Journal of Thermal Analysis and Calorimetry最新文献

The interplay between economic growth and energy consumption naturally drives an escalating demand for energy. However, this surge in demand has prompted concerns due to the depletion of fossil fuel reserves, overdependence on such fuels, and their detrimental environmental impacts. Consequently, there has been a spotlight on a novel biomass fuel emerging in recent years. In order to support sustainable waste management practices, this study examines the effectiveness of several pre-treatment techniques in increasing the production of sustainable energy from municipal solid waste (MSW). Globally, MSW generation is projected to reach around 2.1–2.3 billion tons per year by 2025. Annually, MSW around the world contains almost 170 billion metric tons of biomass. Due to the complex nature and variability of these MSW, optimizing manufacturing necessitates a suitable preliminary treatment. This review synthesizes the major findings and insights about the effectiveness of various pre-treatment processes, their impact on briquette features, and their potential for wider implementation in MSW management strategies by a thorough analysis of the existing literature. The objective of this review is to stimulate additional research and real-world implementations in the waste management field by illuminating these innovative sustainable solutions. Municipal solid waste feature, its generation, and the diverse waste-to-energy (WtE) conversion technologies employed to create energy from waste were discussed. Researchers, decision-makers, and practitioners involved in waste-to-energy conversion as a substitute energy source will find this review to be a useful resource.

In response to environmental concerns, R1234yf is used in mobile air conditioning (MAC) systems, yet it can produce trifluoroacetic acid (TFA) in water bodies, a persistent pollutant with moderate phytotoxicity and high mobility. However, R152a, an alternative, faces challenges due to its flammability (classified as A2). To address this, we propose new R152a-R13I1 mixtures (M10–M50) as R1234yf replacements in MAC units. A Simscape/MATLAB model was developed to elucidate the thermodynamic performance of an MAC unit. Theoretical estimations showed a significant reduction in burning velocity (BV) and an increase in the lower flammability limit (LFL) when R13I1 was added to R152a. For instance, at 0.20 mole fraction of R13I1, BV decreased from 23.1 to 11.3 cm s⁻¹; while, LFL increased from 4.9 to 6.28 vol. %. Hence, M20 emerged as the optimal choice due to its A2L flammability classification and superior thermal properties. Simscape/MATLAB results revealed M20's 11.5–35.4% higher coefficient of performance compared to R1234yf. The model was validated against R1234yf data, showing 3.8–13.8% error. Additionally, M20's impact on MAC CO₂ emissions was evaluated, showing a potential 34.1% reduction compared to R1234yf. This highlights the environmental benefits of transitioning to R152a-R13I1 blends in MAC systems.

The ambient temperature is one of the factors affecting the operation and the fuel consumption rate in boilers. In this article, a D-type boiler was transiently analyzed from the aspects of energy and exergy during the cold start-up at different ambient temperatures. For this purpose, dynamic modeling of the boiler has been demonstrated by using thermodynamic and heat transfer governing equations. The numerical model compared with experimental data indicates high modeling accuracy. The results show that as the ambient temperature increases, the fuel consumption rate declines and the boiler efficiency rises by about 1%; this is due to the higher temperature of the inlet water as well as fuel flow rate reduction. Also, as the temperature increases from 2 to 32 °C, the fuel flow rate decreases by 10%; this analysis reveals that the existing boiler performance can be improved by preheating the inlet air. Exergy efficiency increases with the elevation of ambient temperature during the start-up. The exergy efficiency of the boiler at a temperature of 32 °C reaches 42% at its maximum value and 38.2% in a steady state, while the energy efficiency is 72% in this condition.

The micro-refrigeration system can be utilized in various fields, including personal cooling, medical applications, and other specialized fields. Compressors represent a crucial component of vapor compression refrigeration systems. A simulation model of the micro scroll compressor has been developed. The operating characteristics and leakage of scroll compressors with different capacities (10, 50, 100 cm³/rev) are compared. The effects of rotational speeds, condensing temperature, volume ratios, and clearance on the characteristics of micro scroll compressors have been analyzed. For the scroll compressor that has a suction capacity of 10 cm³/rev, the volumetric and isentropic efficiencies tend to initially rise and subsequently decrease as the rotational speed is raised. The volumetric efficiency reaches a maximum value of 86.26% at 5000 rpm, while the isentropic efficiency reaches a maximum value of 72.93% at 6000 rpm. As the volume ratio increases from 0.79 to 1.0 of the theoretical volume ratios, the volumetric efficiency remains stable, while The isentropic efficiency demonstrates a pattern of initially rising and then falling, reaching a peak of 71.63% at a volume ratio of 0.91 compared to the theoretical volume ratios.

Current article presents a comprehensive mathematical modeling approach to assess the productivity of a cold storage unit enhanced with advanced thermal management techniques. The storage unit, designed as a porous container, is filled with a hybrid nanomaterial that significantly improves the system’s efficiency. The model also incorporates the impact of radiation cooling to provide a more accurate assessment of the freezing. Given the negligible effect of velocity terms on the overall process, the mathematical model was simplified, focusing primarily on the energy equation. The Galerkin technique was engaged to solve the model, coupled with an implicit technique to account for unsteady terms. To further enhance accuracy, an adaptive grid was implemented, allowing for finer resolution near critical areas such as the advancing ice front. The results of the study reveal several key findings. The dispersion of hybrid nano-powders within the porous container accelerates the freezing process by approximately 7.11%, demonstrating the significant role these materials play in enhancing thermal conductivity. Additionally, the inclusion of radiation cooling further improves the efficiency, reducing the freezing time by 3.47%. Most notably, the incorporation of porous foam within the system leads to a remarkable 82.5% reduction in freezing time, highlighting its critical importance in optimizing cold storage systems.

The thermal performance of natural-based composites remains a significant challenge in their industrial applications, especially in plat heat exchanger (PHE). This study aims to address this challenge by developing a bio-composite material using Green-epoxy biodegradable resin reinforced with banana fibre (Bn-GBC) and silicon carbide (SiC) as a filler, with the goal of improving its thermal conductivity and for fabrication PHE polymer biocomposite based. The study explores the effects of adding 2 mass% and 8 mass% SiC to the Bn-GBC, and an intumescent fire retardant (IFR) coating consisting of 29 mass% ammonium polyphosphate (APP) and 1 mass% boric acid was applied to the Bn-GBC/SiC samples. The manufacturing process involved the use of vacuum bag resin transfer moulding (VBRTM) technique. The study conducted Thermogravimetric analysis (TGA) tests under an O₂ atmosphere, with processing parameters such as temperature and variation in heating rates set at 303–1173 K and 5, 10, and 15 °C min⁻¹, respectively. The kinetic mechanism in the material was examined by calculating the kinetic parameters. The activation energy (E_a) was evaluated using model-free (the Friedman and KAS approaches) and fitting model of the Expanded Prout-Tompkins (Bna). In conclusion, all samples defined their kinetic parameter, the use of IFR reveals that increases E_a value by approximately 10–14%. TGA and cone calorimeter results indicated that the use of 8 mass% SiC improved the thermal stability of the composite compared to 2 mass% SiC. Moreover, from both thermal tests indicate that the application of a 16 mass% IFR (29Exolit/1BA) coating helped maintain the thermal stability and delay decomposition process. Thus, the PHE prototype was developed with 8 mass% SiC addition and without SiC addition. The Experimental and numerical heat assessment analysis was performed, it is proven that PHE/8SiC has a higher heat transfer compared to PHE/0SiC.

This study investigates the heat transfer, thermal hydraulic performance, and entropy generation of turbulent flow in a horizontal double pipe heat exchanger. The heat exchanger is integrated with wire coil inserts, featuring various combinations of pitch ratios (P/Dc) and wire diameters (d), using numerical analysis. The RNG k-ε model and the finite volume technique have been utilized to solve the equations, and experimental data from published studies have been used to validate three-dimensional simulations. The computational findings have been obtained for a range of Reynolds numbers (Re) 5500 ≤ Re ≤ 11,500 using three different types of wire diameter (d = 1 mm, d = 1.5, and d = 2 mm) and pitch ratios P/Dc in the range of (3.125–0.625) for a heat flux of 5000 W m^-2. The effect of these parameters on the Nusselt number, friction factor (ƒ), entropy generation number, and thermal performance factor (TPF) are investigated and compared with those of plain pipe under similar conditions. The incorporation of wire coil inserts significantly improves fluid mixing by creating a swirling flow pattern. The Nusselt number showed its highest enhancement at 111.11%, coupled with a substantial 347.8% increase in friction factor penalty with P/Dc = 0.625 and d = 2 mm at the highest Re as compared to plain tube. The highest value of the TPF recorded during the investigation was 1.36, observed at P/Dc = 0.625 and d = 2 mm, with a Re of 5500. This study also compares numerical results with experimental findings, revealing variations within a range of ± 10%.

Understanding the mechanical properties of rocks under high temperature thermal cycles is critically important for deep geotechnical engineering construction. In this study, the mechanical properties and fracture evolution characteristics of Beishan granite after different temperatures of 25–800 °C and thermal cycles were investigated through multiple experiments. The results show that the tensile strength (σ_t) decreased from 7.49 MPa to 0.47 MPa as the temperature increased from 25 ℃ to 800 ℃, and further decreased to 0.43 MPa after thermal cycling. Incremental temperatures led to more active AE events, with AE cumulative events increasing from 25,250 at 25 °C to 99,389 at 800 °C, but AE cumulative events decreased in thermal cycles. The b-value presented higher level fluctuations at T ≤ 400 °C. When T ≥ 600 °C, the b-value before failure decreased and maintained small dramatic fluctuations, but fluctuated upward in the post-peak failure stage, indicating that rock failure changed from brittle failure to plastic failure. The proportion of shear cracks increased substantially with temperature and thermal cycles, from 14.22% at 25 °C to 23.11% at 800 °C. It can be also found that the damage variable (D_AE) increased with temperature under the same condition of stress. The physical and chemical reactions within granite at high temperature led to the initiation, development, and connectivity of numerous microcracks, especially when T ≥ 600 °C. The alternating thermal stress generated by cyclic heating will further promote the increase and propagation of microcracks, thereby exacerbating the damage to granite.

Comprehending and managing the transport characteristics of nanofluids is critical for improving their efficacy in heat transfer applications, thereby improving thermal management systems. This research focuses on investigating the impact of varying concentrations (0.05–1 vol.%) and temperatures (30–60 °C) on the thermal conductivity and viscosity of water-based nanofluids. These nanofluids contain graphene oxide, silicon dioxide, and titanium dioxide, as well as hybrid combinations thereof. The research revealed that nanofluids exhibit higher viscosity and thermal conductivity compared to water. The maximum thermal conductivity and viscosity of 1.52 and 2.77 are observed for GO for 1 vol% compared to the water at 60 and 30 °C, respectively. Notably, graphene oxide nanofluid exhibits the highest thermal conductivity and viscosity among all the studied nanofluids. These findings imply that graphene oxide and its hybrid nanofluids hold promise for enhancing heat transfer and energy efficiency in various industrial applications. The modeling and simulation of hybrid nanofluids' thermophysical properties are difficult and time-consuming. Modern machine learning algorithms are capable of handling such complex data. As a result, in the current investigation, two distinct ensembles and deep learning-based techniques, deep neural networks and extreme gradient boost, were used. The statistical examination of the viscosity model shows that the extreme gradient boost-based model had an R² value of 0.9122, while the deep neural network-based model had just 0.7371. The mean square error for the extreme gradient boost-based model was just 0.010, whereas it climbed to 0.0329 for the deep neural network-based model.