Journal of Thermal Analysis and Calorimetry最新文献

Enhancement in heat transfer can be realized by adding nanoparticles to boost the thermal properties of the base fluid, increase the tube surface area, and modify the flow trajectory of the fluid. In the present investigation, the convective heat transfer and pressure loss characteristics of Al₂O₃-Ethylene glycol and Al₂O₃-Water-based nanofluid in the vertically positioned helically coiled tube with micro-fin are studied by ANSYS FLUENT 19.2 through numerical methods. The effects of nanofluid mass fraction (1–4%), Reynolds number changing (10,000–30,000), micro-fin number (4–12), and the coil diameter (100–200 mm) on the heat transfer coefficient and pressure drop characteristics are carried out. The heat transfer and pressure drop characteristics are found to be highly sensitive to changes in Reynolds number and nanoparticle volume concentration. Furthermore, an increase in micro-fin density contributes to elevated heat transfer coefficients and higher pressure losses in nanofluid. The study confirms that the thermal performance index of Al₂O₃-Ethylene glycol nanofluid is universally lower than that of Al₂O₃-Water nanofluid across all nanofluid mass fraction.

Enhancing the heat transfer efficiency of solar air heaters (SAHs) remains a critical challenge in renewable energy applications due to the inherently poor convective characteristics of air. Improving the absorber plate design through optimized roughness geometry is therefore essential for achieving higher energy conversion efficiency. Despite numerous studies on conventional rib geometries, limited attention has been paid to the comparative thermo-hydraulic behaviour of fixed and variable arc rib configurations under identical boundary conditions. This study numerically investigates the thermal and fluid flow performance of SAHs equipped with three arc rib geometries: Fixed Arc Rib (FAR), Fixed Arc Rib with Diameter variation (FARD), and Variable Arc Rib (VAR) over two duct lengths (1 m and 2 m). Simulations were performed using the RNG k–ε turbulence model under a uniform heat flux of 1000 W m⁻² and Reynolds numbers ranging from 3000 to 21000. The results reveal that the VAR(1 m) configuration achieves the highest thermal efficiency (93.2%) and exergy efficiency (2.65), while FARD(1 m) exhibits the best thermo-hydraulic performance parameter (THPP ≈ 6.1). Velocity contour analysis further confirms enhanced mixing and turbulence intensity for variable rib geometries. The findings offer practical design guidance for developing compact and energy-efficient solar air heaters suitable for sustainable heat recovery systems.

The study is concerned with the optimization of performance of solar drying to be carried out on ivy gourd (Coccinia grandis) making use of indirect convection-based technologies. The results of three systems of dryer such as indirect solar dryer (ISD), mixed-type solar dryer (MSD) and greenhouse solar dryer (GSD) were compared based on drying kinetics, product quality, nutrient retention and energy consumption. The effect of four important parameters such as drying temperature, drying time, air velocity and type of dryer used was studied using response surface methodology (RSM). The experimental analysis indicated that the rate of drying was very much enhanced with variation of temperature and the air velocity, the value being high (19.7 g h^–1) in the mixed-type dryer. A maximum of nutrient retention (86.2) was achieved at the moderate temperatures and low drying times, more so when the application of energy efficiency with consideration of designs in dryers was adopted. Nonetheless, the increased temperature of drying and an increased time had significant knock-off effects on the heat-sensitive nutrients. The difference in energy consumption across conditions was quite large with a high of 15.7 kWh attained at the maximum parameter level. The paper presents essential trade-offs between the consumption of energy and the quality of products. The indirect dryer exhibited a high degree of energy efficiency, and the mixed-type dryer provided relatively high rates of drying with tolerable loss of quality. The greenhouse dryer demonstrated a well-balanced ratio in the quality and sustainability indicators. RSM integrations enabled determination of the best drying conditions, which at the same time consumed minimal energy and preserved maximum nutrients. The study has added a strong framework in the designing and operation of solar drying systems that address various agro-processing requirements, a sustainable, energy-efficient and quality food preservation at post-harvesting.

Forest fires mainly come from the surface fuel layer, and the key to reducing the risk of forest fires is to block the spread of surface fires. Due to the complexity of the terrain environment, it is difficult to achieve efficient and rapid fire prevention by conventional physical means, which increases the difficulty and cost of forest fire prevention and control. Therefore, it is imperative to find a suitable, effective and clean extinguishing agent. In this paper, the inhibition test of fire extinguishing agent isolation zone in indoor environment was carried out on the spread of surface litter fire in the area with frequent forest fires in Southwest China. Three different fire extinguishing media, water, foam fire extinguishing agent and hydrogel fire extinguishing agent, are used. The results show that the different extinguishing media are able to suppress flame spread of mixed leaf litter combustion and the phenomenon of flying fire. However, as the slope increases, water and foam extinguishing agents cannot completely inhibit the spread of foliage litter flames, and during the period of inhibition by these two extinguishing media, when fuel flames are prone to spreading and burning across the containment zone, hydrogel is effective in inhibiting the spread of foliage litter flames. Comparing the peak temperature of TC1 before isolation zone and the peak temperature of TC5 after isolation zone, the reduction is about 70 °C, 176 °C and 208 °C in the three extinguishing media conditions, respectively. And the cooling effect of hydrogel is the best compared with water and foam extinguishing agent. Based on the results of different widths of hydrogel barrier inhibiting the spread of leaf litter at different slopes, the relationship model between the intensity of surface fire spread at different slopes and the width of hydrogel barrier is constructed, and the boundary conditions of the hydrogel barrier inhibiting the spread of surface fire in leaf litter are determined, which is of great significance for the design of forest fire fighting systems.

Scholars are interested in the significance of this study, which looks at a transportation phenomenon where the host fluid is fully mixed with three different types of nanoparticles (ternary hybrid nanofluid). Tri-hybrid nanofluid's (THNF) special capacity to enhance thermal performance is the main driver of its growing popularity, as it is highly beneficial in a variety of heat exchangers. In order to observe the fluid heat presentation, the primary goal of this research is to analyze the Incompressible, unsteady, laminar 3D magnetohydrodynamics (MHD) ternary hybrid flow with the model of heat flux and viscous dissipation of nanofluid between two surfaces. This method for succeeding a well heat conductor than hybrid nanofluid (HNF), and mono nanofluid is described by this model. Three different kinds of nanoparticles with unique chemical and physical bonds are added to water as a base liquid to create the ternary nanofluid. This mixture aids in environmental cleaning, the breakdown of harmful materials, and the cooling of other devices. At z = 0, the lower disk remains fixed the top disk moves axially, while causing the liquid to squeeze. A homogenous suction or injection is applied at the lower surface. At the fixed bottom disk, the effects of energy and velocity slip are also taken into account. The governing equations are transformed into nonlinear ordinary differential equations (ODEs) by applying the proper similarity functions, and the bvp4c approach is then used to solve them numerically in the MATLAB environment. The results are then graphically shown to examine the velocity, temperature and concentration profiles. Finally, we determine that the thermal conductivity of tri-hybrid nanoparticles is well as compare to hybrid and nanofluids particles since the temperature profile reduced against the tri-hybrid case in the bottom disk case and subsequently increased near the top disk in the tri-hybrid case. For a small number of examples, the current findings are shown to be in good agreement with existing literature.

To improve the slow crystallization and difficult processing issues of polyethylene terephthalate (PET) and enhance its mechanical properties, we prepared a nucleating agent composed of sodium linoleate and talc, studied the synergistic effects of both individual and composite components on properties of PET, and established that the optimal talc to sodium linoleate ratio is 1:1. The sodium carboxylate component serves as the primary active agent governing PET crystallization. The synergistic action of both can lower the crystal grain size during PET crystallization, resulting in a 13–23% enhancement in flexural modulus. Based on the findings, we prepared five alternative compound nucleating agents (CNAs) made from sodium carboxylate and talc. Among them, the crystallization performance and mechanical properties of PET nucleated with the CNA in which the mass ratio of sodium linoleate to talc is 1:1 exhibited the most significant enhancement compared with pure PET, surpassing the performance improvement observed in PET nucleated with the commercial nucleating agent P250. The findings indicate that the nucleating agents developed in this work demonstrate significant potential to substitute commercial nucleating agents, reducing production costs, enhancing PET characteristics, and facilitating industrial manufacturing.

The main problems with the selection and operation of fan coils in air conditioning systems impact thermal comfort and energy efficiency, and research on fan coil performance at various operating points is inadequate. No research on artificial neural networks has been undertaken about a concealed ceiling-type electronically commutated motor fan coil that has been subjected to extensive experimental assessments. Four artificial neural networks were trained using 1700 test points to predict the thermal performance and capacity as a main aim. The experiments were conducted in a test apparatus designed according to related standards and an indoor air and heat exchanger fluid regime based on international test norms. The first model estimated air flowrate using six input parameters. The second one estimated air outlet temperature and total cooling capacity using five input parameters. Then, the third one estimated heat exchanger fluid side pressure loss using five input parameters. Lastly, the fourth one estimated air outlet temperature, fan power, and total cooling capacity using eight-input parameters. The Levenberg–Marquardt training algorithm was employed in the feedforward backpropagation multilayer perceptron network model comprising 10 neurons in the hidden layer. The deviation obtained for the air flowrate was  − 0.255% in the first one, while the deviations obtained for the air outlet temperature and cooling capacity were  − 0.195,  − 0.012%, respectively, in the second one. In the third one, the fluid pressure loss exhibited a deviation of − 0.014%. In contrast, the air outlet temperature, cooling capacity, and fan power exhibited deviations of + 0.045, − 0.014, and + 0.283%, respectively, in the fourth one. This study promotes energy-efficient industries using artificial intelligence-driven performance modeling as a collaboration sample between university and industry.

This paper deals with the two-dimensional numerical modelling and dynamic simulation of photovoltaic (PV) module attached with phase change material (PCM) loaded with different nanoparticles (to form PV-NEPCMs) operating at various inclinations ((theta)) for thermal regulation. The study investigates PV-NEPCM systems using n-octadecane PCM loaded with titanium dioxide (TiO₂), copper (Cu), and cupric oxide (CuO) nanoparticles at a mass concentration of 3%. The inclination angles considered are 0°, 15°, 30°, and 45°. Additionally, the effect of varying Cu nanoparticle mass concentrations (0%, 3%, and 5%) is analysed. The findings show that loading of nanoparticles in PCM improves rate of heat transfer and effective thermal conductivity. Out of three NEPCMs studied, Cu nanoparticles are able to give the lowest average PV temperature. The maximum PV temperature reduction of 1.67 °C compared to the conventional PV-PCM system is obtained for PV-NEPCM loaded with Cu nanoparticles at 0° inclination, and the relative impact of NEPCM diminishes with the increase in inclination. It is also found that the mean velocity magnitudes of melted NEPCMs are lower than pure PCM at all inclinations, indicating a decrease in strength of the convection current in NEPCMs. The PV power output rose from 18.6 W in the PCM system to 18.82 W in the Cu-loaded NEPCM system at an inclination of 0°. The study also investigates the effect of varying Cu nanoparticle mass concentration in NEPCM on PV temperature. The greatest PV temperature reductions of 2.37 °C at 0° and 1.03 °C at 45° are observed compared to the conventional PV-PCM system.

Nitrocellulose (NC)-based propellants are reactive solid materials and inherent instability. These propellants undergo chemical and physical changes upon aging, which can reduce their stability and potentially leading to safety issues. Ensuring the stability of NC-based propellants is crucial for safe and efficient operation within propulsion system. To mitigate this issue, stabilizers are incorporated into propellant formulations to improve the stability performance by slowing down autocatalytic reactions so that the safe storage life of propellant can be extended. Recently, the progress in the application of stabilizers in NC-based propellants has garnered extensive attention due to the necessity to enhance stability performances and prolong shelf life of propellants. This review examines various stabilizers utilized in NC-based propellant formulations, elucidating their mechanisms of action, thermal behavior, and compatibility with NC. Through comparative analysis, the advantages and limitations of both conventional and emerging stabilizers are evaluated, with a particular focus on novel compounds demonstrating improved the thermal stability and compatibility with NC. Additionally, the methods used for evaluating the stability performances of NC-based propellants are discussed, focusing on the compatibility and thermal behavior of stabilized NC. The challenges and future directions are identified, paving the way for further advancements in propellant stability. Overall, this review aims to provide a comprehensive understanding of the effect of stabilizer in improving the stability of NC-based propellant, thereby contributing to the development of safer and highly efficient propellants.

By virtue of significant thermal properties, nanofluids have much importance in medical field, pharmaceutical arrangements, electric batteries, chemical engineering areas and industrial heating and cooling processes. This study explores the changing effects of three-dimensional (3D) flow of (WNFM). Due to shear thinning feature of WNFM, this plays a vital role in chemical industries, plastic industries, oil industries, biotechnology and graphic designing. Modeled arrangement of PDEs is transfigured to arrangement of ordinary differential equations (ODEs) via similarity transformation. System of ODEs is then coded into Mathematica software. Numerical dataset is obtained by applying ND-Solve technique. Numerical dataset is then transferred into MATLAB for graphical study. Obtained system of ODEs is numerically solved by classy Levenberg–Marquardt backpropagation scheme (LMBS) joined with neural networks (NNs) of artificial intelligence (AI). Results are gauged through performance graphs under NNs of AI in LMBS. Engagement of regression illustrations (RIs), mean-squared errors (MEs) training state analysis (TSA), and histogram analysis of errors (AHEs) is considered for accuracy and convergence of results. Along temperature, concentration, bioconvection, and velocity profiles, various parameters are analyzed including Lewis number, thermophoresis parameter, Prandtl number, magnetic parameter, parameter of temperature ratio, thermal Biot number, parameter of chemical reaction, and parameter of Brownian motion. The absolute error factor ranges in the bracket of (left[{10}^{-6}-{10}^{-3}right]). This study of WNFM shows momentous associations for real-time applications.