International Journal of Thermophysics最新文献

When using infrared thermography inspection methods to characterize the shape of surface defects in CFRP materials, traditional methods are mainly based on the analysis of infrared images at a single point in time, which makes it difficult to characterize geometrical features with complex shapes. In order to comprehensively analyze the performance of defects in different heating stages, this paper adopts the optimized contour extraction method to obtain the closed contour, and then constructs a fusion model of multi-temporal contours based on the Hausdorff distance function combined with the iterative calculation of weighted averaging method in order to more accurately characterize the defects in the final boundary morphology, and the fitting degree is higher than 95 %; For the selection of edge detection algorithms, this paper compares four commonly used edge detection algorithms, Canny, Sobel, Prewitt and Roberts, and the Canny edge detection algorithm is the most suitable for this study from the fitting degree quantization; the morphology of the defects in the practical application is affected by the secondary damages, the external stresses and the material structure, and often presents complex geometric features. In this paper, multi-shape cracks are processed and characterized separately and the fitting degree is higher than 90 %. This experimental study not only improved the shape characterisation capabilities of infrared detection, but also provided more reliable technical support for the identification and assessment of complex defects.

Simplified surrogate models have gained significant attention for effectively reproducing thermophysical properties of chemically complex rocket kerosene, which is widely used in liquid rocket engines. We used the Helmholtz-type equation of state and the extended corresponding state model to calculate the thermophysical properties of the surrogate model. To optimize the composition ratio of the candidate components, we employed the BP artificial neural network algorithm. As a result, we established four surrogate models, namely the 3-species component, 4-species component, 7-species component, and 9 species component models, which can effectively represent the thermophysical properties of petroleum-based rocket kerosene. The H/C ratio, molecular weight, density, isobaric heat capacity, viscosity, and thermal conductivity were selected as the performance indexes of the surrogate model. A test system designed for measuring the thermodynamic and thermal transport properties of rocket kerosene was used to test and report, for the first time, the thermophysical properties of petroleum-based rocket kerosene. This study was the first to obtain four thermophysical properties data of petroleum-based rocket kerosene at temperatures and pressures ranging from 298 K to 500 K and 1 MPa to 30 MPa, respectively. Upon averaging the average deviations of the four thermophysical properties for the four models under all test conditions, the data analysis revealed that the C9 model, which consisted of nine species, was the most suitable choice for calculating thermophysical properties. The average deviation in the thermodynamic properties between the C9 model and petroleum-based kerosene was 2.53 %.

Thermophysical properties data are crucial for education, research, process modeling, and operational activities in chemical engineering. Supported by the Korean government, Korea University has been providing this data continuously since 1997 (www.cheric.org). Recently, a new version of the Korean Thermophysical Properties Data Bank (KDB) (www.mdlkdb.com) has been developed and released. This updated version features an expanded database and enhanced calculation capabilities. It includes critically evaluated data for 1970 compounds and offers 5567 binary vapor–liquid equilibrium (VLE) data sets. The standard references are assessed based on criteria such as uncertainty, reproducibility, predictability, and consistency, ensuring the reliability and quality of the data. Additionally, machine learning methods for property estimation have been developed using the NIST/TRC database, and these calculation modules have been integrated into the new web interface. The property calculation page allows users to perform calculations for pure properties and binary vapor–liquid equilibrium using methods such as UNIFAC, COSMO-SAC, and a machine learning version of COSMO-SAC for certain simpler cases. This contribution outlines the functionalities and evaluation procedures of the KDB, which is an ongoing project aimed at enhancing the accessibility and reliability of thermophysical data while also improving precision in chemical process modeling and design.

Magnetic hybrid nanofluids (MHNFs), also known as ferrofluids, exhibit increased efficiency under an appropriate magnetic field. This work explores the effectiveness of heat transfer in MHNFs across various nanoparticle concentrations and magnetic field waveforms in both turbulent and transitional flow regimes. Five nanoparticle volume fractions (0.00625 % to 0.1 %) were tested under square, sine, and triangular magnetic fields across a Reynolds number (Re) spectrum of 1000 to 8000. Compared to DIW in the transitional regime, MHNFs showed up to 5.2 % improvement in the convective heat transfer coefficient at a 0.0125 % volume fraction, with average Nusselt number (Nu) increases of up to 5.1 %. The square wave magnetic field was particularly effective, enhancing performance by 8.8 % at 0.0125 % and 7.9 % at 0.00625 % in the turbulent phase. In the transition phase, Nu enhancements reached up to 31.38 % at 0.0125 % volume fraction without a magnetic field, with the square wave field achieving 36.1 % improvement, a 15.0 % increase compared to the no field case. Triangular waves induced the earliest transition onset at Re 2495.12 for 0.1 % volume fraction. The highest thermal performance factor (TPF) was 1.9789 for the turbulent regime and 4.2297 for the transitional regime. Triangular wave fields were most effective at reducing entropy generation, especially at high velocities.

The critical properties of the binary mixture of trans-1,3,3,3-Tetrafluoropropene (HFO-1234ze(E)) + 1,1,1,2-tetrafluoroethane (HFC-134a) and ternary mixture of HFO-1234ze(E) + HFC-134a + difluoromethane (HFC-32) were measured by an apparatus with variable volume. The critical properties of refrigerants can be determined by visually observing the critical opalescence phenomenon and reappearance of the meniscus. The combined expanded measurement uncertainties of the critical temperature, critical pressure and mole fraction were estimated to be less than 57 mK, 23 kPa, and 0.015 (k = 2, 0.95 level of confidence), respectively. The saturated vapor pressures and critical properties of pure HFO-1234ze(E) and HFC-134a were measured to verify the reliability of the apparatus. Redlich–Kister equations were used to correlate the critical properties of HFO-1234ze(E) + HFC-134a and the results were in good agreement with the experimental data. Cibulka’s equations were used to correlate the critical properties of HFO-1234ze(E) + HFC-134a + HFC-32 and the critical surfaces were plotted using Cibulka’s equations.

Nanofluids, colloidal suspensions of nanoparticles in a base fluid, have garnered significant research interest over the past two decades due to their potential as efficient heat transfer fluids in heat exchangers. Particularly interesting are nanofluids with nowadays very popular ionic liquids as base fluids. Understanding the behavior of nanofluids under forced convection in these systems is crucial, yet many studies have overlooked the impact on other system components. Our study focuses on the load exerted on system components by nanofluids. Specifically, we examined how varying nanoparticle concentrations influence the force exerted by the free jet flow of nanofluids on stationary obstacles. This aspect is critical as increased nanoparticle concentration generally leads to higher fluid density, potentially increasing the load on the system parts. Our findings indicate a correlation between nanoparticle concentration and the force exerted by the nanofluid's free jet flow on stationary obstacles. As the density of the nanofluid increases with higher nanoparticle concentration, so does the force exerted, confirming that the suspension of nanoparticles elevates the burden on system components. For illustrative purposes, at a temperature of 303.15 K and a nanoparticle mass concentration of 2.5 wt% in the Al₂O₃/[C₄mim][NTf₂] nanofluid, the relative increase in the force exerted by the free nanofluid jet on the stationary obstacle was approximately 5.7%. Further research into nanofluids' broader impacts is essential. Understanding these dynamics is crucial for optimizing their applications. Continued investigation into their mechanical and thermophysical effects is recommended to ensure efficient and safe integration into future technologies.

This study aims to develop sustainable PLA composites by incorporating coconut shell biochar (BC) (at 1, 2, 5 and 10 wt. %) and evaluating their mechanical, thermal, rheological, and water absorption performance. The composites exhibited enhanced tensile strength (21 to 68 MPa), hardness (28 to 53 HV), and flexural strength (a 62.5% increase), with crystallinity increasing from 24 to 47%. Thermal analysis revealed reduced stability but a 5% increase in char residue at 500 °C. Rheological improvements included higher storage/loss moduli and a 57% rise in damping factor. Water absorption increased with biochar content due to porosity and interfacial voids, confirmed by contact angle measurements. These results demonstrate the potential of PLA/BC composites as eco-friendly materials for packaging, agricultural films, and moisture-sensitive applications, contributing to sustainable development and greener urban environments.

A high-speed shadowgraph technique was developed to measure the linear thermal expansion of metallic solids up to approximately 2400 K during pulsed-current heating in vacuum. Niobium coupon specimens (3 mm × 100 mm × 0.5 mm) were resistively heated with a direct current of over 100 A for up to 2.3 s. The system incorporates a 405 nm bandpass filter, a Type-C thermocouple welded to the specimen surface, and a high-speed CMOS camera to enable high-contrast silhouette imaging under intense thermal radiation emitted by the specimen. Specimen elongation was determined by subpixel contour extraction of silhouette images, and the specimen temperature was recorded via the welded thermocouple. The relative linear thermal expansion (ε) and average coefficients of thermal expansion (α) were determined at three temperatures, yielding a maximum ε of 1.87 × 10^–2 between 334 K and 2352 K and a corresponding α of 9.28 × 10^–6 K⁻¹ at a mean temperature of 1343 K. In all three cases, the relative deviations from literature values were less than 1.2 × 10^–7 K⁻¹, which fall within the combined standard uncertainty of up to 1.83 × 10^–7 K⁻¹ (1.97%).

New physicochemical data for 2, 2, 3, 3, 4, 4, 4-heptafluoro-1-butanol (≥ 0.998 mass fr.) and 2, 2, 3, 3, 4, 4, 4-heptafluorobutyl acetate (≥ 0.994 mass fr.) are presented. The dependences of the saturated vapor pressure of 2, 2, 3, 3, 4, 4, 4-heptafluoro-1-butanol and 2, 2, 3, 3, 4, 4, 4-heptafluorobutyl acetate on temperature were obtained. The coefficients of Antoine’s equation are calculated based on the experimental temperature–pressure dependence data. This article also presents data on the rheological properties (viscosity and apparent activation energy for the viscous flow) of the studied compounds. The dependencies of refractive index and excess volume (density) on temperature are studied. Fourier transform infrared spectroscopy spectra are also provided. The experimental data presented in this paper extend and complement the information presented in the scientific literature. These data are background information and a starting point for further research in engineering design of chemical processing equipment. In addition, the received data may support the development of property models of pure substances and systems containing them, such as phase behavior and the processes underlying it.