• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 춘계학술대회 논문집
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• pp.481-485
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• 2002

In these days, as the scale of our technology becomes larger and more highly advanced, the magnitude of an accident tends to be large. For this reason, in some systems whose accident may cause a large-scale and long-term catastrophe, a preliminary and quantitative safety assessment has become required before its construction. A method developed for this requirement is risk assessment. In this study, we focused on the methodology of probabilistic risk assessment, which has been developed mainly in the field of nuclear power industry, and considered the process to adopt this method to railway system in order to establish a scientific and comprehensive way of safety assessment.

• 한국환경보건학회지
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• 제47권4호
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• pp.366-377
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• 2021

Background: Polycyclic aromatic hydrocarbons (PAHs) are generated in petrochemical complexes, can spread to residential areas and affect the health of residents. Although harmful PAHs are mainly present in particle phase, gas phase PAHs can generate stronger toxic substances through photochemical reaction. Therefore, the risk assessment for PAHs around the petrochemical complex should consider both particle and gas phase concentrations. Objectives: This study aimed to investigate the concentration characteristics of particle and gas phase PAHs by season in residential areas around petrochemical complexes, and to assess the risk of PAHs. Methods: Samples were collected for 7 days by seasons in 2014~2015 using a high volume air sampler. Particle and gas phase PAHs were sampled using quartz filter and polyurethane foam, respectively, analyzed by GC-MS. Chronic toxicity and probabilistic risk assessment were performed on 14 PAHs. For chronic toxicity risk assessment, inhalation unit risk was used. Monte-Carlo simulation was performed for probabilistic risk assessment using the mean and standard deviation of measured PAHs. Results: The concentration of particle total PAHs was highest in autumn. The gas phase concentration was highest in autumn. The average gas phase distribution ratio of low molecular weight PAHs composed of 2~3 benzene rings was 85%. The average of the medium molecular weight composed of 4 benzene rings was 53%, and the average of the high molecular weight composed of 5 or more benzene rings was 9%. In the chronic toxicity risk assessment, 7 of the 14 PAHs exceeded the excess carcinogenic risk of 1.00×10^-6. In the Monte-Carlo simulation, Benzo[a]pyrene had the highest probability of exceeding 1.00×10^-6, which was 100%. Conclusions: The concentration of PAHs in the residential area around the petrochemical complex exceeded the standard, and the excess carcinogenic risk was evaluated to be high. Therefore, it is necessary to manage the air environment around the petrochemical complex.

• 대한인간공학회지
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• 제30권1호
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• pp.55-64
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• 2011

Objective: The aim of this paper is to introduce the activities and research trends of human reliability analysis including brief summary about contents and methods of the analysis. Background: Various approaches and methods have been suggested and used to assess human reliability in field of risk assessment of nuclear power plants. However, it has noticed that there is high uncertainty in human reliability analysis which results in a major bottleneck for risk-informed activities of nuclear power plants. Method: First and second generation methods of human reliability analysis are reviewed and a few representative methods are discussed from the risk assessment perspective. The strength and weakness of each method is also examined from the viewpoint of reliability analyst as a user. In addition, new research trends in this field are briefly summarized. Results: Human reliability analysis has become an important tool to support not only risk assessment but also system design of a centralized complex system. Conclusion: Human reliability analysis should be improved by active cooperation with researchers in field of human factors. Application: The trends of human reliability analysis explained in this paper will help researchers to find interest topics to which they could contribute.

• 시스템엔지니어링워크숍
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• 통권7호
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• pp.75-78
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• 2006

• Nuclear Engineering and Technology
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• 제52권4호
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• pp.764-775
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• 2020

Periodic safety reviews (PSRs) are conducted on operating nuclear power plants (NPPs) and have been mandated also for research reactors in Korea, in response to the Fukushima accident. One safety review tool, the probabilistic safety assessment (PSA), aims to identify weaknesses in the design and operation of the research reactor, and to evaluate and compare possible safety improvements. However, the PSA for research reactors is difficult due to scarce data availability. An important element in the analysis of research reactors is the reactor protection system (RPS), with its functionality and importance. In this view, we consider that of the AGN-201K, a zero-power reactor without forced decay heat removal systems, to demonstrate a risk-informed safety improvement study. By incorporating risk- and safety-significance importance measures, and sensitivity and uncertainty analyses, the proposed method identifies critical components in the RPS reliability model, systematically proposes potential safety improvements and ranks them to assist in the decision-making process.

• 한국지능시스템학회논문지
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• 제21권4호
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• pp.475-480
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• 2011

본 논문에서는 충돌 위험도 판단 시스템을 제안한다. 먼저 칼만 필터를 이용하여 보행자의 정보를 예측하고, 몬테 카르롤로 모의 실험과 신경 회로망을 이용해 충돌 확률을 계산한다. 그리고 과거의 충돌 확률 정보를 이용하여 충돌확률을 예측한다. Belief 충돌 예측 방법은 현재뿐만 아니라, 과거의 필터링 정보를 모두 이용하여 충돌 확률을 에측한다. 마지막으로 컴퓨터 시뮬레이션으로 제안된 알고리즘의 성능을 확인한다.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1246-1254
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• 2018

The importance of performing Level 3 probabilistic safety assessments (PSA) along with a general interest in assessing multi-unit risk has been sharply increasing after the Fukushima Daiichi nuclear power plant (NPP) accident. However, relatively few studies on multi-unit Level 3 PSA have been performed to date, reflecting limited scenarios of multi-unit accidents with higher priority. The major difficulty to carry out a multi-unit Level 3 PSA lies in the exponentially increasing number of multi-unit accident combinations, as different source terms can be released from each NPP unit; indeed, building consequence models for the astronomical number of accident scenarios is simply impractical. In this study, a new approach has been developed that employs the look-up table method to cover every multi-unit accident scenario. Consequence results for each scenario can be found on the table, established with a practical amount of effort, and can be matched to the frequency of the scenario. Preliminary application to a six-unit NPP site was carried out, where it was found that the difference between full-coverage and cut-off cases could be considerably high and therefore influence the total risk. Additional studies should be performed to fine tune the details and overcome the limitations of the approach.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2924-2932
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• 2022

Motivated by learning from experience and exploiting existing knowledge in civil nuclear operations, we have developed in-house generic Probabilistic Safety Assessment (PSA) models for pressurized and boiling water reactors. The models are computationally light, handy, transparent, user-friendly, and easily adaptable to account for major plant-specific differences. They cover the common internal initiating events, frontline and support systems reliability and dependencies, human-factors, common-cause failures, and account for new factors typically overlooked in many PSAs. For quantification, the models use generic US reliability data, precursor analysis reports, the ETHZ Curated Nuclear Events Database, and experts' opinions. Moreover, uncertainties in the most influential basic events are addressed. The generated results show good agreement with assessments available in the literature with detailed PSAs. We envision the models as an unbiased framework to measure nuclear operational risk with the same "ruler", and hence support inter-plant risk comparisons that are usually not possible due to differences in plant-specific PSA assumptions and scopes. The models can be used for initial risk screening, order-of-magnitude precursor analysis, and other research/pedagogic applications especially when no plant-specific PSAs are available. Finally, we are using the generic models for large-scale precursor analysis that will generate big picture trends, lessons, and insights.

• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3324-3335
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• 2022

Several countries show interest in the Generation-IV power reactor innovative small module (PRISM), including: Canada, Japan, Korea, Saudi Arabia and the United Kingdom. Generation IV International Forum (GIF) has recommended the utilizing of probabilistic safety assessment (PSA) in evaluating the safety of Generation-IV reactors. This paper reviews the PSA performed for PRISM using SAPHIRE 7.27 code. This work shows that the core damage frequency (CDF) of PRISM for a single module is estimated by 8.5E-8/year which is lower than the Generation-IV target that is 1E-6 core damage per year. The social risk of PRISM (likelihood of latent cancer fatality) with evacuation is estimated by 9.0E-12/year which is much lower than the basic safety objective (BSO) that is 1E-7/year. The social risk without evacuation is estimated by 1.2E- 11/year which is also much lower than the BSO. For the individual risk (likelihood of prompt fatality), it is concluded that it can be considered negligible with evacuation (1.0E-13/year). Assuming no evacuation, the individual risk is 2.7E-10/year which is again much lower than the BSO. In comparison with other PSAs performed for similar sodium fast reactors (SFRs), it shows that PRISM concept has the lowest CDF.

• Earthquakes and Structures
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• 제25권6호
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.