• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.10 no.3
• /
• pp.271-281
• /
• 1998

In this study, condensation heat transfer experiments were conducted with two small diameter(ø7.5, ø4.0) tubes. Comparison with existing in-tube condensation heat transfer correlations indicated that the correlations overpredict the present data. For example, Akers correlation overpredicts the data upto 104%. The condensation heat transfer coefficient of the ø4.0 I.D. tube was smaller than that of the ø7.5 I.D tube; at the mass velocity of 300kg/$m^2$s, the difference was 12%. The pressure drop data of the small diameter tubes ware highly(two to six times) overpredicted by the Lockhart-Martinelli correlation. Subcooled forced convection heat transfer test confirmed that Gnielinski's single phase heat transfer correlation predicted the data reasonably well.

• Nuclear Engineering and Technology
• /
• v.36 no.5
• /
• pp.460-474
• /
• 2004

Effects of liquid subcooling on pool boiling heat transfer in an annulus with an open bottom have been investigated experimentally. A tube of 19.1mm diameter and the water at atmospheric pressure have been used for the fest. Up to $50^{\circ}C$ of liquid subcooling has been tested and experimental data of the annulus have been compared with the data of a single unrestricted tube. Temperatures on the heated tube surface fluctuate only slightly regardless of the heat flux in the annulus, whereas high variation is observed on the surface of the single tube. An increase in the degree of subcooling decreases heat transfer coefficients greatly both for the single tube and the annulus. Heat transfer coefficients increase suddenly at ${\Delta}T_{sub}\;{\le}\;10^{\circ}C$ and much greater change in heat transfer coefficients is observed at the annulus. To obtain effects of subcooling on heat transfer quantitatively, two new empirical equations have been suggested, and the correlations predict the empirical data within ${\pm}30\%$ error bound excluding some data at lower heat transfer coefficients.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.2
• /
• pp.58-71
• /
• 2021

The number of elderly people worldwide is rapidly increasing and the mobility handicapped suffering from inconvenient public transportation service is also increasing. In Korea and abroad, various policies are being implemented to provide high-quality transportation services for the mobility handicapped, and budget support and investment related to mobility facilities are being expanded. The mobility handicapped spends more time for transit transfer than normal users and their satisfaction with transit service is also lower. There exist transfer inconvenience points of the mobility handicapped due to various factors such as long transfer distances, absence of transportation facilities like elevators, escalators, etc. The purpose of this study is to find transfer inconvenience points for convenient transit transfer of the mobility handicapped using Smart card Big data. This study process traffic card transaction data and construct transfer travel data by user groups using smart card big data and analysis of the transfer characteristics for each user group ; normal, children, elderly, etc. Finally, find transfer inconveniences points by comparing transfer patterns between normal users and the mobility handicapped. This study is significant in that it can find transfer inconvenience points for convenient transit transfer of the mobility handicapped using Smart card Big data. In addition, it can be applicated of Smart card Big data for developing public transportation polices in the future. It is expected that the result of this study be used to improve the accessibility of transit transportation for mobility handicapped.

• Journal of Information Processing Systems
• /
• v.4 no.4
• /
• pp.133-144
• /
• 2008

Clusters have become a popular alternative for building high-performance parallel computing systems. Today's high-performance system area network (SAN) protocols such as VIA and IBA significantly reduce user-to-user communication latency by implementing protocol stacks outside of operating system kernel. However, emerging parallel applications require a significant improvement in communication latency. Since the time required for transferring data between host memory and network interface (NI) make up a large portion of overall communication latency, the reduction of data transfer time is crucial for achieving low-latency communication. In this paper, Eager Data Transfer (EDT) mechanism is proposed to reduce the time for data transfers between the host and network interface. The EDT employs cache coherence interface hardware to directly transfer data between the host and NI. An EDT-based network interface was modeled and simulated on the Linux-based, complete system simulation environment, Linux/SimOS. Our simulation results show that the EDT approach significantly reduces the data transfer time compared to DMA-based approaches. The EDTbased NI attains 17% to 38% reduction in user-to-user message time compared to the cache-coherent DMA-based NIs for a range of message sizes (64 bytes${\sim}$4 Kbytes) in a SAN environment.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.1699-1706
• /
• 2011

This study analyzed the level of service on passenger transfer between metro and bus based on transit smart card data obtained in 2010. In order to evaluate the level of service on transfer, we defined the service level specially on transfer time at metro stations. The data of passenger transfer time were used in cluster analysis to classify the service level from A to F. The results show that the average transfer time from metro to bus was 6.45 minutes. The number of stations with level of service A(approximately less than 7 minutes) and B(less than 16minutes) were found to be 215 and 227stations respectively. Also, the number of stations with the level of service C and D (greater than 20 minutes for transfer) were found to be 6 stations where any type of improvement on transfer facilities is required.

• International Journal of Air-Conditioning and Refrigeration
• /
• v.7
• /
• pp.45-54
• /
• 1999

In this study, condensation heat transfer experiments were conducted in two small diameter (ø17.5, ø4.0) tubes. Comparison with the existing in-tube condensation heat transfer correlations indicated that these correlations over predict the present data. For example, Akers correlation over predicted the data up to 104 %. The condensation heat transfer coefficient of the ø4.0 I.D. tube was smaller than that of the ø7.5 I.D tube; at the mass velocity of 300 kg/$m^2$s, the difference was 12 %. The pressure drop data of the small diameter tubes were highly (two to six times) over predicted by the Lockhart-Martinelli correlation. Sub-cooled forced convection heat transfer test confirmed that Gnielinski's single phase heat transfer correlation predicted the data reasonably well.

• Journal of Korean Society of Water and Wastewater
• /
• v.10 no.2
• /
• pp.88-103
• /
• 1996

The objective of this study is to develop stochastic and deterministic models which could be used to synthesize water application time series. Adaptive models using mulitivariate ARIMA(Transfer Function Model) are developed for daily urban water use forecasting. The model considers several variables on which water demands is dependent. The dynamic response of water demands to several factors(e.g. weekday, average temperature, minimum temperature, maximum temperature, humidity, cloudiness, rainfall) are characterized in the model by transfer functions. Daily water use data of Kumi city in 1992 are employed for model parameter estimation. Meteorological data of Seonsan station are utilized to input variables because Kumi has no records about the meteorological factor data.To determine the main factors influencing water use, autocorrelogram and cross correlogram analysis are performed. Through the identification, parameter estimation, and diagnostic checking of tentative model, final transfer function models by each month are established. The simulation output by transfer function models are compared to a historical data and shows the good agreement.

• Proceedings of the KSR Conference
• /
• 2001.05a
• /
• pp.36-43
• /
• 2001

Although the transferring is one of the most important factors in urban railways, there is very little analytic research in the transfer-related field. This paper analyses the transfer rate of urban railways in the Seoul Metropolitan Area and the actual passenger boardings and alightings at transfer stations using the AFC(Automatic Fare Collector) O/D data collected doling Sep. 2000. According to the results of this study the transfer rate is 0.657, which is calculated from the transfer hoardings/initial boardings. And the actual ridership of Subway Line 2 and Line 5 are different from the data which was provided by the AFC.

• Journal of KIISE:Software and Applications
• /
• v.35 no.5
• /
• pp.281-287
• /
• 2008

Data transfers occur during the execution time of a Java program, from constant to variable, from variable to other variable and so on. Data are located in memory and hence data transfer requires access to memory. As memory access generates both time delay and energy consumption it is absolutely necessary to know the data transfer overheads incurred among different paths not only to write an efficient program but also to build a high-performance Java virtual machine. In this paper we classify Java memory into three different regions, constant, local variable, and field, and then investigate data transfer overheads among these regions. The result says that the transfer between local variables incur the least overhead usually, while the transfer between fields incur the most. The difference of overheads reaches up to a double. Optimization techniques like JIT reduces the data transfer overhead dramatically. It is observed that the overhead is reduced from 14 to 27 times for the case of Hotspot JVM.

• Nuclear Engineering and Technology
• /
• v.55 no.11
• /
• pp.4102-4111
• /
• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.