International Journal of Thermophysics最新文献

High-intensity focused ultrasound (HIFU) thermal therapies utilize concentrated sound waves to ablate diseased tissue at precise locations within the body. Computational simulations of HIFU can assist clinicians by predicting the death of target tissues, identifying sensitive healthy tissues that risk thermal damage, and optimizing acoustic power delivery to minimize treatment times and maximize treatment efficacy. Accurate simulations require accurate inputs, and many computational solvers neglect property changes induced by tissue heating during treatment. Additionally, temperature-dependent tissue property data in the literature are relatively scarce. This study presents methodology for characterizing temperature-dependent acoustic and thermal properties in ex vivo porcine muscle tissue. From 20 – 50 °C, speed of sound is found to increase from approximately 1580 – 1620 m/s. The acoustic attenuation coefficient increases for 20 – 50 °C from 0.09 – 0.24 Np/cm at 0.5 MHz and 0.16 – 0.37 Np/cm at 1.6 MHz. Thermal conductivity and thermal diffusivity increase from 0.52 – 0.55 W/m °C and 0.147 – 0.158 mm²/s, respectively, over 20 – 60 °C. Specific heat capacity increases from approximately 3500 – 3800 J/kg °C, over 20 – 80 °C. Each property is consistent with data found in the literature, extends the literature to a larger temperature range, and, for acoustic properties, extends to unique frequencies. Temperature-dependent predictive models are also developed for each of the five properties. This study’s property measurement methodologies can be used to characterize other biological tissues, and the predictive models developed herein will facilitate future efforts in temperature-dependent modeling and uncertainty quantification of HIFU thermal therapies.

Sound speed data measured using a dual-path pulse-echo instrument are reported for pure trans-1,2-dichloroethene (R-1130(E)) and an azeotropic blend of cis-1,1,1,4,4,4-hexafluorobutene (R-1336mzz(Z)) and R-1130(E) with a composition of 74.8 mass % R-1336mzz(Z) with the balance being R-1130(E). The azeotropic blend of R-1336mzz(Z)/1130(E) is classified as R-514A in ANSI/ASHRAE standard 34. Liquid phase speed of sound data are reported from just above the saturation pressure of pure R-1130(E) or the bubble point pressure of R-514A to a maximum pressure of 26.7 MPa. The relative combined expanded uncertainty in the speed of sound varies from 0.032 % to 0.148 % with the greatest deviations occurring at the lowest sound speeds. At present, no reference Helmholtz-energy-explicit equation of state (EOS) is available for R-1130(E). Therefore, the reported data for pure R-1130(E) are compared to an extended corresponding states (ECS) model. Deviations between the pure R-1130(E) sound speed data and the ECS model were found to be consistently negative ranging between − 4.1 % and − 3.5 %. The R-514A data are compared to a multifluid model inclusive of the established reference Helmholtz-energy-explicit EOS for R-1336mzz(Z) and ECS model for R-1130(E) with estimated binary interaction parameters. Deviations between the experimental speed of sound data and the multifluid model were also found to be consistently negative. However, deviations from the multifluid model were found to be as great as − 17.1 %. The large deviations from the ECS model and multifluid model underscore the need for a robust Helmholtz-energy-explicit EOS for R-1130(E).

This Note highlights the convenience of extensively flared capillary viscometers in the elimination of the kinetic energy correction and the consequent simplification of their calibration and use in liquid viscosity measurements.

The present study presents an artificial neural network (ANN) model developed to predict the thermal conductivity of steels at different service temperatures based on their composition. The model was developed using a comprehensive database of 413 datasets, spanning diverse steel compositions and pure iron across a temperature spectrum from 0 ºC to 1200 ºC, extracted from literature. The ANN model, with steel composition and temperature as inputs and thermal conductivity as output, underwent meticulous experimentation, resulting in an optimal architecture among 291 variations. The model was trained using 253 datasets and validated against an unseen dataset of 160 data points. The model exhibited superior predictive accuracy, boasting an R² of 98.42%, Pearson's r of 99.21%, and a mean average error of 1.165 for unseen data. The user-friendly software derived from this model facilitates the accurate prediction of thermal conductivity for a wide range of steels, providing a valuable source for industry professionals and researchers.

Thermophysical properties relevant to clathrate hydrate-based technologies were reviewed. Clathrate hydrates are solids composed of water and guests. The clathrate hydrate-based technologies considered in this study were as follows: carbon capture, utilization, and sequestration; natural gas storage and transportation; ozone storage and transportation; carbon dioxide clathrate hydrate as food; desalination and salt production; separation of tritiated water; cold thermal energy storage; and heat pumps and heat engines. The review was based on the experimentally measured data. The reviewed thermophysical properties were phase equilibrium conditions, formation/decomposition enthalpy, heat capacity, thermal conductivity, interfacial tension, and density. The phase equilibrium conditions determine the operating conditions for the clathrate hydrate-based technologies. The formation/decomposition enthalpy, heat capacity, and thermal conductivity relate to the thermal energy exchange during hydrate formation/decomposition. The interfacial tension is a key parameter when considering the multiphase flow composed of water and guests. The density influences the behavior of clathrate hydrates within the reactor. The relevance between these properties and the clathrate hydrate-based technologies was discussed. The methods correlating the phase equilibrium conditions were also compared in terms of applicability and usefulness. It was revealed that the suitability of the model, which is based on the Clausius–Clapeyron equation or statistical thermodynamic modeling, depends on the purpose of the correlation. Future perspectives of the thermophysical properties of clathrate hydrates were also discussed.

This work reports on the critical amplitudes of the thermodynamic properties of fluids, such as the specific heat, the coexistence-curve diameter, the susceptibility, the chemical potential, and the correlation length. These amplitudes are first determined from the crossover model and then correlated as a function of the acentric factor. A comparison with their values from the literature is also made. Finally, this work completes the critical amplitudes data of few fluids not reported in previous publications (Perkins et al., Int J Thermophys 34:191–212, 2013.https://doi.org/10.1007/s10765-013-1409-z ).

Currently, the properties of molten lithium, sodium and potassium fluoride eutectic mixtures with different additions are immensely important for the development of molten salt nuclear reactors. In the present work, the density of molten FLiNaK mixtures with additions of neodymium fluoride was studied by the Archimedean method. The neodymium fluoride addition increased the density of the 46.5 mol% LiF–11.5 mol % NaF–42.0 mol % KF (FLiNaK) and FLiNaK + 25 mol% NdF₃ mixture from 2.00 g⋅cm⁻³ to 3.25 g⋅cm⁻³, respectively. Thermal diffusivity was measured by the laser flash method. It was found to decrease abruptly as the NdF₃ concentration increased. Thermal conductivity of the FLiNaK–NdF₃ system, which was calculated using thermal diffusivity, density and heat capacity values, was lower than that of molten FLiNaK at the same temperature. The composition with 25 mol % NdF₃ (0.69 W⋅m⁻¹⋅K⁻¹) had a lower value of thermal conductivity than molten FLiNaK without additions (0.74 W⋅m⁻¹⋅K⁻¹) at the same temperature of at 973 K. It can be concluded that neodymium fluoride additions resulted in the density growth and decrease in the thermal diffusivity, heat capacity and thermal conductivity of molten FLiNaK. The change in the neodymium fluoride concentration can affect the technological process in nuclear reactor.

This paper is a combined experimental and modeling study aimed at exploring the densities, sound speeds, and refractive indices of the ternary system MTBE + n-hexane + cyclohexane and its binary subsystems at a temperature of 298.15 K under ambient pressure conditions. Experimental data were used to derive essential properties such as excess molar volumes, excess isentropic compressibilities, and refractive index deviations. The excess and deviation properties provided invaluable insights into the interactions occurring among the mixture components. Redlich–Kister and Cibulka's equations were employed to correlate these properties for binary and ternary systems, respectively. Remarkably, the standard deviations consistently fell below the estimated uncertainties associated with the corresponding properties, attesting to the robustness of the correlations. Additionally, the Perturbed Chain Statistical Associating Fluid Theory was applied to model the density of both binary and ternary mixtures. The study also compared Schaaff’s collision factor theory and Nomoto’s relation in their ability to predict sound speeds for the investigated mixtures. Various mixing rules, including Lorentz-Lorenz, Gladstone-Dale, Laplace, and Eykman, were employed to model the refractive indices of the mixtures. The efficacy of these models in predicting the properties was evaluated using the average absolute percentage deviation between the experimental and calculated values. The modeled densities matched well with the experimental data, with overall deviations of 0.19 %, 0.38 %, and 0.25 % for the binary systems MTBE + n-hexane, MTBE + cyclohexane, and n-hexane + cyclohexane, respectively, and 0.21 % for the ternary system MTBE + n-hexane + cyclohexane. Notably, Nomoto’s relation exhibited superior performance in predicting both binary (overall deviation of 0.65 %) and ternary (deviation of 1.10 %) sound speeds. In contrast, any of the four tested mixing rules performed equally well for predicting binary and ternary refractive indices. This work contributes to the understanding of interactions between components in mixtures. It also provides valuable data for petrochemical and environmental engineers involved in designing extraction processes, processing equipment, and formulating gasoline blends that meet the industry's rigorous standards and align with environmental sustainability goals.

Mass and thermodiffusion are transport phenomena in fluid mixtures important in many applications. In this paper it is argued that these transport phenomena have even become more interesting in view of some surprising discoveries from fluctuating hydrodynamics leading to possible new emerging issues in non-equilibrium thermodynamics. A short review of the history of this subject is presented. The paper then addresses the problem that the conventional mass and thermodiffusion coefficients depend on the frame of reference. A simple solution to this problem is elucidated.

A comprehensive discussion/analysis of the published viscosity data of ethylene glycol, EG, in the temperature range from 260 (just above the freezing point) to 465 K was recently reported in this journal. It was found that some of the reported data sets significantly deviate from each other, and the largest discrepancies were found at the lower end of the temperature interval examined (Mebelli et al. in Int. J. Thermophys. 42:116, 2021). Hence, in this work, the densities and viscosities of EG were measured in the temperature interval starting in the supercooled region at 248 and extending up to 313 K. Well-established experimental techniques were employed, that is, pycnometry and laminar flow viscometry, the relative precision of which were better than 0.5 and 0.5 %, respectively. The density was found to linearly depend on temperature in the temperature range studied; the cubic expansion coefficient was found to be γ = (5.20 + 3.99 × 10⁻³ T K^− 1) × 10⁻⁴ K⁻¹. When our experimental density data were applied to calculate the dynamic viscosity values using the correlation dependence published in the aforementioned review (Mebelli et al. in Int. J. Thermophys. 42:116, 2021), the discrepancy between our experimental data and the calculated values is less than 2 % above the freezing point; however, in the supercooled region, the discrepancy increases up to 4 % at 248 K. When the cooling rate is higher than 10 K min^− 1 and the sample mass is less than 5 mg, EG does not freeze; it undergoes glass formation (Tg =  − 121 °C) as revealed in our DSC experiments. The Arrhenius plot for viscosity data was found to be nonlinear; from the Angell plot, it was concluded that EG is a moderately fragile liquid with the fragility index = 70.