• 한국안전학회지
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• 제39권3호
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• pp.75-83
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• 2024

Accurately assessing and managing risks in any endeavor is crucial. Risk assessment in engineering translates the abstract concept of risk into actionable strategies for systematic risk management. However, risk validation is met with significant skepticism, particularly concerning the uncertainty of probability. This study aims to address the aforementioned uncertainty in a multitude of ways. Firstly, instead of relying on deterministic probability, it acknowledges uncertainty and presents a probabilistic interval. Secondly, considering the uncertainty interval highlighted in OREDA, it delineates the bounds of the probabilistic interval. Lastly, it investigates how much explanatory power deterministic probability has within the defined probabilistic interval. By utilizing fault tree analysis (FTA) and integrating confidence intervals, a probabilistic risk assessment was conducted to scrutinize the explanatory power of deterministic probability. In this context, explanatory power signifies the proportion of probability within the probabilistic risk assessment interval that lies below the deterministic probability. Research results reveal that at a 90% confidence interval, the explanatory power of deterministic probability decreases to 73%. Additionally, it was confirmed that explanatory power reached 100% only with a probability application 36.9 times higher.

• 환경영향평가
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• 제9권3호
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• pp.185-202
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• 2000

Uncertainty and variability in Life Cycle Assessment(LCA) have been significant key issues in LCA methodology with techniques in other research area such as social and political science. Variability is understood as stemming from inherent variations in the real world, while uncertainty comes from inaccurate measurements, lack of data, model assumptions, etc. Related articles in this issues were reviewed for classification, distinguish and elaboration of probabilistic/stochastic health risk analysis application in LCA. Concept of focal zone, streamlining technique, scenario modelling and Monte Carlo/Latin Hypercube risk analysis were applied to the uncertainty/variability analysis of health risk in LCA. These results show that this general framework of multi-disciplinary methodology between probabilistic health risk assessment and LCA was of benefit to decision making process by suppling information about input/output data sensitivity, health effect priority and health risk distribution. There should be further research needs for case study using this methodology.

• 환경영향평가
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• 제9권3호
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2006년도 제27회 추계학술대회논문집
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• pp.71-74
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• 2006

본 논문은 미국의 우주개발과 함께 고안되어 여러 산업에 걸쳐 적용된 바 있는 확률적 위험 분석(probabilistic Risk Assessment; PRA) 기법의 역사와 내용을 소개하고 현재 항공우주연구연이 개발하고 있는 소형위성발사체(KSLV-I)의 추진기관에 대하여 그 흐름대로 적용하여 실제 기술적 위험 관리와 신뢰도 분석에 적용 가능함을 확인하고 한다.

• Nuclear Engineering and Technology
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• 제50권5호
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• pp.627-638
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• 2018

This article describes an integrated Level 1-Level 2 probabilistic risk assessment (PRA) methodology to evaluate the radiological risk during postulated accident scenarios initiated during the decommissioning phase of a typical Mark I containment boiling water reactor. The fuel damage scenarios include those initiated while the reactor is permanently shut down, defueled, and the spent fuel is located into the spent fuel storage pool. This article focuses on the integrated Level 1-Level 2 PRA aspects of the analysis, from the beginning of the accident to the radiological release into the environment. The integrated Level 1-Level 2 decommissioning PRA uses event trees and fault trees that assess the accident progression until and after fuel damage. Detailed deterministic severe accident analyses are performed to support the fault tree/event tree development and to provide source term information for the various pieces of the Level 1-Level 2 model. Source terms information is collected from accidents occurring in both the reactor pressure vessel and the spent fuel pool, including simultaneous accidents. The Level 1-Level 2 PRA model evaluates the temporal and physical changes in plant conditions including consideration of major uncertainties. The goal of this article is to provide a methodology framework to perform a decommissioning Probabilistic Risk Assessment (PRA), and an application to a real case study is provided to show the use of the methodology. Results will be derived from the integrated Level 1-Level 2 decommissioning PSA event tree in terms of fuel damage frequency, large release frequency, and large early release frequency, including uncertainties.

• 한국물환경학회지
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• 제25권4호
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• pp.494-501
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• 2009

Probabilistic Ecological risk assessment (PERA) is extensive approach to qualify and quantify risk on the multi species based on species sensitivity distribution (SSD). As a while, deterministic ecological risk assessment (DERA) considers the comparison of predicted no-effect concentration (PNEC) and predicted exposure concentration (PEC). DERA is used to determine if there is potential risk or no risk, and it doesn't consider the nature variability and the species sensitivity. But PERA can be more realistic and reasonable approach to estimate likelihood or risk. In this study, we compared PERA used in developed countries, and proposed PERA applicable for the Korean water environment. Taxonomic groups were classified as "class" level including Actinopterygill, Branchiopoda, Chlorophyceae, Maxillapoda, Insects, Bivalvia, Gastropoda, Secernentea, Polychaeta, Monocotyldoneae, and Chanophyceae in this study. Statistical extrapolation method (SEM), statistical extrapolation method $_{acutechronicratio}$ ($SEM_{ACR}$) and assessment factor method (AFM) were used to calculate the ecological protective concentration based on qualitative and quantitative levels of taxonomic toxicity data. This study would be useful to establish the PERA for the protection of aquatic ecosystem in Korea.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.286-294
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• 2017

The events at the Fukushima Daiichi Nuclear Power Station in March 2011 point out, among other matters, that concurrent accidents at multiple units of a site can occur in reality. Although site risk has been deterministically considered to some extent in nuclear power plant siting and design, potential occurrence of multi-unit accident sequences at a site was not investigated in sufficient detail thus far in the nuclear power community. Therefore, there is considerable worldwide interest and research effort directed toward multi-unit site risk assessment, especially in the countries with high-density nuclear-power-plant sites such as Korea. As the technique of probabilistic safety assessment (PSA) has been successfully applied to evaluate the risk associated with operation of nuclear power plants in the past several decades, the PSA having primarily focused on single-unit risks is now being extended to the multi-unit PSA. In this paper we first characterize the site risk with explicit consideration of the risk associated with spent fuel pools as well as the reactor risks. The status of multi-unit risk assessment is discussed next, followed by a description of the emerging issues relevant to the multi-unit risk evaluation from a practical standpoint.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1210-1216
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• 2018

Site or multi-unit (MU) risk assessment has been a major issue in the field of nuclear safety study since the Fukushima accident in 2011. There have been few methods or experiences for MU risk assessment because the Fukushima accident was the first real MU accident and before the accident, there was little expectation of the possibility that an MU accident will occur. In addition to the lack of experience of MU risk assessment, since an MU nuclear power plant site is usually very complex to analyze as a whole, it was considered that a systematic method such as probabilistic safety assessment (PSA) is difficult to apply to MU risk assessment. This paper proposes a new MU risk assessment methodology by using the conventional PSA methodology which is widely used in nuclear power plant risk assessment. The logical failure structure of a site with multiple units is suggested from the definition of site risk, and a decomposition method is applied to identify specific MU failure scenarios.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1997년도 가을 학술발표회 논문집
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• pp.24-31
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• 1997

Recently, in Korea, demand for establishment of systematic risk assessment techniques for construction projects has increased, especially after the large construction failures occurred during construction such as New Haengju Bridge construction projects, subway construction projects, gas explosion accidents etc. Most of existing risk analysis modeling techniques such as Event Tree Analysis and Fault Tree Analysis may not be available for realistic risk assessment of construction projects because it is very complex and difficult to estimate occurrence frequency and failure probability precisely due to a lack of data related to the various risks inherent in construction projects like natural disasters, financial and economic risks, political risks, environmental risks as well as design and construction-related risks. Therefor the main objective of this paper is to suggest systematic probabilistic risk assessment model and demonstrate an approach for probabilistic risk assessment using advanced Event Tree Analysis introducing Fuzzy set theory concepts. It may be stated that the Fuzzy Event Tree AnaIysis may be very usefu1 for the systematic and rational risk assessment for real constructions problems because the approach is able to effectively deal with all the related construction risks in terms of the linguistic variables that incorporate systematically expert's experiences and subjective judgement.