International Journal of Thermophysics最新文献

Passive cooling and air-conditioning methods are being developed for both night-time and daytime cooling of buildings. A passive cooling skylight under development at Åbo Akademi demonstrated a night-time passive cooling effect of ~ 100 W/m². This depends strongly on the gas used inside the skylight, picking up (long wavelength, LW) thermal radiation via a lower window and after a natural convection transfer inside the skylight, releasing the heat to the sky via an upper window. Proof-of-concept work utilised air, carbon dioxide, ammonia and, for best results, pentafluoro ethane, HFC-125. The 2016 Kigali Amendment to the 1986 Montreal Protocol on HFCs necessitates using a low-global warming potential (GWP) alternative for HFC-125: future refrigeration installations cannot contain a GWP > 150 gas under European regulation. The key gas property is high emissivity/absorption in the LW range 8–14 µm, the “atmospheric window”, thus HFC-152a or HFC-41 could replace HFC-125. CFD simulations (Ansys Fluent 2024 R1) were used to calculate the passive cooling heat fluxes, temperatures, convection flow fields, and transported heat inside the skylight, comparing gases. Results show that HFC-152a (117.8 W/m²) and slightly less so HFC-41 (115.4 W/m²), both with a GWP < 150, can match the performance achieved earlier with HFC-125 (117.3 W/m²).

Understanding the evolution of frozen soil thermal conductivity under thermo-mechanical coupling is critical for predicting heat transfer in porous media. In this paper, the thermal conductivity evolution of sandy silt under thermal–mechanical coupling was systematically investigated using a thermal constant analyzer, focusing on the phase transition zone (PTZ, − 0.5 °C, − 1 °C, and − 5 °C). We quantified the effects of temperature (20 °C, − 0.5 °C, − 1 °C, and − 5 °C) and stress ranges (0 kPa, 25 kPa, 50 kPa, and 100 kPa) on thermal conductivity of sandy silt using thermal constant analysis and in-situ magnetic resonance imaging (MRI), while revealing microstructural drivers via pore-scale moisture distribution. The findings demonstrated an asymmetric thermal conductivity evolution between the unfrozen zone and the phase transition zone, with pronounced nonlinear behavior at subzero temperatures. One of the most significant enhancements (up to 55.7 %) occurred in the phase transition zone, where ice formation and stress-optimized particle contact cooperatively promoted heat transfer. The discrete ice crystal (− 0.5 °C) triggered a gradual increase in the thermal conductivity. At − 1 °C, the ice lens body gradually formed a continuous network, causing a sudden jump. Eventually, it was gradually frozen at − 5 °C, and the ice skeletal restructuring enabled steady enhancement through heat path optimization. The phase transition zone led to a significant increase in the microporosity of the sandy silt, forming an interconnected pore network that enhanced the heat transfer pathway. The results provide essential information for evaluating the thermal conductivity of fine-grained soils under freeze–thaw conditions and offer fundamental insights into heat transfer within porous media undergoing phase transition change.

Densities and sound speeds of the ternary system {propan-1-ol + pyridine + nitrobenzene} were measured at T = (293.15, 298.15, 303.15, 313.15, and 323.15) K and atmospheric pressure over the entire composition range, together with those of the corresponding binaries. Excess molar volumes and excess isentropic compressibilities, derived from the experimental data, were correlated using the Redlich–Kister and Cibulka equations for binary and ternary systems, respectively. The composition and temperature dependence of these properties provided information on intermolecular interactions and structural effects. Densities were modeled with the predictive PC-SAFT equation of state, while Schaaff’s Collision Factor Theory and Nomoto’s relation predicted sound speeds. The Jouyban-Acree model correlated density, sound speed, and their derived properties (isentropic compressibility and isobaric thermal expansivity) with a small number of adjustable parameters. Ternary excess properties were further compared with predictions from symmetric (Kohler, Muggianu) and asymmetric (Hillert, Toop) geometric models. Model performance was assessed using statistical indicators, demonstrating the applicability of both theoretical and empirical approaches to describe the thermophysical behavior of these mixtures.

The speeds of sound of ternary refrigerant mixtures, namely, R-444A (difluoromethane (R-32)/1,1-difluoroethane (R-152a)/trans-1,3,3,3-tetrafluoropropene (R-1234ze(E)) with respective mass fractions of 0.1194/0.0519/0.8287), R-457B (R-32/2,3,3,3-tetrafluoropropene (R-1234yf)/R-152a with respective mass fractions of 0.3489/0.5495/0.1016), and R-407C (R-32/pentafluoroethane (R-125)/R-152a with respective mass fractions of 0.5178/0.2480/0.2342), were measured using a dual-path pulse-echo technique at temperatures ranging between 230 K and 345 K and pressures between 0.14 MPa and 30 MPa. The standard uncertainties in temperature and pressure were 5 mK and 0.014 MPa, respectively. The average combined expanded uncertainty for all speed of sound data was 0.07%. Greater uncertainties were encountered as the system approached the critical regions where the speed of sound is more sensitive to changes in pressure. The experimental speed of sound data was used to assess the predictive capabilities of default REFPROP v10.0 mixture models with binary interaction parameters fit using mainly vapor–liquid equilibria and/or density data. We quantify the improvements for ternary mixture predictions when using updated binary interaction parameters that included speed of sound data in the fitting procedure. Reductions of 1.64%, 1.50%, and 0.11% in the average absolute deviations for R-444A, R-457B, and a R-125/1234yf/152a (0.3521/0.5465/0.1014 mass composition) mixture, respectively, are obtained with the updated binary interaction parameters. Further improvements to the mixture models could be made by refitting both the pure component equations of state and interaction parameters of certain hydrofluorocarbon binary pairs.

This study evaluates the potential of free cooling to improve marine HVAC efficiency under the coastal climate of Porbandar, India and examines the benefits of integrating thermal energy storage (TES) using phase change materials (PCMs). Analysis of hourly weather data for 2023 shows that free cooling is feasible for 45 % of the year, comprising 6 % (525 h) full free cooling and 39 % (3416 h) partial free cooling, which can reduce compressor load by 50 %. For a ship operating in harbor, this corresponds to annual fuel savings of 71,500 l, a reduction of 191.8 t of CO₂ emissions, and cost savings of ₹6.8 million. The highest potential occurs from November to February, particularly between the period 20:30 and 11:30, with over half of the air-conditioned hours during peak months allowing free cooling at a 27 °C supply air temperature set point. TES–PCM integration further reduces compressor load by 30 % and enhances onboard temperature stability. The methodology provides a framework to assess free cooling potential in other coastal regions and for ships at sea, demonstrating its viability as an energy-efficient, cost-saving, and sustainable solution for the maritime sector. The validation with real climatic data demonstrates measurable benefits in fuel consumption, emissions, and operational costs, underscoring both the scientific and practical significance of the findings in supporting sustainable and decarbonized maritime sector. This work is novel in extending free cooling and TES–PCM concepts, widely studied in buildings, to marine HVAC systems where research remains scarce.

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.