of process parameters is obtained with a relative error of about 0.41%. The research results are helpful to understand the heat transfer behaviors in the MS process of Nd-Fe-B ribbons, improve the utilization rate of the cooling roller and enhance the production efficiency in the actual application.

Investigation of maximum temperatures in lithium-ion batteries by CFD and machine learning

Alternative fuels are becoming more popular as awareness of fossil fuel depletion, pollution, and climate change grows. Numerous industrial companies are producing electric automobiles for use worldwide. Electric vehicles’ battery packs’ cooling causes firing due to high temperatures. In this study, the surface temperatures of a single electric battery with dimensions of 160 mm × 210 mm within a battery pack were investigated using computational fluid dynamics and, subsequently, Levenberg-Marquardt machine learning as a function of ambient temperature, convective heat transfer coefficient, nominal capacity of the electric battery, and discharge rate. The transport coefficient has been calculated for a rechargeable electric battery with a nominal capacity ranging from 14.6 to 20 Ah and a discharge rate varying between 1 and 15, taking into account conditions of stagnant air at temperatures ranging from 20°C to 35°C and values between 5 and 20 W/m2.K. Insufficient or absent cooling of battery temperatures can lead to them reaching combustion temperatures of electric vehicle batteries, typically from 50°C to 80°C, depending on the operational circumstances. An artificial neural network was utilized in machine learning to forecast maximum temperatures based on operating conditions without requiring simulation. The neural network achieved an estimated mean squared error of 0.00552 and a calculated coefficient of determination of 0.99. The neural network model can predict outputs with mean and standard deviation rates below 0.237. The anticipated artificial neural network model can accurately forecast the maximum surface temperature of an electric vehicle battery.