• 한국해양학회지
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• v.20 no.1
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• pp.22-30
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• 1985

The mean sea level(MSL) along the coast of Korea is high in summer and low in winter, mainly due to the inverse barometric effect and the steric departure. The MSL associated with the inverse barometric effect is spatially uniform and has an amplitude of 8.5$\pm$0.8cm. The thermal departure, with amplitude of 4~8cm, is most dominant in the Yellow Sea. The MSL in the South Sea of Korea is strongly affected by the haline departure, which has an amplitude up to 5cm. The annual range of MSL along the western and eastern coasts of Korea are about 40 and 20cm, respectively. The spatial inhomogeneity of the annual range of MSL arises mainly due to the influence of the Asian monsoon, which amplifies (weakens) the annual MSL along the western (eastern) coast of Korea.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.165-169
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• 2010

무선 센서 네트워크에서 LBS(Location Based Services) 에 적합한 기술적인 요구사항이 증가하고 있다. 최근 LBS의 가장 기본이 되는 위치추정(Localization) 에 관련하여 많은 알고리즘이 제안되고 있지만 센서 네트워크를 위한 요구사항을 만족하지 못하고 있다. 본 논문에서는 센서 네트워크에서 5가지 주된 위치추정방식의 요구사항을 정의하고 이를 만족하는 SCORE 알고리즘을 제안한다. 고정노드는 다중 파워의 비콘신호를 전승하게 되며, 이때 고정노드는 센서노드에게 위치정보를 비콘 신호에 담아서 전승하게 되는데 이때 다중 비콘신호에 신호 순서에 해당하는 SCORE 라고 고정노드로부터 센서노드까지의 거리에 대한 값을 포함하여서 전승하게 된다. 여러 고정노드로부터 수신한 위치정보를 수집한 센서노드는 간단한 연산과정을 거쳐 자신의 위치를 분산적으로 추정하게 된다. CAB 위치추정 알고리즘의 2 가지 알고리즘을 동시에 사용하는 복잡성 문제와 Diffusion 알고리즘의 네트워크 외곽에서 발생하는 큰 위치추정 오류의 문제점을 SCORE 알고리즘에서는 해결하였다. 시뮬레이션 결과 SCORE 알고리즘은 독립적인 알고리즘 사용임에도 불구하고 CAB 위치추정 알고리즘과 비슷한 성능을 나타내었으며, Diffusion 알고리즘에서 발생한 네트워크 외곽 센서노드들의 오류를 평균 7% 이상 향상 시켰다.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.915-924
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• 2016

After a severe accident to the nuclear reactor, the in-vessel retention strategy is a key way to prevent the leakage of radioactive material. Nanofluid is a steady suspension used to improve heat-transfer characteristics of working fluids, formed by adding solid particles with diameters below 100nm to the base fluids, and its thermal physical properties and heat-transfer characteristics are much different from the conventional working fluids. Thus, nanofluids with appropriate nanoparticle type and volume concentration can enhance the heat-transfer process. In this study, the moving particle semi-implicit method-meshless advection using flow-directional local grid method is used to simulate the bubble growth, departure, and sliding on the downward-facing heating surface in pure water and nanofluid (1.0 vol.% $Al_2O_3/H_2O$) flow boiling processes; additionally, the bubble critical departure angle and sliding characteristics and their influence are also investigated. The results indicate that the bubble in nanofluid departs from the heating surface more easily and the critical departure inclined angle of nanofluid is greater than that of pure water. In addition, the influence of nanofluid on bubble sliding is not significant compared with pure water.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.41-48
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• 2018

This paper describes the systems engineering development process for the Departure from Nucleate Boiling Ratio (DNBR) algorithm using FPGA. Current Core Protection Calculator System (CPCS) requirement and DNBR logic are analyzed in the reverse engineering phase and the new FPGA based DNBR algorithm is designed in the re-engineering phase. FPGA based DNBR algorithm is developed by VHSIC Hardware Description Language (VHDL) in the implementation phase and VHDL DNBR software is verified in the software Verification & Validation phase. Test cases are developed to perform the software module test for VHDL software modules. The APR 1400 simulator is used to collect the inputs data in 100%, 75%, and 50% reactor power condition. Test input signals are injected to the software modules following test case tables and output signals are compared with the expected test value. Minimum DNBR value from developed DNBR algorithm is validated by KEPCO E&C CPCS development facility. This paper summarizes the process to develop the FPGA-based DNBR calculation algorithm using systems engineering approach.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.25-31
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• 2019

As artificial intelligence technology has been developed rapidly, many researchers who are interested in next-generation vehicles have been studying on applying the artificial intelligence technology to advanced driver assistance systems (ADAS). In this paper, a method of applying deep learning algorithm to the lane departure warning system which is one of the main components of the ADAS was proposed. The performance of the proposed method was evaluated by taking a comparative experiments with the existing algorithm which is based on the line detection using image processing techniques. The experiments were carried out for two different driving situations with image databases for driving on a highway and on the urban streets. The experimental results showed that the proposed system has higher accuracy and precision than the existing method under both situations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.1-20
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• 2021

Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1269-1279
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• 2023

Pool boiling experiments are performed within an isolated bubble regime at inclination angles of 0° and 45°. When a bubble grows and departs from the heating surface, the pressure, buoyancy, and surface tension force play important roles. The curvature and base diameter are required to calculate the pressure force, the bubble volume is required to calculate the buoyancy force, and the contact angle and base diameter are required to calculate the surface tension force. The contact angle, base diameter, and volume of the bubbles are evaluated using images captured via a high-speed camera. The surface tension force equation proposed by Fritz is modified with the contact angles obtained in this study. When the bubble grows, the contact angle decreases slowly. However, when the bubble departs, the contact angle rapidly increases owing to necking. At an inclination angle of 0°, the contact angle is calculated as 82.88° at departure. Additionally, the advancing and receding contact angles are calculated as 70.25° and 82.28° at departure, respectively, at an inclination angle of 45°. The dynamic behaviors of bubble growth and departure are discussed with forces by pressure, buoyancy, and surface tension.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.182-189
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• 2015

Climate departure from the past variability was projected to start in 2042 for Seoul. In order to understand the implication of climate departure in Seoul for urban agriculture, we evaluated the daily temperature for the June-September period from 2041 to 2070, which were projected by the RCP8.5 climate scenario. These data were analyzed with respect to climate extremes and their effects on growth of hot pepper (Capsicum annuum), one of the major crops in urban farming. The mean daily maximum and minimum temperatures in 2041-2070 approached to the $90^{th}$ percentile in the past 30 years (1951-1980). However, the frequency of extreme events such as heat waves and tropical nights appeared to exceed the past variability. While the departure of mean temperature might begin in or after 2040, the climate departure in the sense of extreme weather events seems already in progress. When the climate scenario data were applied to the growth and development of hot pepper, the departures of both planting date and harvest date are expected to follow those of temperature. However, the maximum duration for hot pepper cultivation, which is the number of days between the first planting and the last harvest, seems to have already deviated from the past variability.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.143-155
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• 2009

A dynamic traffic assignment (DTA) has recently been implemented in many practical projects. The core of dynamic model is the inclusion of time scale. If excluding the time dimension from a DTA model, the framework of a DTA model is similar to that of static model. Similar to static model, with given exogenous travel demand, a DTA model loads vehicles on the network and finds an optimal solution satisfying a pre-defined route choice rule. In most DTA models, the departure pattern of given travel demand is predefined and assumed as a fixed pattern, although the departure pattern of driver is changeable depending on a network traffic condition. Especially, for morning peak commute where most drivers have their preferred arrival time, the departure time, therefore, should be modeled as an endogenous variable. In this paper, the authors point out some shortcomings of current DTA model and propose an alternative approach which could overcome the shortcomings of current DTA model. The authors substitute a traditional definition for time-dependent OD table by a new definition in which the time-dependent OD table is defined as arrival time-based one. In addition, the authors develop a new DTA model which is capable of finding an equilibrium departure pattern without the use of schedule delay functions. Three types of objective function for a new DTA framework are proposed, and the solution algorithms for the three objective functions are also explained.