Journal of Thermal Analysis and Calorimetry最新文献

Nanofluid (NF) as a new type of high thermal conductivity fluid, macroscopic research methods can only observe the macroscopic change of thermal conductivity of NF, but cannot further reveal the microscopic mechanism of nanoparticles. In this paper, the microscopic mechanism of thermal conductivity enhancement of NF was simulated based on non-equilibrium molecular dynamics method (NEMD), and the thermal conductivities of argon-based gold (Au–Ar) NF with different volume fractions and Au nanoparticle sizes are simulated separately, and the radial distribution functions, system densities, and tracking atom trajectories are computed to explore the mechanism of the action of the change in thermal conductivity of the nanofluids induced by nanoparticles at the microscopic level. It was found that the thermal conductivity of Au–Ar–NF system is positively correlated with the volume fraction of nanoparticles and negatively correlated with the particle size. When the NP particle size was 0.8 nm and the volume fraction was 6.0%, the NF thermal conductivity increased by 65.7% compared to the base solution. The key finding of the study was that the underlying liquid atoms on the surface of the nanoparticles form a non-fugitive adsorption layer, and that their arrangement resembles the ordered arrangement of a solid. In the model with r (NP) = 0.8 nm, the highest thermal conductivity was 1.21 times that of the base solution, and the thickness of the adsorption layer on the particle surface was about 0.35 nm. Generally speaking, the addition of nanoparticles alters the atomic configuration of NF, resulting in NF displaying a solid-like microstructure, which significantly increases the thermal conductivity of NF.

This study delved into the influence of starch botanic origin on the ultimate physicochemical properties and energetic attributes of modified starches. To accomplish this, starches extracted from potato (PS), corn (CS), and wheat (WS) underwent chemical modification via nitration, resulting in the creation of high-energy polysaccharides (NPS), (NCS), and (NWS), respectively, which were then subjected to comprehensive characterization. The principal finding of this investigation underscored the substantial impact of starch botanical origin on the properties of the resultant starch nitrate. Notably, the synthesized starch nitrate exhibited promising characteristics, including heightened density and elevated nitrogen content. Moreover, it is observed that both the short and long-term thermal stability of starch nitrate are influenced by the botanical origin of the starch, alongside their mechanical sensitivities, which diminish with higher nitrogen content. Through kinetic degradation analysis of all prepared nitro-starches, it was observed that the Arrhenius parameters decreased as nitrogen content increased. Specifically, starch nitrate derived from corn (NCS), with lower nitrogen content, displayed a higher energy of activation (E_a), while potato-derived starch nitrate (NPS), with the highest nitrogen concentration, exhibited the lowest activation energy value, indicative of its heightened reactivity.

The surge in electricity generation demand has led to heightened CO₂ emissions and climate change; thus, the emphasis on transitioning to renewable energy (solar energy) and enhancing energy efficiency (hybrid nanofluids) is emerged as the most significant solutions. The investigation examines MWCNTs-Al₂O₃-water hybrid nanofluid laminar forced convection in a circular duct subject to a uniform heat flux. The effect of MWCNTs nanoparticles percentage ratio (0 to 100%), total nanoparticles volume fraction (1 to 4%), and Reynolds number (100 to 2100) on thermal and hydraulic performance, entropy generation, and CO₂ emissions, embodied energy, and water saving is investigated numerically. ANSYS Fluent was employed to solve this issue using the finite volume method; validation of the current work demonstrates strong concordance with experimental, numerical, and theoretical investigations. Outcomes show that increasing Reynolds number, total nanoparticles volume fraction, and percentage ratio of MWCNT in hybrid nanofluid significantly affects the hydrodynamic and thermal entry region in terms of average velocity, outlet temperature, and the temperature gap in the system. The heat transfer coefficient enhances by up to 50.96%. However, the maximum pressure drop, Nusselt number, and thermal efficiency increased by 769.97%, 24.75%, and 24.75%, respectively. Moreover, the entropy production due to the thermal irreversibility was reduced by 32.65% compared with water showed for 4% of (100%:0) MWCNTs-Al₂O₃–water at Reynolds number about 2100. Furthermore, the embodied energy and water consumption, tube mass, and CO₂ emissions are reduced by 1.81041 MJ, 9.00691 m³, 0.00831 kg, and 1.09892 kg, respectively.

High-temperature heat damage is a common phenomenon in the field of mine mining, and as the mining depth increases, the degree of underground heat damage is also increasing, which seriously restricts the productivity of the mine and affects the physical and mental health of workers. Based on the mining situation of mineral resources, this paper summarized the formation mechanism and heat dissipation characteristics of different heat sources of mine high-temperature heat damage and analyzed the influence of heat damage on the mine production process and human physiological and biochemical indicators. Then, we summarized the existing cooling technologies, mainly divided into non-artificial and artificial cooling technology. The cooling mechanism and application status of cooling technology were introduced and analyzed and compared the characteristics and application scope of each cooling technology, which have specific guiding and reference significance for the selection of cooling technology for different degrees of heat damage mines. Finally, building upon the low-temperature rock formation pre-cooling technology, a novel concept for quantifying the mine inlet airflow volume was advanced, along with the formulation of a relationship model that correlates the geometry of the roadway with the temperature alteration of the airflow. This development laid a theoretical foundation for harnessing the ground temperature effect in shallow roadways to regulate the temperature of the mine’s inlet airflow, thereby enhancing the working environment at the mine’s working face.

This study employs a machine learning methodology, specifically the Random Forest (RF) model, to evaluate and optimize the productivity of a photovoltaic (PV) unit integrated with a cooling duct equipped with helical fins. A thermoelectric generator (TEG) is strategically positioned above the cooling duct to enhance electricity production. The cooling mechanism utilizes confined jets involving of ND-Co₃O₄- water nanomaterial to improve thermal regulation. The key variables considered include the number of fins (N_f), their revolution number (N_r), inlet velocity (V_i), and heat flux intensity (I). The optimization focuses on three primary objectives: maximizing profit, enhancing CO₂ mitigation (CM), and minimizing pumping power (W_p). The RF model showed strong predictive capability, achieving a test RMSE of 0.4590 and an R² of 0.9474 for W_p, an RMSE of 71.8501 and an R² of 0.8421 for Profit, and an RMSE of 2.9472 with an R² of 0.8143 for CM. A multi-objective optimization technique was used to derive Pareto front solutions, balancing trade-offs among these objectives. The results demonstrate that integrating helical fins and nanoparticle-infused cooling jets significantly improves system performance, with optimized solutions reducing pumping power, while enhancing both profit and CO₂ mitigation.

To reduce energy consumption, a model was developed to optimize a multi-generation system. The system integrates multi-effect distillation through thermal vapor compression (MED-TVC), solar flat plate collectors (FPCs), and photovoltaic panels (PVs). The objective function was to minimize the annual cost of the system. To achieve this, an evolutionary algorithm was employed to determine the optimal values of 34 design parameters. The design parameters considered for optimization included the capacity of the gas turbine as the prime mover, electrical chiller capacity, absorption chiller capacity, size of the boiler, partial loads of the gas turbine for each month of the year (12 values in total), number of FPCs and PVs, number of effects in the desalination unit, driving steam pressure, feed water flow rate, driving steam flow rate, and electric cooling ratio. A novel approach was introduced by incorporating a variable electrical cooling ratio, which represents the proportion of electrical and absorption chiller usage, for each month of the year. The optimization aimed to fulfill the heating, cooling, electricity, and freshwater requirements of a residential complex situated in Bandar Abbas, Hormozgan Province, Iran. The optimization results were compared with a constant electrical cooling ratio system where the electrical cooling ratio was assumed to be fixed throughout the year. The optimal scenario, considering the variable electrical cooling ratio strategy, yielded an annual cost of $0.9780 × 10⁶ $/year, indicating a significant 10.11% improvement compared to the conventional case ($1.0882 × 10⁶ $/year). These findings underscore the potential advantages of the proposed strategy in terms of cost savings and system performance optimization.

The improve design and enhanced thermal management systems nowadays depends upon the enhanced heat transfer capabilities of hybrid nanofluids and their wide range of applications. These lead to efficient cooling in electronic devices, thermal control in chemical processing, and several many industrial as well as biomedical applications. The proposed study aims to enrich the heat transfer characteristic of methanol-based hybrid nanofluid comprising CuO and MgO nanoparticles in convergent and divergent channels. The study focuses on the Jeffery–Hamel flow via porous medium where the impact of heat source is analyzed. The flow behavior is characterized by the role of several pertinent factors those are derived by the implementation of similarity variables in the governing equations. These rules help in transforming the dimensional form of set of equations into non-dimensional form. Numerical solution is presented for the set of equations by using bvp4c routine function in MATLAB particularly utilizing Runge–Kutta fourth-order. However, the investigation explores the key factors such as particle concentration, Reynolds number, Darcy parameter and heat source affecting various flow characteristic. The important results indicate that the existence of CuO and MgO nanoparticles significantly overshoots the conductivity and heat transfer rate in comparison with the base fluid. Further, the fluid velocity is significantly controlled by the increasing Reynolds number.

The thermochemical properties of phenyl and benzyl benzoates, including vapour pressures, enthalpies of vaporisation and enthalpies of formation, were the subject of this study. The datasets for each thermodynamic property were evaluated using quantum chemical calculations and structure–property correlations and recommended for engineering calculations. The energetics of hydrogenation/dehydrogenation reactions relevant to hydrogen storage were calculated and compared with the enthalpies of reactions of conventional liquid organic hydrogen carriers.

Graphical Abstract

Metallic foams have become a cutting-edge solution for many thermal management problems. These are of interest by thermal research community because of the cellular structure and have gas-filled pores inside a metal matrix. Due to the uniqueness in their structure, they exhibit good performance in boiling heat transfer because of the properties such as higher specific surface area, large number of nucleation sites, wettability characteristics, and capillary action. The boiling heat transfer over metal foam is a complex phenomenon, greatly affected by the thickness, porosity, and pores per inch (PPI) of metal foam along with the thermo-physical properties of the foam and boiling liquid. By thoroughly examining recent research investigations, the paper explains the impact of open-cell metal foams on pool boiling of different liquids such as water, refrigerants, organic liquids, and dielectric liquids. This paper reviews the complexity and various influencing factors involved in flow boiling through metal foam in tubes. It also highlights findings that show metal foam significantly enhances jet impingement boiling heat transfer. Moreover, the discussion on gradient metal foams, offering insights into their potential to enhance boiling heat transfer. The comprehensive review also encompasses numerical modeling studies, such as the lattice Boltzmann method, contributing to a deeper understanding of the intricate flow and heat transfer characteristics within channels filled with metal foam.

In this paper, a continuous microchannel with nonlinear cross section (M-NCS) applied to parallel plate heat exchangers is designed, and the M-NCS is quantitatively analyzed using an analytical calculation method. By comparing the M-NCS with the microchannel with a fixed cross section (M-FCS), it is deduced that under the same internal volume of the pipe and the same average flow velocity at the inlet, the internal flow rate of M-NCS is greater than that of M-FCS, with a local maximum increase of 43%, which can improve heat exchange efficiency. The Darcy friction factor of the internal fluid of M-NCS is smaller than that of M-FCS. The internal fluid pressure drop of the M-NCS is more significant, which requires a higher external pump energy required. It is also deduced that the average temperature change of the fluid inside M-NCS is larger than that inside M-FCS. In addition, the Nusselt number and convective heat transfer coefficient of the fluid inside M-NCS are larger than those of inside M-FCS. Moreover, the local maximum value of M-NCS is 18.5% higher than that of M-FCS. In summary, the obtained results show that, compared with M-FCS, M-NCS can improve the heat exchange degree and heat diffusion capacity of the fluid inside the microchannel pipe under the same inlet mass flow rate, allowing to enhance the heat transfer. This paper also studies the impact of the microchannel local structural changes on the heat transfer and fluid performance, which provides a theoretical support for the optimization of the microchannel design of heat exchangers.