• Journal of Korean Society of Disaster and Security
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• v.17 no.1
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• pp.1-8
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• 2024

In Korea, mountainous areas cover 60% of the land, leading to increased factors such as concentrated heavy rainfall and typhoons, which can result in debris flow and landslide. Despite the high risk of disasters like landslides and debris flow, there has been a tendency in most regions to focus more on post-damage recovery rather than preventing damage. Therefore, in this study, precise topographic data was constructed by conducting on-site surveys and drone measurements in areas where debris flow actually occurred, to analyze the risk zones for such events. The numerical analysis program RAMMS model was utilized to perform debris flow analysis on the areas prone to debris flow, and the actual distribution of debris flow was compared and analyzed to evaluate the applicability of the model. As a result, the debris flow generation area calculated by the RAMMS model was found to be 18% larger than the actual area, and the travel distance was estimated to be 10% smaller. However, the simulated shape of debris flow generation and the path of movement calculated by the model closely resembled the actual data. In the future, we aim to conduct additional research, including model verification suitable for domestic conditions and the selection of areas for damage prediction through debris flow analysis in unmeasured watersheds.

• Journal of the Korean Geotechnical Society
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• v.31 no.6
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• pp.59-69
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• 2015

Recently, landslide and debris-flow disasters caused by severe rain storms have frequently occurred. Many researches related to landslide susceptibility analysis and debris-flow hazard analysis have been conducted, but there are not many researches related to mobilization analysis for landslides transforming into debris-flow in slope areas. In this study, statistical analyses such as discriminant analysis and logistic regression analysis were conducted to develop a mobilization criterion using geomorphological and geological factors. Ten parameters of geomorphological and geological factors were used as independent variables, and 466 cases (228 non-mobilization cases and 238 mobilization cases) were investigated for the statistical analyses. First of all, Fisher's discriminant function was used for the mobilization criterion. It showed 91.6 percent in the accuracy of actual mobilization cases, but homogeneity condition of variance and covariance between non-mobilization and mobilization groups was not satisfied, and independent variables did not follow normal distribution, either. Second, binomial logistic analysis was conducted for the mobilization criterion. The result showed 92.3 percent in the accuracy of actual mobilization cases, and all assumptions for the logistic analysis were satisfied. Therefore, it can be concluded that the mobilization criterion for debris-flow using binomial logistic regression analysis can be effectively applied for the prediction of debris-flow hazard analysis.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.95-102
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• 2017

Debris flow is a composition of solid objects of various sizes, suspension and water, which occurs frequently as the results of landslide following heavy rainfall. This often causes extensive damage in the form of socio-economic losses and casualties as witnessed during the incident around Mt. Umyeon, Seoul in 2011. There have been numerous investigation to mitigate the impacts from debris flow; however, the estimation as preparedness measure has not been successful due to nonlinear and multiphase characteristics of phenomena both in material and process inherent in the debris flow. This study presents a numerical approach to simulate the debris flow using open source code of computational fluid dynamics, OpenFOAM with non-Newtonian viscosity model for three phase material modeling. In order to validate the proposed numerical method, the quantitative evaluations were made by comparisons with experimental results and qualitative analysis for the dispersion characteristics was carried for the case of debris flow in the actual incident from Mt. Umyeon.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.283-291
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• 2024

Sodium cooled Fast Reactors (SFR) are built with several engineered safety features and hence a severe accident such as a core melt accident is hypothetical with a probability of <10^-6/ry. However, in case of such accidents, the mixture of the molten fuel and structural materials interacts with sodium. This phenomenon is known as Molten Fuel Coolant Interaction (MFCI) and results in fragmentation of the melt due to various instabilities. The fragmented particles settle as a debris bed on the core catcher at the bottom of the reactor vessel, and continue to generate decay heat. Characteristics of the debris particles play a vital role in heat transfer from the bed and need thorough investigation. The size, shape, and physical state of the debris depend on the associated fragmentation mechanism, superheating of the melt, and sodium temperature. Experiments have been conducted by releasing simulated corium, a molten mixture of alumina and iron generated by the aluminothermy process at ~2400 ℃ into liquid sodium, to study the fragmentation phenomena. After the experiment, the fragmented debris was retrieved and the particle size distribution was determined by sieve analysis. The debris was subjected to microscopic investigation for obtaining morphological characteristics. Based on the characteristics of debris, an attempt has been made to assess of fragmentation mechanism of simulated corium in sodium.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.45-58
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• 2015

The aim of this study is to find out major accumulation zones through field survey and moving route tracking trials on floating debris of Nakdong River. It also identified composition and accumulated amount of the floating debris by sample survey for accumulation zones. As a result, total 5 accumulation zones were selected from the midstream and downstream of the Nakdong River. There was a large amount of floating debris, including vegetation debris, in the accumulation zones. And two accumulation zones located in the downstream region, it is much more likely to flow into the ocean along river. From the sample survey on the major accumulation zones, more than $40{\ell}$ of floating debris were collected including vegetation and artificial debris. As a result of composition analysis for artificial debris, plastic(49%) and styrofoam(36%) were the majority in number. The present study is expected to help to plan an efficient pre-collecting activity and to reduce floating debris flowing into the ocean from the Nakdong River.

• Journal of the Korean GEO-environmental Society
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• v.18 no.1
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• pp.13-21
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• 2017

In this study, the behavior characteristics and triggering rainfall of debris flow were investigated on the basis of DB constructed by performing field investigation and collecting the rainfall data at the sites where debris flow occurred around the west of Gangwon and adjacent areas during the last 10 years. For hill slope and channelized type of debris flow, its behavior characteristic was analyzed through runout channel of debris flow divided into zone of initiation, transportation and deposition and its magnitude was estimated by considering erosion at zones of initiation and transportation. Some considerations related to establishment of landslide forecasting criterion were raised by comparing the analyzed results of analysis of rainfall at the time of debris-flow occurrence with the previous researches about the triggering rainfall of debris flow. In addition, an ID curve of inducing debris flow adequate to the investigated site was proposed and compared with results of previous study.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.7
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• pp.1044-1051
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• 2009

During contact between surfaces, there is wear and the generation of wear. The particles contained in the lubricating oil carry detailed and important monitoring information about the condition of the machine. Therefore, this paper was undertaken for the Ferrography system of wear debris generated from a lubricated moving machine surface. The lubricating wear test was performed under different experimental conditions using the Falex wear test of the Pin and V-Block types by Ti(C,N) coated. It was shown from the test results that wear particle concentration(WPC), wear severity index(Is) and size distribution have come out all higher with increases in sliding friction time. With the Ferrogram thin leaf wear debris as well as ball and plate type wear particles were observed.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.448-449
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• 2005

• Journal of Industrial Technology
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• v.36
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• pp.49-55
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• 2016

Different criteria for evaluating vulnerability of debris flow hazard proposed by various institutes such as Korea Forest Service(KFS), Korea Institute of Geoscience and Mineral Resources(KIGAM), Ministry of Public Safety and Security (MPSS) and Korea Expressway Corporation (KEC) were reviewed and discussed. Assessment of debris flow hazard for natural slopes around land for house development was carried out on the basis of the report about results of performing in-situ survey. Results of evaluating vulnerability of debris flow hazard by using these methods were compared to each other to discuss appropriateness of their evaluation and to recommend improvement.

• Tribology and Lubricants
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• v.11 no.3
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• pp.24-30
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• 1995

This paper was undertaken to recognize the pattern of the wear debris by neural network as a link for the development of diagnosis system for movable condition of the lubricated machine surface. The wear test was carried out under different experimental conditions using the wear test device was made in laboratory and wear testing specimen of the pin-on-disk type were rubbed in paraffine series base oil, by varying applied load, sliding distance and mating material. The neural network has been used to pattern recognition of four parameter (diameter, elongation, complex and contrast) of the wear debris and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by the neural network. The characteristic parameter of the large wear debris over a few micron size enlarged recognition ability.