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Differential equations are pivotal in modeling and understanding the dynamics of various systems, as they offer insights into their future states through parameter estimation fitted to time series data. In fields such as economy, politics, and biology, the observation data points in the time series are often independently obtained (i.e., Repeated Cross-Sectional (RCS) data). RCS data showed that traditional methods for parameter estimation in differential equations, such as using mean values of RCS data over time, Gaussian Process-based trajectory generation, and Bayesian-based methods, have limitations in estimating the shape of parameter distributions, leading to a significant loss of data information. To address this issue, this study proposes a novel method called Estimation of Parameter Distribution (EPD) that provides accurate distribution of parameters without loss of data information. EPD operates in three main steps: generating synthetic time trajectories by randomly selecting observed values at each time point, estimating parameters of a differential equation that minimizes the discrepancy between these trajectories and the true solution of the equation, and selecting the parameters depending on the scale of discrepancy. We then evaluated the performance of EPD across several models, including exponential growth, logistic population models, and target cell-limited models with delayed virus production, thereby demonstrating the ability of the proposed method in capturing the shape of parameter distributions. Furthermore, we applied EPD to real-world datasets, capturing various shapes of parameter distributions over a normal distribution. These results address the heterogeneity within systems, marking a substantial progression in accurately modeling systems using RCS data. Therefore, EPD marks a significant advancement in accurately modeling systems with RCS data, realizing a deeper understanding of system dynamics and parameter variability.

The prediction of radio signal transmission in tunnels is important for wireless communication link design as it enables the delivery of optimum power to the intended receiver inside the tunnel. Several techniques have been proposed to estimate path loss for wireless communication inside tunnels. The radio coverage range and where base stations need to be installed can be figured out with the help of propagation models. At the time of developing these models, modeling complexity and environmental attributes, such as the tunnel geometry and the electrical and magnetic properties of its walls and interior materials are considered. A limited amount of literature currently overviews how waves transmits through tunnels and how electromagnetic wave transmission has recently changed. This survey, which examines current advancements in the propagation of waves in tunnels, aims to address this gap. In this review, thirty wave propagation models were analyzed and grouped into distinct categories for the first time. The detailed specifications of each model were omitted to make the survey easy to comprehend. This comparative research will help service providers adopt an appropriate propagation model and plan efficient transmitter and receiver placement and link management for a specific tunnel environment.

Since liquefied natural gas (LNG) is imported in a liquid state of about -162℃ to increase transportation efficiency in Korea, it must be vaporized in a gaseous state to supply it to consumers. Among them, ambient air vaporizer (AAV) has caught attention due to eco-friendly and low costs characteristics. However, there is a disadvantage that the performance of the heat exchanger is deteriorated due to frost due to mist and icing when used for a long time. In this paper, frost generation model in AAV vaporizer was investigated with numerically to examine utilizing the vaporizer performance with the frost generation behavior. The frost generation behavior of AAV vaporizers was examined with humidity, fin characteristic, and temperature effects. As for the LNG discharge temperature, the 12 fin vaporizer showed the highest discharge temperature when the atmospheric temperature was 25℃, and the 8 fin vaporizer had the lowest LNG discharge temperature when the atmospheric temperature was 0℃. In the case of frost formation, in the case of the 12 fin vaporizer, it was formed the most at the atmospheric temperature of 25℃, and the least was formed in the vaporizer at the 0℃ condition of the atmospheric temperature of 8 fins.

Due to the low density of hydrogen gas under ambient temperature and atmospheric pressure conditions, the high-pressure gaseous hydrogen storage method is widely employed. With high-pressure characteristics of hydrogen storage, rigorous safety precautions are required, such as filling of compressed gas in a hydrogen tank to achieve reliable operational solutions. Especially for the large-sized tanks (above 150 L), safety operation of hydrogen storage should be considered. In the present study, the compressed hydrogen gas behavior in a large hydrogen tank of 175 L is investigated for its filling. To validate the numerical approach used in this study, numerical models for the adaptation of the gas and turbulence models are examined. Numerical parametric studies on hydrogen filling for the large hydrogen tank of 175 L are conducted to estimate the hydrogen gas behavior in the hydrogen tank under various conditions of state of charge of pressure and ambient temperature. From the parametric studies, the relationship between the initial SOC pressure condition and the maximum temperature rise of hydrogen gas was shown. That is, the maximum temperature rise increases as the ambient temperature decreases, and the rise increases as the SOC decreases.

In the present study, the flow characteristics of butterfly valves with different sizes DN 80 (nominal diameter: 76.2 mm), DN 262 (nominal diameter: 254 mm), DN 400 (nominal diameter: 406 mm) were numerically investigated under different valve opening percentages. Representative two-equation turbulence models of two-equation k-epsilon model of Launder and Sharma, two-equation k-omega model of Wilcox, and two-equation k-omega SST model of Menter were selected. Flow characteristics of butterfly valves were examined to determine turbulence model effects. It was determined that increasing turbulence effect could cause many discrepancies between turbulence models, especially in areas with large pressure drop and velocity increase. In addition, sensitivity analysis of flow properties was conducted to determine the effect of constants used in each turbulence model. It was observed that the most sensitive flow properties were turbulence dissipation rate (Epsilon) for the k-epsilon turbulence model and turbulence specific dissipation rate (Omega) for the k-omega turbulence model.

With the rapid development of high-performance fibers such as carbon, enhanced glass fibers in structural applications, the use of fiber-reinforced composite (FRC) materials has also increased in many areas. Liquid composite molding (LCM) is a widely used manufacturing process in composite manufacturing; however, the rapid impregnation of resin in the reinforcing fibers during processing poses a significant issue. The optimization of resin impregnation is related to tow deformations in the reinforcing fibers. The present study therefore focuses on this tow deformation. The permeability behaviors in double-scale porous media were observed under different flow rates and viscosity conditions to examine the overall tendencies of structural changes in the reinforcement. The permeability results showed hysteresis with increasing and decreasing flow rate conditions of 50–800 mm3/s, indicating structural changes in the reinforcement. The tow behaviors of the double-scale porous media with respect to the thickness and flow rate were investigated in terms of the representative indices of the minor axis (tow thickness) and major axis. The minor axis and major axis of the tow showed decreasing and increasing trends of 2–5% and 2%, respectively, with minimum and maximum values at different positions along the reinforcement, affected by the different hydrodynamic entry lengths. Finally, the deformed tow behavior was observed microscopically to examine the behavior of the tow at different flow rates.

The high-pressure gaseous hydrogen (HPGH2) storage method is widely used owing to the low density of hydrogen gas at ambient temperature and atmospheric pressure. Therefore, rigorous safety analysis of the filling and discharging of compressed gas in a hydrogen tank is required to achieve reliable operational solutions for the safe storage of hydrogen. In this study, the behavior of compressed hydrogen gas in a hydrogen tank was investigated for its discharge. Numerical models for the adaptation of gas and turbulence models were examined. Gas model effects were examined to account for hydrogen gas behavior at the discharge temperature and pressure conditions. Turbulence model effects were analyzed to consider the accuracy of each model: the assessment of the turbulence models was compared in terms of the turbulence intensity. From the study of gas model effect, the Redlich–Kwong equation was found to be one of the realistic gas models of the discharging gas flow. Among the turbulence models, the shear stress transport model and Reynolds stress model predicted the compressed gas behavior more accurately, showing a lower turbulence intensity than those of the realizable and renormalization group models.