International Journal of Thermophysics最新文献

CO₂-based binary mixtures offer superior thermodynamic advantages and environmental benefits compared to alternative working fluids. Enthalpy and entropy are essential in thermodynamic analysis, necessitating the availability of vapor–liquid equilibrium data. The static thermostatic analysis system accurately measures the mixtures’ temperature, pressure, and molar fractions. We carry out five temperatures at 283.15 K to 323.15 K while maintaining a pressure of approximately 6.38 MPa. Two electromagnetic capillary samplers effectively extract working fluids from the equilibrium cell, facilitating precise analysis using a gas chromatograph. The standard measurement uncertainties of experimental temperature, mole fractions, and pressure are determined at 0.06 K, 0.004, and 0.002 MPa, ensuring precise and reliable data for our analysis. The experimental data we gathered has undergone extensive analysis and modeling using the PR + WS + NRTL model to offer a comprehensive insight into the system's behavior. The AARDp value is 0.81%, whereas AADy₁ demonstrates merely a slight variance of 0.0047. The relative volatility is determined at five temperatures ranging from 283.15 K to 323.15 K. The majority of the experimental data falls within the ± 5% deviation boundary, affirming their reliability.

This study aimed to accurately measure the density (ρ), normal spectral emissivity (ε), heat capacity at constant pressure (C_p), and thermal conductivity (κ) of the Ti–6 mass % Al–4 mass % V (Ti64) melt by electromagnetic levitation with a static magnetic field and laser modulation calorimetry. A static magnetic field was applied to the levitated Ti64 melt to suppress the surface oscillation and translational motion of the droplets, and to suppress the convection flow inside the droplet for each property measurement, as needed. The measurement uncertainty was analyzed for all of the thermophysical property data. The excess volume and excess heat capacity of the Ti64 melt obtained in this study were compared with those evaluated using the ideal solution model. The contribution of the thermal vibrations of the atoms in κ for the Ti64 melt was evaluated from the difference between the measured thermal conductivity (κ) value and the κ values calculated using the Wiedemann–Franz law.

In this paper, based on the principle of the Burnett isothermal expansion method, the P-ρ-T data for the R1216/R1234ze(E) mixture, with molar fractions of R1216 at 0.330, 0.564, and 0.786, were measured using a high-precision PVT test bench over a temperature range of 303.15 K to 333.15 K and a pressure range of 0.1 MPa to 1.7 MPa. The uncertainties in the experimental measurements are estimated to be within ± 1.4 kPa for pressure, ± 15 mK for temperature, and ± 0.2 % for molar fraction. Based on the experimental data, the relationship between the second and third Virial coefficients of the mixture R1216 / R1234ze(E) and temperature is fitted, and the Virial equation of state that can realize the high-precision calculations of the fundamental thermal properties of the gas phase of the mixture is obtained. The maximum relative deviation between the pressure values calculated by this equation and the experimental data is only 0.9 %, which verifies the accuracy and reliability of the Virial equation of state for calculating the basic thermophysical properties of R1216/R1234ze(E). This study provides detailed experimental data and reliable computational models for the thermodynamic performance of the new mixed refrigerant, as well as for other application studies.

A thermal diode is a component that allows heat flow in one direction while opposing it in the opposite direction. Its applications are wide, for example, it has recently been used for solar energy harvesting and in solar thermal technologies. This work studies a coating made with biomass soot and pine resin, which absorbs and stores captured energy with a preferential heat flow system. The research consists of 3 stages: (a) evaluating the thermal conductivity of soot through experimental arrangements with simple materials and equipment, (b) estimating the thermal rectification of the coating, and (c) applying the soot as a thermal diode in a small-scale system. The results show thermal conductivity values from 0.070 W·mK⁻¹ to 0.095 W·mK⁻¹ for the soot-resin coating, while the rectification factor was 21 % and 53 % for the best coating of 30 % soot–70 % pine resin and the double layer with 10 % soot and 90 % resin, respectively. The soot coating in a small-scale system showed thermal rectification associated with energy charging and discharging, with energy collection efficiency of 34 % and retention efficiency of 17 %. Compared to low-cost paint used in solar technologies, 31.4 % collection efficiency and 8.4 % retention efficiency were achieved. The coating is low-cost, environmentally friendly, and easy to reproduce, showing promise for use in low-power solar thermal technologies, to increase energy storage capacity as a thermal diode.

In this study, a method employing lock-in thermography is proposed for measuring the thermal diffusivity distribution of materials with high thermal conductivity. In this method, the thermal response distribution induced by periodic laser heating is analyzed, and the thermal diffusivity in the out-of-plane direction over the material surface is mapped. An undersampling method is applied during lock-in thermography to measure the thermal diffusivity distribution of materials with low thermal resistance at high frequencies. Additionally, a principle is developed to eliminate the inherent phase lag generated by the measurement system. The accuracy of the proposed method is validated by quantitatively measuring the thermal diffusivity of a pure copper sheet that exhibits an isotropic thermal diffusivity distribution. Results reveal that its average thermal diffusivity agreed with the reference value within + 2.4 %. The proposed method is also used to measure the thermal diffusivity of an isotropic graphite sheet with an inhomogeneous thermal diffusivity distribution. Results reveal that its average thermal diffusivity agreed with the reference value within + 7.0 %, and local areas with high thermal diffusivity are successfully visualized.

In various engineering applications, particularly pumping systems, two-phase flows that involve the simultaneous flow of two different states of matter are widely employed. For instance, in industrial settings, the utilization of an airlift pump is common for transferring air or other gases to lift liquid. Conversely, in diffusion-absorption refrigeration cycles, a bubble pump is employed to create a two-phase flow through fluid boiling. To comprehend the impact of design and operational parameters on the lift water bubble pump, a comprehensive theoretical study was undertaken. The engineering equation solver (EES) was utilized in this investigation to examine the influence of lift pipe diameter, heat flux, and mass flux on the performance of the bubble pump. The study’s findings revealed that a single set of optimal conditions and values cannot be universally applicable to the bubble pump. This is because each system possesses unique characteristics and operational parameters, leading to a distinct set of optimized parameters. The theoretical study on the lift water bubble pump underscores the significance of considering design and operational parameters while developing and operating pumping systems that employ two-phase flow. Moreover, it emphasizes the necessity for extensive research to establish optimal conditions and values tailored to the specific characteristics and operating parameters of each individual system.

The present paper reports the full range Joule–Thomson inversion curves of two helium isotopologues, ⁴He and ³He, constructed by the density virial equation of state with state-of-the-art theoretical virial coefficients. The peak temperatures and the peak pressures were determined to be 20.45 K and 3.715 MPa for ⁴He, and 18.57 K and 2.456 MPa for ³He. The maximum inversion temperatures at zero pressure were determined to be 44.72 K for ⁴He and 38.80 K for ³He, which are identical with the expected values from the second virial coefficients. The present full range inversion curves were improved compared to the previous ones especially in their higher temperature branches, and hence they are the most reliable at the point in time.

The thermodynamic behavior of glycolic and lactobionic acids in aqueous sodium benzoate solution provides an understanding of the nature of interactions with such systems. The experimental investigation involved measuring the density, denoted by ‘ρ,’ as well as the sound speed, represented by ‘c.’ Ultrasonic and volumetric characteristics for the liquid system (Sodium Benzoate + Water + Glycolic Acid/Lactobionic Acid) are investigated throughout a range of potassium benzoate concentrations (0.1, 0.4, 0.7) mol‧kg⁻¹ at a fixed pressure and several temperatures. The investigational values of densities and sound velocities were utilized to calculate various parameters, including apparent and partial molar characteristics, transfer parameters, expansibilities, temperature-dependent derivatives, and the coefficient of thermal expansibility. The findings are interpreted by examining the interactions occurring within the liquid system, using the co-sphere overlap approach as a theoretical framework. Thermodynamic parameters are employed to analyze interaction coefficients, which provide an understanding of the interactions between components in the ternary liquid combinations.

This work presents new measurements of the vapor pressure of trans-1,2-dichloroethene [R1130(E)], which is a promising refrigerant for the next-generation refrigeration systems. Due to the inconsistency among currently available vapor pressure data, additional experimental data are needed to develop a Helmholtz energy equation of state. The data obtained in this work were verified using a correlation based on the corresponding states principle. Comparisons with several representative experimental data identified those that are consistent with the present measurements.

This study is significant as it introduces an innovative approach to improving cancer drug delivery. It integrates machine learning algorithms, potentially revolutionizing treatment precision and efficiency. The study investigates nanoparticles modeled using a Levenberg–Marquardt neural network (LM-NN). These nanoparticles can act as dual-function agents to enhance drug delivery to tumors and reduce harmful hydrogen peroxide levels in the bloodstream. The research methodology includes modeling blood flow as pulsatile within a parallel plate channel. It also incorporates porous media to simulate foamy structures. The study addresses heat transfer dynamics and chemically reactive species. It uses nanoparticle concentration equations that account for diffusion, convection, and chemical reaction processes. The study concludes that combining machine learning with fluid dynamics modeling greatly improves the understanding of drug delivery efficiency. It also highlights its impact on physiological factors. Heat transfer, Reynolds number, and parameters like Darcy and Forchheimer are vital for optimizing the delivery of therapeutic agents. Magnetic fields and Schmidt numbers are crucial for regulating blood flow and enhancing treatment outcomes. These insights could lead to improved treatment protocols and better management of blood flow within the cardiovascular system, particularly in areas targeted for cancer treatment. By optimizing drug delivery to cancer tissues, this approach could potentially lower side effects through more controlled and efficient targeting of therapeutic agents. Additionally, the research emphasizes the critical role of computational models in refining drug delivery strategies, offering a pathway toward more personalized and effective cancer treatment protocols in the future.