International Journal of Thermophysics最新文献

In the last years, studies have demonstrated the potential of hybrid nanofluids to enhance the performance of direct absorption solar collectors. These working fluids containing noble metals (gold, silver) are known for their local surface plasmon resonance which is the main cause for the increased absorption within the solar spectrum. In the current paper, new direct absorption solar collectors prototypes using water-ethylene glycol solution and 0.1 wt.% silver nanoparticles + reduced graphene oxide dispersed in water-ethylene glycol mixture were designed, built, and tested under outdoor conditions, at two flow rates (1.0 and 1.5 l·min⁻¹) and two inlet temperatures (20 (^circ{rm C}) and 30 (^circ{rm C})), over several days in September 2023, at Brasov, Romania. The results suggested that by using silver nanoparticles + reduced graphene oxide nanofluid, the efficiency is improved related to water-ethylene glycol solution. The maximum relative enhancement in efficiency was 16.72% related to the base fluid. Also, at 1.0 l·min⁻¹, the instantaneous and accumulative energies delivered were about 13.51% and 42.91%, respectively, higher than the water-ethylene glycol solution. Finally, the current results were compared to other research carried out on full-scale direct absorption solar collectors tested in outdoor conditions.

Ethylene glycols are a group of versatile industrial solvents with broad applications across various sectors. Accurate thermodynamic modeling of these compounds is essential for enhancing their utilization and optimizing industrial processes. Among the advanced models available, the Statistical Associating Fluid Theory (SAFT) type equation of state (EoS) stands out for its effectiveness in capturing the thermodynamic behavior of complex fluids. This study employs the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs to model pure monoethylene glycol (MEG), diethylene glycol (DEG), triethylene glycol (TEG), and their mixtures. Furthermore, the predictive capabilities of these models are critically evaluated for polyethylene glycol 400 (PEG 400). The performance of the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs was evaluated for predicting key thermodynamic properties, including density, thermal expansion coefficient, isothermal compressibility, isobaric heat capacity, speed of sound, and saturated vapor pressure, for pure MEG, DEG, TEG, and PEG 400. Among the models, the PρT-SAFT demonstrated superior accuracy in modeling their properties. Subsequently, the volumetric properties and vapor–liquid equilibrium data of binary mixtures of MEG, DEG, and TEG were predicted using the same EoSs, without incorporating any binary interaction parameters. Under these conditions, the PρT-SAFT achieved the highest accuracy. Furthermore, predictions of the volumetric properties for the ternary mixture of MEG, DEG, and TEG also indicated that the PρT-SAFT outperformed the other models. The overall average absolute deviation percentages for the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs across all examined thermodynamic properties and systems were 7.0, 8.2, 22.2, and 30.2, respectively, confirming the robustness of the PρT-SAFT.

According to the current fire regulations in Turkey, the use of insulation materials such as EPS, which are commonly employed in building insulation, is limited to buildings up to 28.5 m in height. The regulations mandate the use of Class A fire-resistant thermal insulation materials in high-rise buildings. However, these materials may present challenges in terms of application and sustainability. This study aims to develop a perlite-based thermal insulation board that is Class A fire-resistant, competitive with traditional insulation materials, and possesses optimal physical, mechanical, and thermal properties. In the production of the specimens, expanded perlite, liquid sodium silicate, and silicon powder were used, and tests for apparent density, compressive-flexural strength, capillary water absorption, and thermal conductivity were conducted in accordance with EN standards. In the first stage, the produced specimens were subjected to four different activation temperatures to determine the optimal process temperature. In the second stage, the ratios of perlite, sodium silicate, and water were varied to achieve the mixture design that yielded the highest mechanical properties from the specimens. In the final stage, water-repellent admixtures were incorporated into the batches at mass ratios of 1.5 %, 3 %, 4.5 %, and 6 %. The perlite-based thermal insulation board, which offers optimal properties in the most cost-effective manner, has an apparent density of 127 kg·m⁻³, compressive strength of 266 kPa, flexural strength of 156 kPa, capillary water absorption value of 0.0197 kg·m⁻²·min^−0.5, thermal conductivity of 0.0475 Wm⁻¹·K⁻¹, and a unit cost of 97 $ m⁻³. Consequently, the insulation board developed in this study presents a viable alternative to conventional insulation materials, offering Class A fire resistance.

For over a century, cubic equations of state (EoS) have been used to calculate density and phase equilibria of pure fluids and mixtures. Despite a century’s development with hundreds of resulting cubic EoS, their accuracy in liquid phase density calculations is still unsatisfactory. In this work, a new cubic EoS was developed to improve the accuracy of liquid phase density calculation while keeping similar accuracy of other properties. The new cubic EoS, named YFR (Yang-Frotscher-Richter) EoS, was developed based on the functional form of the Patel–Teja (PT) EoS [p = RT/(v − b) − a/(v(v + b) + c(v − b)]. In the PT EoS, parameters b and c are linked to an empirical critical compressibility factor ξ_c, and all these three parameters are constants for a pure fluid. By contrast, in the YFR EoS, ξ_c, b, and c are functions of temperature, and the equations describing this dependency were developed with symbolic regression. This is the key to improving liquid phase density calculation, although it leads to thermodynamic inconsistencies at high pressures. The application range of the new cubic EoS is thus limited to pressures up to 100 MPa. The YFR EoS was developed using nearly all pure fluids available in NIST’s REFPROP 10.0 database, with reference values computed with REFPROP. The average of the absolute value of relative deviations (AARD) of liquid phase densities calculated with the YFR EoS from reference values is approximately 2 %, compared to 3 % when using the Patel–Teja–Valderrama (PTV) EoS and 6 % when using the Peng-Robinson (PR) EoS. The YFR EoS has been implemented in our self-developed OilMixProp 1.0 software package.

Experimental densities and sound speeds at temperatures (293.15, 298.15, 303.15, and 313.15) K and under ambient pressure conditions are reported for the first time for the ternary system {MTBE + benzene + n-hexane} covering the entire composition range. The corresponding binary subsystems have also been studied. The excess molar volume and excess isentropic compressibility, derived from experimental density and sound speed data, were correlated using Redlich-Kister and Cibulka equations for binary and ternary systems, respectively. The composition and temperature dependence of these properties provided insights into the nature of molecular interactions and structural effects within the mixtures. The Perturbed Chain Statistical Associating Fluid Theory Equation of State was used to model the densities of both binary and ternary mixtures using a predictive approach. Schaaff’s Collision Factor Theory and Nomoto’s relation modeled the sound speeds. Further, this work utilized the Jouyban–Acree model to represent the composition and temperature dependence of experimental densities and sound speeds of the studied binary and ternary mixtures. Finally, the ternary excess properties are compared with the predicted values from binary contribution symmetric (Kohler and Muggianu) and asymmetric (Hillert and Toop) geometric models. The accuracy of the theoretical and empirical models was assessed by computing various statistical indicators.

The Ag₂S-Ag₈SiS₆-Ag₈SnS₆ system was studied using DTA/DSC, diffraction of X-ray, as well as SEM methods. The T-x phase diagram of the Ag₈SiS₆-Ag₈SnS₆ boundary system, several vertical and isothermal sections of the phase diagram, as well as a projection of the liquidus surface, were plotted, and the thermodynamic functions of polymorphic transitions of the Ag₈SiS₆ compound and Ag₈Si_1-xSn_xS₆ solid solutions were calculated. It was obtained that the Ag₈SiS₆-Ag₈SnS₆ boundary system is quasi-binary and is characterized by the formation of a continuous solid solutions during low-temperature orthorhombic and high-temperature cubic modifications of the initial compounds. It is shown that investigated system is a quasi-ternary plane of the Ag–Si–Sn–S concentration tetrahedron. The liquidus surface consists of two fields corresponding to the primary crystallization of high-temperature Ag₈Si_1-xSn_xS₆ solid solutions based on HT-Ag₂S. Below the solidus, phase transformations associated with the polymorphism of the initial compounds and phases based on them were observed. Based on DSC data, the temperatures, enthalpies, and entropies of phase transitions of the argyrodite phases from low-temperature orthorhombic modification to high-temperature cubic modification were calculated. It was determined that the heats and entropies of tranformations of above phases have anomalously high values ​​compared to ordinary polymorphic transitions. In addition, it was established that the entropies of phase transformations of solid solutions are practically equal to the sum of the corresponding functions of the original compounds. This indirectly indicates the quasi-ideality of solutions between both modifications of these compounds.

The present study represents a continuation of our investigations on the effective thermal conductivity λ_eff of nanofluids by systematically varying the types of base fluids and particles. For the spherical nanoparticles with mean diameters between (20 and 175) nm, the metal oxides silicon dioxide (SiO₂), titanium dioxide (TiO₂), and copper oxide (CuO) as well as the polymers polystyrene (PS) and polymethylmethacrylate (PMMA) were selected to cover a broad range for the particle thermal conductivity λ_p from about (0.1 to 30) W⋅m^–1⋅K^–1. The corresponding polar base fluids water, ethylene glycol, and glycerol allow to not only vary their thermal conductivity λ_bf by a factor of more than two, but also their dynamic viscosity by about three orders of magnitude. For the measurement of λ_eff of the twelve different particle–fluid combinations, i.e., TiO₂ or CuO with all three liquids as well as SiO₂, PS, or PMMA with water or ethylene glycol, a steady-state guarded parallel-plate instrument (GPPI) associated with an expanded (k = 2) relative uncertainty between 0.022 and 0.032 was used at atmospheric pressure over a temperature range from (283 to 358) K at varying particle volume fractions up to 0.31. The results for the thermal-conductivity ratio λ_eff·λ_bf^–1 are independent of temperature and show a moderate and relatively linear change as a function of the particle volume fraction. For similar ratios λ_p·λ_bf^–1, the experimental data for λ_eff·λ_bf^–1 are also very similar, which are above, close to, or below 1 if λ_p is larger than, comparable to, or smaller than λ_bf, respectively. For all nanofluids investigated, the Hamilton–Crosser model can describe the present measurement results and reliable experimental data reported in the literature for λ_eff·λ_bf^–1 typically within ± 5 %. Overall, the measurement results from this work contribute to an extension of the database for λ_eff of nanofluids with respect to the investigated wide ranges of systems, temperature, and particle volume fraction.

The paper presents a complete theory for a new method for the determination of the thermal diffusivity of a bulk solid in the form of a cylinder using a pulse of energy of finite duration delivered on one face and the subsequent temperature rise detected on a parallel face. It is an important feature of the method that the departure from equilibrium in the solid sample is small so that the temperature rise is no more than a few degrees Kelvin. The energy pulse may be of any temporal distribution and the detection of the temperature rise can be conducted at any point on the opposing face of the sample. The theory explicitly accounts for heat losses at all the surfaces of the sample and enables absolute measurement of the thermal diffusivity of the sample. A prototype instrument is described to realize this theory in which the heating pulse is generated by an array of light emitting diodes in a circular configuration which is then guided by a light pipe so that a uniform distribution is ensured across the flat face of the solid sample being tested. The instrument is designed for operation over the temperature range from ambient to 1300 K but, in the current proof of principle, measurements are conducted at room temperature on a sample of Pyroceram™ 9606.¹ In this case, the detection is performed with a micro-thermocouple at the center of the sample. Several different rectangular heating pulse durations are employed to show that the theory provides an appropriate description of the experiment. The potential for future applications of the technique is demonstrated.

The mathematical tool “Parametrical Identity Mapping (PIM)” is presented in detail. Its tasks are to effectively assists (1) in choosing the best form of a measurement model, e.g., for the transient hot-wire method and (2) in completely adjusting the selected model by two global correction factors. These factors control the amplitude and time-response of the adjusted model in a way that this form of the model optimally predicts the experimental data points. The goodness of the adjusted model can easily be determined by a simple statistic, the level of similarity, (R^{2} le 1). (R^{2}) is known as the coefficient of determination. Here, it describes the proportion of the variation in the observed values that is predictable from the estimated values. PIM is able to create an adjusted model of a level of similarity that comes very close to unity, (R^{2} approx 1).

This study introduces a novel method for calculating the thermal conductivity of graphene using a Monte Carlo approach to evaluate anisotropic three-phonon interactions. The phonon dispersion relation is derived using a force constant model that incorporates up to fifth-order nearest neighbor interactions, while the phonon density of states (DOS) is computed via a generalized Gilat–Raubenheimer method. A quantitative relationship for the scaling exponent of the specific heat capacity at low temperatures is established, emphasizing the unique two-dimensional characteristics of graphene. To address anisotropic effects, the Monte Carlo approach efficiently identifies three-phonon combinations that adhere to the conservation laws of energy and momentum. The findings highlight the pivotal role of anisotropic phonon interactions in graphene’s thermal conductivity. The thermal conductivity values obtained through the iterative method exhibit strong agreement with previous three-phonon calculations, thereby validating the model. Nevertheless, discrepancies with experimental data suggest that incorporating higher-order phonon processes, such as four-phonon scattering, may further improve predictive accuracy.