• Nuclear Engineering and Technology
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• 제53권12호
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• pp.3990-4002
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• 2021

CSPACE (Core meltdown, Safety and Performance Analysis CodE for nuclear power plants) for a simulation of severe accident progression in a Pressurized Water Reactor (PWR) is developed by coupling of verified system thermal hydraulic code of SPACE (Safety and Performance Analysis CodE for nuclear power plants) and core damage progression code of COMPASS (Core Meltdown Progression Accident Simulation Software). SPACE is responsible for the description of fluid state in nuclear system nodes, while COMPASS is responsible for the prediction of thermal and mechanical responses of core fuels and reactor vessel heat structures. New heat transfer models to each phase of the fluid, flow blockage, corium behavior in the lower head are added to COMPASS. Then, an interface module for the data transfer between two codes was developed to enable coupling. An implicit coupling scheme of wall heat transfer was applied to prevent fluid temperature oscillation. To validate the performance of newly developed code CSPACE, we analyzed typical severe accident scenarios for OPR1000 (Optimized Power Reactor 1000), which were initiated from large break loss of coolant accident, small break loss of coolant accident, and station black out accident. The results including thermal hydraulic behavior of RCS, core damage progression, hydrogen generation, corium behavior in the lower head, reactor vessel failure were reasonable and consistent. We demonstrate that CSPACE provides a good platform for the prediction of severe accident progression by detailed review of analysis results and a qualitative comparison with the results of previous MELCOR analysis.

• 한국해양공학회지
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• 제36권5호
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• pp.295-302
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• 2022

The initial response to a marine accident can play a key role to minimize the accident. Therefore, various decision support systems have been developed using sensors, simulations, and active response equipment. In this study, we developed an algorithm to predict damage locations using ship motion data with bidirectional long short-term memory (BiLSTM), a type of recurrent neural network. To reflect the low frequency ship motion characteristics, 200 time-series data collected for 100 s were considered as input values. Heave, roll, and pitch were used as features for the prediction model. The F1-score of the BiLSTM model was 0.92; this was an improvement over the F1-score of 0.90 of a prior model. Furthermore, 53 of 75 locations of damage had an F1-score above 0.90. The model predicted the damage location with high accuracy, allowing for a quick initial response even if the ship did not have flood sensors. The model can be used as input data with high accuracy for a real-time progressive flooding simulator on board.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.2987-3002
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• 2023

In 2015, the number of senior citizens aged 65 and over in Korea was 6,662,400, accounting for 13.1% of the total population. Along with these social phenomena, risk information related to the elderly is increasing every year. In particular, a fall accident caused by a fall can cause serious injury to an elderly person, so special attention is required. Therefore, in this paper, we implemented a system that monitors fall accidents and informs them in real time to minimize damage caused by falls. To this end, beacon-based indoor location positioning was performed and biometric information based on an integrated module was collected using various sensors. In other words, a multi-functional sensor integration module was designed based on Arduino to collect and monitor user's temperature, heart rate, and motion data in real time. Finally, through the analysis and prediction of measurement signals from the integrated module, damage from fall accidents can be reduced and rapid emergency treatment is possible. Through this, it is possible to reduce the damage caused by a fall accident, and rapid emergency treatment will be possible. In addition, it is expected to lead a new paradigm of safety systems through expansion and application to socially vulnerable groups.

• 한국재난정보학회 논문집
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• 제14권1호
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• pp.59-64
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• 2018

화학사고에 대한 경각심이 지속적으로 높아지고 있는 동향 속에서 매년 꾸준히 발생하고 있는 유해화학물질 운송차량 사고의 추세 및 특성을 조사하고 향후 운송차량에 의한 사고예방 대응분야에서의 개선방향을 연구하였다. 2014년 1월부터 2017년 12월까지 발생한 총 383건의 화학사고를 분석한 결과 운송차량 사고는 83건으로 전체 화학사고의 21.67%를 차지했다. 현행제도에서는 사업장과 다르게 위험물을 직접적으로 취급함에도 불구하고 피해예측에 대한 규제에서 벗어나 있으며 실제 사고 시 효과적으로 대응하기 위해서는 피해예측에 대한 정보가 있어야하고 각 관계부처와 이를 공유하는 것이 필요하다. 그리고 유해화학 물질을 포함하는 위험물의 통합적인 컨트롤타워를 통한 운송차량 실시간 모니터링이 이뤄지는 방향으로 발전되어야 한다.

• 한국안전학회지
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• 제26권6호
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• pp.130-136
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• 2011

Since out of a lot of traffic problems traffic accidents cause damage to life and properties of people, it stands out as one of traffic problems which needs improvement, and the loss due to traffic accident negatively affects not only the parties to the accident but also the national economy. Thus, continual concern of the government toward traffic safety is getting bigger and lately each local government is preparing a basic plan for traffic safety and vitalizing traffic safety policies. As expanding the responsibility and role of local governments for traffic safety, traffic safety measures which are based on the characteristics of each local government should be studied. Most of analytical methods in the existing traffic accidents prediction models with macroscopic vision focus on socioeconomic variables such as local population and the number of registered vehicles, and present a great deal of prediction error when they are applied in practice. In this context, this study proposed a traffic accident prediction model in respect of macroscopic level for autonomous districts (administrative districts) of Seoul City. The model development was not based on the entire city but on the type of local land usage (development density) whose relationship with traffic accident frequency was analyzed.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2747-2756
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• 2023

Reinforced Concrete (RC) shear walls are one of the civil structures in nuclear power plants to resist lateral loads such as earthquakes and wind loads effectively. Risk-informed and performance-based regulation in the nuclear industry requires considering possible accidents and determining desirable performance on structures. As a result, rather than predicting only the ultimate capacity of structures, the prediction of performances on structures depending on different damage states or various accident scenarios have increasingly needed. This study aims to develop machine-learning models predicting drifts of the RC shear walls according to the damage limit states. The damage limit states are divided into four categories: the onset of cracking, yielding of rebars, crushing of concrete, and structural failure. The data on the drift of shear walls at each damage state are collected from the existing studies, and four regression machine-learning models are used to train the datasets. In addition, the bagging ensemble method is applied to improve the accuracy of the individual machine-learning models. The developed models are to predict the drifts of shear walls consisting of various cross-sections based on designated damage limit states in advance and help to determine the repairing methods according to damage levels to shear walls.

• 대한원격탐사학회지
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• 제36권5_4호
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• pp.1255-1266
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• 2020

본 연구에서는 화학사고에 따른 인명피해 저감을 위해서 신속하고 정확한 화학물질 확산 범위 예측을 위한 복합시뮬레이션 프로토타입을 개발하였다. 복합시뮬레이션은 화학물질의 누출 특성을 고려하고자 근거리 확산과정에서 누출 운동량을 고려하였다. 원거리 확산과정에서는 사고지점 주변의 기상 및 지형정보를 이용하여 획일적으로 제시되었던 기존 모델의 바람 분포를 개선하여 실제와 유사한 바람장을 구현하였다. 개선된 근·원거리 확산과정에 따라 최종적으로 피해확산 범위는 기존의 모델에 비해서 정밀한 분포를 나타냈다. 본 연구에서 개발된 복합시뮬레이션의 시간대별 피해 범위 예측 결과 통해서 화학사고 발생 후 주민 대피 및 복귀 등 정책적 의사결정의 지원시스템으로서 활용도가 높을 것으로 기대된다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2014년도 춘계학술대회
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• pp.36-37
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• 2014

It is necessary to develop highly sophisticated Modeling & Simulation (M&S) system for the scientific investigation of marine accident causes and for the systematic reproduction of accidental damage procedure. To ensure an accurate and reasonable prediction of marine accidental causes, such as collision, grounding and flooding, full-scale ship M&S simulations would be the best approach using hydrocode, such as LS-DYNA code, with its Fluid-Structure Interaction (FSI) analysis technique. The objectivity of this paper is to present three full-scale ship collision, grounding and flooding simulation results of marine accidents, and to show the possibility of the scientific investigation of marine accident causes using highly sophisticated M&S system.

• 한국가스학회지
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• 제7권4호
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• pp.61-66
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• 2003

본 연구에서는 화학설비의 취약점을 파악하여 안전성을 경제적으로 확보할 수 있는 대안에 대한 설비별 안전투자비용과 그에 따른 편익을 산출하고, 분석함으로써 경제적인 안전 투자 대안을 제시할 수 있는 시스템을 개발하였다. 이를 위해 화학설비의 위험성을 정량적으로 평가하기 위한 사고 빈도 분석 모듈과 사고 피해 예측 모듈을 개발하고, 중대산업사고 사례 및 선진국(네덜란드, 호주, 미국, 영국, 독일 등)의 사회적 위험성을 비교 $\cdot$ 분석하여 국내 현실에 반영할 수 있는 사회적 위험성(societal risk : F-N Curve) 기준을 제시하였다. 또한, 현장 방문을 통하여 공정에 대한 투자비용과 그에 따른 편익 항목을 분석$\cdot$선정하여 앞의 결과들을 통하여 화학설비에서 발생하는 비용$\cdot$편익에 대한 안전투자대안의 순현재가치(NVP, Net Present Value)를 도출하여 안전성을 향상시킬 수 있는 대안들을 분석하고 비교할 수 있는 시스템을 개발하였다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.251-252
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• 2023

Compared to other industries the construction industry experiences more casualties and property damage due to safety accidents. One of the reasons is the increasing number of foreign workers. For this reason, past studies have found that foreign workers at construction sites are more exposed to safety accidents than non-foreign workers. Nevertheless the proportion of foreign workers involved in safety accidents at construction sites is increasing, and there has been a lack of research to predict the risk of safety accidents at construction sites. Additionally, realistic safety management is lacking due to a lack of safety accident risk prediction research. Therefore, in this study, we would like to propose basic research that proposes an AI-based safety accident prediction model framework for predicting safety accidents of foreign workers at construction sites. The framework and results of this study will contribute to reducing and preventing the risk of safety accidents for foreign workers through risk prediction for safety management of foreign workers at construction sites.