• 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.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1217-1233
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• 2018

Following a surge of interest in multi-unit risk in the last few years, many recent studies have suggested methods for multi-unit probabilistic safety assessment (MUPSA) and addressed several related aspects. Most of the existing studies though focused on two-unit nuclear power plant (NPP) sites or used rather simplified probabilistic safety assessment (PSA) models to demonstrate the proposed approaches. When considering an NPP site with three or more units, some approaches are inapplicable or yield very conservative results. Since the number of such sites is increasing, there is a strong need to develop and validate practical approaches to the related MUPSA. This article provides several detailed approaches that are applicable to multi-unit Level 1 PSA for sites with up to six or more reactor units. To validate the approaches, a multi-unit Level 1 PSA model is developed and the site core damage frequency is estimated for each of four representative multi-unit initiators, as well as for the case of a simultaneous occurrence of independent single-unit initiators in multiple units. For this purpose, an NPP site with six identical OPR-1000 units is considered, with full-scale Level 1 PSA models for a specific OPR-1000 plant used as the base single-unit models.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• 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.

• Nuclear Engineering and Technology
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• 제52권1호
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• pp.211-221
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• 2020

One fundamental element of probabilistic safety assessment (PSA) is the initiating event (IE) analysis. Since IE frequencies can change over time, time-trend analysis is required to obtain optimized IE frequencies. Accordingly, such time-trend analyses have been employed to estimate industry-average IE frequencies for use in the PSAs of U.S. nuclear power plants (NPPs); existing PSAs of Korean NPPs, however, neglect such analysis in the estimation of IE frequencies. This article therefore provides the method for and results of estimating Korean industry-average IE frequencies using time-trend analysis. It also examines the effects of the IE frequencies obtained from this study on risk insights by applying them to recently updated internal events Level 1 PSA models (at-power and shutdown) for an OPR-1000 plant. As a result, at-power core damage frequency decreased while shutdown core damage frequency increased, with the related contributions from each IE category changing accordingly. These results imply that the incorporation of time-trend analysis leads to different IE frequencies and resulting risk insights. The IE frequency distributions presented in this study can be used in future PSA updates for Korean NPPs, and should be further updated themselves by adding more recent data.

• 한국안전학회지
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• 제12권4호
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• pp.143-152
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• 1997

Probabilistic Safety Assessment(PSA) is an engineering analysis of the possible contributors to the risk from a nuclear power plant. It consist of three phases named as Level 1, 2 and 3. Level 1 PSA mainly focused in this paper is the phase of system analysis which includes the development of accident scenarios and the frequency estimation of each scenario. It covers also the system reliability analysis, component data analysis, and human reliability analysis. PSA have become a standard tool in safety evaluation of nuclear power plants. The main benefit of PSA is to provide insights into plant design, performance and environmental impacts, including the identification of dominant risk contributors and the comparison of options for reducing risk.

• 한국항해항만학회지
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• 제33권1호
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• pp.9-19
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• 2009

본 논문에서는 상선의 운항 사고에 관한 양적 위기평가에 관한 실험적인 접근방법들을 기술했다. 이 연구의 목적은 국제해사기구의 공식 안전성 평가(FSA)를 기반으로 운항 사고에 크게 기여하는 요소들을 분석하고, 양적 위기평가기법에 기반을 둔 운항 사고의 확률적인 위기수준을 평가한 후, 선박 안전을 저해할 수 있는 운항 사고 위기를 예측하는 것이다. 확률지수(PI)와 심각성지수(SI) 구성된 위기지수(RI)에 대한 운항 사고의 확률적인 위기수준은 베이지안 이론을 적용한 베이지안 네트워크를 기반으로 본 연구에서 제안한 운항사고 위기 모델을 이용해서 예측했다. 그리고 355건의 핵심 손상 사고기록으로 구성된 시나리오 그룹을 이용하여 제안한 모델의 적용 가능성을 평가하였다. 평가결과, 예측한 PI의 정답률 $r_{Acc}$은 82.8%로 나타났고, $S_p{\gg}1.0$과 $S_p{\ll}1.0$에 포함되는 PI 변수들의 민감도 초과비율은 10% 이내로 나타났으며, 예측한 SI의 평균 오차 $\bar{d_{SI}}$는 0.0195로 나타났고, 예측한 RI의 정답률은 91.8%로 나타났다. 이러한 결과는 제안한 모델과 방법이 실제 해상운송 현장에 적용 가능함을 나타낸다.

• Asian-Australasian Journal of Animal Sciences
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• 제32권2호
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• 한국안전학회지
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• 제33권5호
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• pp.157-163
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• 2018

This paper describes design improvement to a research rector for safety enhancement using Probabilistic Safety Assessment (PSA). This PSA under reactor design was undertaken to assess the level of safety for the design of a research reactor and to evaluate whether it is probabilistically safe to operate and reliable to use. The scope of the PSA reported here is a Level 1 PSA, which addresses the risks associated with the core damage. The technical objectives of this study were to identify accident sequences leading to core damage and to derive design improvement from the dominant accident sequences through the sensitivity analysis. The AIMS-PSA and FTREX were used for the this PSA of the research reactor. The criterion for inclusion was all sequences with a point estimate frequency greater than a truncation value of 1.0E-14/yr. The final result indicates a point estimate of 6.79E-05/yr for the overall Core Damage Frequency (CDF) attributable to internal initiating events for the research reactor under design. Based on the dominant accident sequences from the PSA, the seven kinds of sensitivity analysis were performed and some design improvement items were derived. When the five methods to improve the safety were all applied to the reactor design and emergency operating procedure, its risk was reduced to about 1.21E-06/yr from 6.79E-05/yr. The contribution of LOCA and LOEP with high CDF were significantly reduced by the sensitivity analysis. The safety of the research reactor was well improved and the risk was reduced than before adapting the design improvement gotten from the sensitivity analysis. The present study indicated that the research reactor has the well-balanced safety in regard to each initiating event contribution to CDF. The PSA methodology is very effective to improve reactor safety in a conceptual design phase and especially, Risk-informed design(RID) is very nice way to find the deficiencies of research reactor under design and to improve the reactor safety by solving them.

• 한국환경보건학회지
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• 제40권5호
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• pp.397-406
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• 2014

Objectives: Perchloroethylene (PCE) is a volatile chemical widely used as a solvent in the dry-cleaning and textile processing industries. It was evaluated as Group 2 "probably carcinogenic to humans" by the Integrated Risk Information System (IRIS) of the United State Environmental Protection Agency (U.S. EPA) in 2012. In order to provide a scientific basis for establishing risk management measures for chemicals on the national priority substances list, aggregate risk assessment was conducted for PCE, included in the top-10 substances. Methods: We conducted the investigation and monitoring of PCE exposure (e.g., exposure scenario, detection levels, and exposure factors, etc.) and assessed its multi-media (e.g., outdoor air, indoor air, and ground water) exposure risk with a deterministic and probabilistic approach. Results: In human risk assessment (HRA), the level of human exposure was higher in the younger age group. The exposure level through inhalation at home was the highest among the exposure routes. Outdoor air or uptake of drinking water represented less than 1% of total contributions to PCE exposure. These findings suggested that the level of risk was negligible since the Hazard Index (HI) induced by HRA was below one among all age groups, with a maximum HI value of 0.17 when reasonable maximum exposure was applied. Conclusion: In conclusion, it was suggested that despite low exposure risk, further studies are needed considering main sources, including occupational exposure.