A new regularity for internal pressure has been introduced based on the suggested potential energy function in liquid bismuth. Both the experimental data and the calculated quantities from the power law equation of state have been used to show the validity of the regularity. The quantity X3Z−1 is a linear function of ln(X) with crossing points for all isotherms at high temperature, where X=VVm0, V, Vm0, and Z are molar volume, the molar volume at melting point and zero pressure, and compressibility factor. For the reduced isothermal bulk modulus B*=BTVRT and the quantity Zint=PintVRT, where BT, R, T and Pint are isothermal bulk modulus, the gas constant, temperature and internal pressure, the new regularities have been introduced that both calculated X3B*−1 and X3Zint from the equation of state of a power law form versus ln(X) are nearly linear along each isotherm. However, those derived values from experiments become nonlinear functions of ln(X) at large pressure for all isotherms. Based on the new equation of state, analytical expression of thermodynamic properties of liquid bismuth can be obtained. The different extreme values exist along the isotherms for the calculated internal energy, isobaric heat capacity, and isochoric heat capacity for the new equation of state and the power law form equation of state.
The primary methods for hydrogen transportation include gaseous storage and transport, liquid hydrogen storage, and transport via organic liquid carriers. Among these, pipeline transportation offers the lowest cost and the greatest potential for large-scale, long-distance transport. Although the construction and operation costs of dedicated hydrogen pipelines are relatively high, blending hydrogen into existing natural gas networks presents a viable alternative. This approach allows hydrogen to be transported to the end-users, where it can be either separated for use or directly combusted, thereby reducing hydrogen transport costs. This study, based on the GERG-2008 equation of state, conducts experimental tests on the compressibility factor of hydrogen-doped natural gas mixtures across a temperature range of −10 °C to 110 °C and a pressure range of 2 to 12 MPa, with hydrogen blending ratios of 5%, 10%, 20%, 30%, and 40%. The results indicate that the hydrogen blending ratio, temperature, and pressure significantly affect the compressibility factor, particularly under low-temperature and high-pressure conditions, where an increase in the hydrogen blending ratio leads to a notable rise in the compressibility factor. These findings have substantial implications for the practical design of hydrogen-enriched natural gas pipelines, as changes in the compressibility factor directly impact pipeline operational parameters, compressor characteristics, and other system performance aspects. Specifically, the introduction of hydrogen alters the compressibility factor of the transported medium, thereby affecting the pipeline’s flowability and compressibility, which are crucial for optimizing and applying the performance of hydrogen-enriched natural gas in transportation channels. The research outcomes provide valuable insights for understanding combustion reactions, adjusting pipeline operational parameters, and compressor performance characteristics, facilitating more precise decision-making in the design and operation of hydrogen-enriched natural gas pipelines.
Abstract Tongluo-Qutong rubber plaster (TQRP), a typical Chinese patent medicine that contains 13 different herbal remedies, is widely used in clinical practice for the treatment of cervical spondylosis and osteoarthritis. However, due to a lack of in vitro transdermal studies, the active ingredients of TQRP have not been fully elucidated. This presents a huge obstacle for quality evaluation, pharmacokinetic studies and clinical safety assessment of TQRP. In this work, a UPLC/UV/MS/MS method was established and validated to evaluate five analytes in TQRP. The validation demonstrated linearity (r > 0.99), specificity (no co-eluting peaks at the retention times of the analytes), and precision (RSD < 15%) within acceptable parameters. A skin permeation study was performed to determine the concentrations of drugs delivered to the dermis. The 24-hour cumulative permeation of ferulic acid, aleo-emodin, emodin and piperine were 303.68, 709.31, 671.06 and 25561.01 ng/cm2, respectively. According to the fitting data of the TQRP active components, skin permeation was mainly due to a combination of passive diffusion and drug release after matrix erosion.
Earthquakes are the most dangerous natural disasters, and scholars try to predict them to protect lives and property. Recently, a long-term statistical analysis based on a “heating core” filter was applied to explore thermal anomalies related to earthquakes; however, some gaps are still present. Specifically, (1) whether there are differences in thermal anomalies generated by earthquakes of different magnitudes has not yet been discussed; and (2) thermal anomalies in high-spatial-resolution data are often distributed in spots, which is not convenient for statistics of thermal anomalies. To address these issues, in this study, we applied high-spatial-resolution thermal infrared data to explore the performance of the “heating core” for earthquake prediction at different magnitudes (i.e., 3, 3.5, 4, 4.5, and 5). The specific steps were as follows: first, the resampling and moving-window methods were applied to reduce the spatial resolution of the dataset and extract the suspected thermal anomalies; second, the “heating core” filter was used to eliminate thermal noise unrelated to the seismic activity in order to identify potential thermal anomalies; third, the time–distance–magnitude (TDM) windows were used to establish the correspondence between earthquakes and thermal anomalies; finally, the new 3D error diagram (false discovery rate, false negative rate, and space–time correlation window) and the significance test method were applied to investigate the performance under each minimum magnitude with training data, and the robustness was validated using a test dataset. The results show that the following: (1) there is no obvious difference in the thermal anomalies produced by earthquakes of different magnitudes under the conditions of a “heating core”, and (2) the best model with a “heating core” can predict earthquakes effectively within 200 km and within 20 days of thermal anomalies’ appearance. The binary prediction model with a “heating core” based on thermal infrared anomalies can provide some reference for earthquake prediction.
Seismo-induced Thermal infrared (TIR) anomalies has been proposed as a significant precursor of earthquakes. Several methods have been proposed to detect Thermal infrared anomalies that may be associated with earthquakes. However, there is no comparison of the influence for Thermal infrared extraction methods with a long time statistical analysis. To quantify the effects of various techniques used in Thermal infrared anomaly extraction, in this paper, we offer a complete workflow of their comparative impacts. This study was divided into three parts: anomaly detection, statistical analysis, and tectonic factor research. For anomaly detection, daily continuous nighttime surface temperature (ConLST) data was obtained from the Google Earth Engine (GEE) platform, and each different anomaly detection method was used to detect Thermal infrared outliers in the Sichuan region (27°-37°N, 97°-107°E). During statistical analysis, The heated core model was applied to explore Thermal infrared anomalies which is to filter anomalies unrelated to earthquakes by setting time-space-intensity conditions. The 3D error diagram offers scores to assume the best parameter set using training-test-validation steps. In the final part, we considered information on stresses, active faults, and seismic zones to determine the optimal parameters for extracting the Thermal infrared anomalies. The Kalman filter method detected the highest seismic anomaly frequency without considerating the heating core condition. The Autoencoder and Isolation Forest methods obtain the optimal alert type and parameter set to determine if the anomaly is likely earthquake-related. The RST method performs optimally in the final part of the workflow when it considers physical factors such as active faults, seismic zones, and stresses. However, The six methods we have chosen are not sufficient to contain the entire Thermal infrared anomaly extraction. The consideration of tectonic factors in the research remains poorly developed, as statistical methods were not employed to explore the role of constructive factors. Nevertheless, it is a significant factor in comparing anomaly extraction methods and precursor studies.
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