• Journal of the Korean Institute of Gas
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• v.11 no.3
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• pp.7-12
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• 2007

The search for a new fire-extinguishing agent with all the desirable properties of halon 1301 has not been successful. To study binary gaseous extinguishing agents instead, one has to determine the extinguishing concentrations for several compositions of a given chemical in an inert gas. This process is expensive and time consuming. The fire suppression efficiencies of gas mixtures of HFC 125 and HFC 227ea with nitrogen as total flooding agents were studied by cup burner method. It was shown that addition of small amounts of those extinguishants to nitrogen can enhance the suppression effectiveness of the inert gas. As expected, the degree of synergism was highest at low concentrations of the chemical. For each binary system, extinguishing concentrations of the pure compounds and one binary data were used to predict the extinguishing concentrations for the entire range of binary composition. The predicted values were very close to experimental data.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.4
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• pp.98-111
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• 2015

Urban environmental problems such as flooding, depletion of ground water, pollution of urban streams and the heat island effect caused by urban development and climate change can be mitigated by the improvement of the urban water cycle. For the effective planning of water cycle management it is necessary to establish aerial Hydrotope Maps, with which we can estimate the status and change of the water allowance for any site. The structure of the German water balance model BAGLUVA, which is based on soil and vegetation, was analyzed and the input data and boundary condition of the model was compared with Korean data and research results. The BAGLUVA Model consists of 5 Input categories (climate, land use, topography, soil hydrology and irrigation). The structure and interconnection of these categories are analyzed and new concepts and implementation methods of topographic factor, maximum evapotranspiration ratio, effective rooting depth and Bagrov n parameter was compared and analyzed. The relation of real evapotranspiration ($ET_a$)-maximum evapotranspiration ($ET_{max}$) - precipitation (P) was via Bagrov n factor represented. The aerial and land use oriented Hydrotope Map can help us to investigate the water balance of small catchment areas and to set goals for volume of rainwater management and LID facilities effectively in the city. Further, this map is a useful tool for implementing water resource management within landscape and urban planning.

• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.447-458
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• 2007

In this study, the coastal urban flood prediction and warning system based on HEC-RAS and SWMM were investigated to evaluate a watershed of On-Cheon stream in Busan which has characteristics of costal area cased by flooding of coastal urban areas. The basis of this study is a selection of various geological data from the numerical map that is a watershed of On-Cheon stream and computation of hydrologic GIS data. Thiessen method was used for analyzing of rainfall on the On-Cheon stream and 6th regression equation, which is Huff's Type II was time-distribution of rainfall. To evaluate the deployment of flood prediction and warning system, risk depth was used on the 3 selected areas. To find the threshold runoff for hydraulic analysis of stream, HEC-RAS was used and flood depth and threshold runoff was considered with the effect of tidal water level. To estimate urban flash flood trigger rainfall, PCSWMM 2002 was introduced for hydrologic analysis. Consequently, not only were the criteria of coastal urban flood prediction and warning system decided on the watershed of On-Cheon stream, but also the deployment flow charts of flood prediction and warning system and operation system was evaluated. This study indicates the criteria of flood prediction and warning system on the coastal areas and modeling methods with application of ArcView GIS, HEC-RAS and SWMM on the basin. For the future, flood prediction and warning system should be considered and developed to various basin cases to reduce natural flood disasters in coastal urban area.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.699-708
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• 2023

Nuclear power plants (NPPs) consider possible external events, including natural hazards, during the design phase to ensure safe operation. However, in recent years, due to the increasing probability of natural hazards exceeding the design, a careful review of extreme natural hazards and unforeseen external events during the design phase has become necessary. In this study, the objective was to screen potential extreme natural hazards at NPP sites in Korea. Initially, we investigated and analyzed the characteristics of NPP sites and the events caused by external hazards. Furthermore, we analyzed existing literature and research data to establish screening procedures and criteria that suit the actual conditions of domestic NPPs. Based on these criteria and data, we conducted qualitative screening for each NPP site and identified potential extreme natural hazards through quantitative screening and walkdown. As a result of the screening, in addition to internal flooding caused by heavy rain, wind pressure and extreme air pressure caused by extreme winds were screened as potential extreme natural hazards common to all sites. Additionally, at the Kori site, storm surge was selected as the most significant potential extreme natural hazard.

• Economic and Environmental Geology
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• v.38 no.6 s.175
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• pp.633-642
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• 2005

We present the sedimentary sequence and distribution pattern of the late Holocene muddy deposits in the northern East China Sea shelf using the high-resolution 'Chirp' profiles. The seismic sedimentary sequence overlying acoustic basement (basal reflector-B) can be divided into two depositional units (Unit 1 and 2) bounded by erosional bounding surface (mid reflector-M). The lower Unit 1 above basal reflector-H is characterized by the acoustically parallel to subparallel reflections and channel-fill facies. The upper Unit 2, up to 7 m in thickness, shows seismically semi-transparent seismic facies and lenticular body form. On the base of sequence stratigraphic concept, these two sediment units have developed during transgression and highstand period, respectively, since the last sea-level lowstand. The transgressive systems tract (Unit 1) lie directly on the sequence boundary (reflector B) that have farmed during the last glacial maximum. The transgressive systems tract in this study consists mostly of complex of delta, fluvial, and tidal deposits within the incised valley estuary system. The maximum flooding surface (reflector M) corresponding to the top surface of transgressive systems tract is obviously characterized by erosional depression. The highstand systems tract (Unit 2) above maximum flooding surface is made up of the mud patch filled with the erosional depression. The high-stand mud deposits showing a circle shape just like a typhoon symbol locates about 140 km off the south of Cheju Island with water depth of $60\~90m$. Coverage area and total sediment volume of the mud deposits are about $3,200km^2$ and $10.7\times10^9\;m^3$, respectively. The origin of the mud patch is interpreted as a result of accumulating suspended sediments derived from the paleo-Yellow and/or Yangtze Rivers. The circular distribution pattern of the mud patch appears to be largely controlled by the presence of cyclonic eddy in the northern East China Sea.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.329-342
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• 2003

Most of the existing multicast routing protocols for ad-hoc networks do not take into account the efficiency of the protocol for the cases when there are large number of sources in the multicast group, resulting in either large overhead or poor data delivery ratio when the number of sources is large. In this paper, we propose a multicast routing protocol for ad-hoc networks, which particularly considers the scalability of the protocol in terms of the number of sources in the multicast groups. The proposed protocol designates a set of sources as the core sources. Each core source is a root of each tree that reaches all the destinations of the multicast group. The union of these trees constitutes the data delivery mesh, and each of the non-core sources finds the nearest core source in order to delegate its data delivery. For the efficient operation of the proposed protocol, it is important to have an appropriate number of core sources. Having too many of the core sources incurs excessive control and data packet overhead, whereas having too little of them results in a vulnerable and overloaded data delivery mesh. The data delivery mesh is optimally reconfigured through the periodic control message flooding from the core sources, whereas the connectivity of the mesh is maintained by a persistent local mesh recovery mechanism. The simulation results show that the proposed protocol achieves an efficient multicast communication with high data delivery ratio and low communication overhead compared with the other existing multicast routing protocols when there are multiple sources in the multicast group.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.