• Journal of the Korean Geotechnical Society
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• v.32 no.4
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• pp.15-27
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• 2016

This study was conducted to suggest a landslide triggering rainfall threshold (ID curve) for landslide prediction by considering the effect of antecedent rainfall. 202 rainfall data including domestic landslide and rainfall records were used in this study. In order to consider the effect of antecedent rainfall, rainfall data were analyzed by changing Inter Event Time Definition (IETD) and IETD based ID curve were presented by regression analysis. Compared to the findings of the previous studies, the presented ID curve has a tendency to predict the landslides occurring at a relatively low rainfall intensity. It is shown that the proposed ID curve is appropriate and realistic for predicting landslides through the validation of proposed ID curve using records of landslides in 2014. Based on this analysis, it is found that the longer IETD, the greater the effect of antecedent rainfall, and the steeper the gradient of ID curve. It is also found that the rainfall threshold (intensity) is higher for the short period rainfall and lower for the long period rainfall.

• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.45-53
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• 2012

In this paper, oil spreading simulation model is proposed for analyzing the oil spreading phenomenon rapidly when the ocean is polluted by the oil from a stranded ship. The space occupied by the ocean is converted into the latticed cell, and the each cell contains the information, such as the quantity of the oil, the temperature of the ocean, and the direction of current and wind. Two states, such as "clean" and "polluted" are defined in the each cell, and the oil in the cell spreads to the neighbor cells by the spreading rules. There are three spreading rules. First, the oil in the certain cell only spreads to the neighbor cells that contain larger oil than the certain cell. Second, the oil evaporates in proportion to the temperature of the ocean at the every time step. Third, the oil spreading property is affected by the direction and the speed of the current and the wind. The oil spreading simulation model of the each cell is defined by using the combined discrete event and discrete time simulation model architecture with the information and the spreading rules in the cell. The oil spreading simulation is performed when the oil of 10,000 kL is polluted in the ocean environment of 300 m by 300 m with various current and wind.

• Atmosphere
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• v.16 no.3
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• pp.203-213
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• 2006

The objective of this paper is to investigate the effects of physical parameterization on the simulation of a snowfall event over Korea caused by air-mass transformation by using the PSU/NCAR MM5. A heavy snowfall event over Korea during 3-5 January 2003 is selected. In addition to the control experiments employing simple-ice microphysics scheme, MRF PBL scheme, and original surface layer process, three consequent physics sensitivity experiments are performed. Each experiment exchanges microphysics (Reisner Graupel), boundary layer (YSU PBL) schemes, and revised surface layer process with a reduced thermal roughness length for the control run. The control run reproduces an overall pattern of snowfall over Korea, but with a high bias by a factor of about 2. As revealed in the previous studies, the cloud microphysics and PBL parameterizations do not show a significant sensitivity for the case of snowfall. A more sophisticated cloud processes does not reveal a discernible effect on the simulated snowfall. Further, high bias in snowfall is exaggerated when a more realistic PBL scheme is employed. On the other hand, it is found that the revised surface layer process plays a role in improving the prediction of snowfall by reducing it. Thus, it is found that a realistic design of surface layer physics in mesoscale models is an important factor to the reduction of systematic bias of the snowfall over Korea that is caused by air-mass transformation over the Yellow sea.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.337-351
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• 2010

There is a growing dissatisfaction with use of conventional statistical methods for the prediction of extreme events. Conventional methodology for modeling extreme event consists of adopting an asymptotic model to describe stochastic variation. However asymptotically motivated models remain the centerpiece of our modeling strategy, since without such an asymptotic basis, models have no rational for extrapolation beyond the level of observed data. Also, this asymptotic models ignored or overestimate the uncertainty and finally decrease the reliability of uncertainty. Therefore this article provide the research example of the extreme rainfall event and the methodology to reduce the uncertainty. In this study, the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) and the MLE (Maximum Likelihood Estimation) methods using a quadratic approximation are applied to perform the at-site rainfall frequency analysis. Especially, the GEV distribution and Gumbel distribution which frequently used distribution in the fields of rainfall frequency distribution are used and compared. Also, the results of two distribution are analyzed and compared in the aspect of uncertainty.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.2
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• pp.56-67
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• 2006

The reliability and failure mode effect analysis are effective means to achieve efficient and cost-reduction design for satellite development. The failure rate of COTS (Commercial-Off-The-Shelf) parts required for reliability analysis is not usually provided from the manufacturer. Space environment factors based on empirical data obtained from MIL-HDBK-217F can be applicable to the reliability calculation. As a radiation environment factor, the occurrence rate of SEL (Single Event Latch-up) is additionally incorporated for the failure rate prediction. In this paper, the statistical reliability analysis method for low-cost small satellite using COTS parts is suggested. This statistical reliability analysis was applied to HAUSAT-2 small satellite whose electronic boxes are consisted of many COTS parts to calculate the system reliability at the end of design mission life.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.696-706
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• 2023

Consequences of an anticipated Beyond Design Basis Accident (BDBA) Long-Term Station Blackout (LTSBO) event with complete loss of grid power in the VVER-1200 reactor of Rooppur Nuclear Power Plant (NPP) of Unit-1 are assessed using the RASCAL 4.3 code. This study estimated the released radionuclides, received public radiological dose, and ground surface concentration considering 3 accident scenarios of International Nuclear and Radiological Event Scale (INES) level 7 and two meteorological conditions. Atmospheric transport, dispersion, and deposition processes of released radionuclides are simulated using a straight-line trajectory Gaussian plume model for short distances and a Gaussian puff model for long distances. Total Effective Dose Equivalent (TEDE) to the public within 40 km and radionuclides contribution for three-dose pathways of inhalation, cloudshine, and groundshine owing to airborne releases are evaluated considering with and without passive safety Emergency Core Cooling System (ECCS) in dry (winter) and wet (monsoon) seasons. Source term and their release rates are varied with the functional duration of passive safety ECCS. In three accident scenarios, the TEDE of 10 mSv and above are confined to 8 km and 2 km for the wet and dry seasons, respectively in the downwind direction. The groundshine dose is the most dominating in the wet season while the inhalation dose is in the dry season. Total received doses and surface concentration in the wet season near the plant are higher than those in the dry season due to the deposition effect of rain on the radioactive substances.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.230-237
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• 2018

Purpose: In Korea, traffic information is collected in real time as part of Intelligent Transportation System to enhance efficiency of road operation. However, traffic information based on real-time data is different from the traffic situation the driver will experience. Method: In this study, forecasts were made for future highway traffic by day and time period by adjusting the Archived data reference days to 3, 5 and 10 days based on existing traffic Archived data. Results: Fewer days of reference in the past showed smaller errors. The prediction of Monday based on five past histories showed greater errors than the 10 past histories, as the traffic flow on the sixth Monday of 2016 was somewhat different from the usual holiday. Conclution: This study shows that less of the reference days of the past history when estimating traffic volume, the more accurate the data of the traffic history of the event can be used on special days.

• Atmosphere
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• v.24 no.1
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• pp.1-15
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• 2014

This study compared ensemble mean and probability forecasts of snow depth amount associated with winter storm over South Korea on 28 December 2012 at five operational forecast centers (CMA, ECMWF, NCEP, KMA, and UMKO). And cause of difference in predicted snow depth at each Ensemble Prediction System (EPS) was investigated by using THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data. This snowfall event occurred due to low pressure passing through South Sea of Korea. Amount of 6 hr accumulated snow depth was more than 10 cm over southern region of South Korea In this case study, ECMWF showed best prediction skill for the spatio-temporal distribution of snow depth. At first, ECMWF EPS has been consistently enhancing the indications present in ensemble mean snow depth forecasts from 7-day lead time. Secondly, its ensemble probabilities in excess of 2~5 cm/6 hour have been coincided with observation frequencies. And this snowfall case could be predicted from 5-day lead time by using 10-day lag ensemble mean 6 hr accumulated snow depth distribution. In addition, the cause of good performances at ECMWF EPS in predicted snow depth amounts was due to outstanding prediction ability of forming inversion layer with below $0^{\circ}C$ temperature in low level (below 850 hPa) according to $35^{\circ}N$ at 1-day lead time.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.537-549
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• 2017

This study evaluated the accuracy of rainfall and flood forecasts in Sancheong basin with three rainfall events such as typhoon and stationary front by using LDAPS provided by Korea Meteorological Agency and MSM provided by Japan Meteorological Agency. In the rainfall forecast result, both LDAPS and MSM showed high forecast accuracy for wide-area prediction such as typhoon event, but local-area prediction such as stationary front has a limit to quantitative precipitation forecast (QPF). In the flood forecast result, the forecast accuracy was improved with the increase of the lead time, and it showed the possibility of LDAPS and MSM in the field of rainfall and flood forecast by linking meteorology and water resources.