• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.130-140
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• 2017

Background: With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. Materials and Methods: A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. Results and Discussion: The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.899-905
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• 1998

The analysis priority makings the recommendation to reduce the total core damage frequency (CDF) of Wolsong nuclear Power Plant nits 2/3/4 was Performed in this paper. In order to derive the recommendation, the sensitivity analysis of CDF on which major contributors effect m performed based on the accident quantification results during Level 1 Probabilistic safety assessment (PSA). Priorities were ranked in tile way that compares the CDF reduction rate with efforts required to implement those recommendations using risk matrix

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.509-521
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• 2021

In this paper, from a review of the size distribution of the bubbles during pool scrubbing obtained from experiments by EPRI, we apply the bubble size distributions to analyses on the decontamination factors of pool scrubbing via I-COSTA (In-Containment Source Term Analysis). We perform sensitivity studies of the bubble size on the various mechanisms of deposition of aerosol particles in pool scrubbing. We also perform sensitivity studies on the size distributions of the bubbles depending on the diameters at the nozzle exit, the molecular weights of non-condensable gases in the carrier gases, and the steam fractions of the carrier gases. We then perform analyses of LACE-ESPANA experiments and compare the numerical ~ results to those from SPARC-90 and experimental results in order to show the effect of the bubble size distributions.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Nuclear Engineering and Technology
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• v.35 no.2
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• pp.154-164
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• 2003

The explicit consideration of different pressurization rates in estimating the probabilities of containment failure modes has a profound effect on the confidence of containment performance evaluation that is so critical for risk assessment of nuclear power plants. Except for the sophisticated NUREG-1150 study, many of the recent containment performance analyses (through Level 2 PSAs or IPE back-end analyses) did not take into account an explicit distinction between slow and fast pressurization in their analyses. A careful investigation of both approaches shows that many of the approaches adopted in the recent containment performance analyses exactly correspond to the NUREG-1150 approach for the prediction of containment failure mode probabilities in the presence of fast pressurization. As a result, it was expected that the existing containment performance analysis results would be subjected to greater or less conservatism in light of the ultimate failure mode of the containment. The main purpose of this paper is to assess potential conservatism of a plant-specific containment performance analysis result in light of containment failure mode probabilities.

• Journal of the Korean Society of Safety
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• v.37 no.4
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• pp.129-138
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• 2022

A new method for injecting cooling water into the Korean research reactor (KRR) in the event of beam tube rupture is proposed in this paper. Moreover, the research evaluates the risk to the reactor core in terms of core damage frequency (CDF). The proposed method maintains the cooling water in the chimney at a certain level in the tank to prevent nuclear fuel damage solely by gravitational coolant feeding from the emergency water supply system (EWSS). This technique does not require sump recirculation operations described in the current procedure for resolving beam tube accidents. The reduction in the risk to the core in the event of beam tube rupture that can be achieved by the proposed change in the cooling water injection design is quantified as follows. 1) The total CDF of the KRR for the proposed design change is approximately 4.17E-06/yr, which is 8.4% lower than the CDF of the current design (4.55E-06/yr). 2) The CDF for beam tube rupture is 7.10E-08/yr, which represents an 84.1% decrease compared with that of the current design (4.49E-07/yr). In addition to this quantitative reduction in risk, the modified cooling water injection design maintains a supply of pure coolant to the EWSS tank. This means that the reactor does not require decontamination after an accident. Thermal hydraulic analysis proves that the water level in the reactor pool does not cause damage to the nuclear fuel cladding after beam tube rupture. This is because the amount of water in the chimney can be regulated by the EWSS function. The EWSS supplies emergency water to the reactor core to compensate for the evaporation of coolant in the core, thus allowing water to cover the fuel assemblies in the reactor core over a sufficient amount of time.

• Korean Journal of Food Science and Technology
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• v.37 no.3
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• pp.484-491
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• 2005

Quantitative microbial risk assessment (QMRA) analyzes potential hazard of microorganisms on public health and offers structured approach to assess risks associated with microorganisms in foods. This paper addresses specific risk management questions associated with Staphylococcus aureus in kimbab and improvement and dissemination of QMRA methodology, QMRA model was developed by constructing four nodes from retail to table pathway. Predictive microbial growth model and survey data were combined with probabilistic modeling to simulate levels of S. aureus in kimbab at time of consumption, Due to lack of dose-response models, final level of S. aureus in kimbeb was used as proxy for potential hazard level, based on which possibility of contamination over this level and consumption level of S. aureus through kimbab were estimated as 30.7% and 3.67 log cfu/g, respectively. Regression sensitivity results showed time-temperature during storage at selling was the most significant factor. These results suggested temperature control under $10^{\circ}C$ was critical control point for kimbab production to prevent growth of S. aureus and showed QMRA was useful for evaluation of factors influencing potential risk and could be applied directly to risk management.

• Korean Journal of Food Science and Technology
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• v.44 no.1
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• pp.106-113
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• 2012

The present study was conducted to assess the dietary exposure to mercury and the associated risks for Koreans resulting from their food intake. The probabilistic approach in the Monte Carlo simulation was used to estimate dietary exposures. Based on several reports regarding heavy metals published by KFDA in the 2000s, 178 types of representative foods were selected and data were collected on the occurrence of mercury. The contents of mercury in foods ranged: agricultural products 0.1 (fruits)-45.4 ${\mu}g/kg$ (mushrooms), 3.7 ${\mu}g/kg$ (meat), and 9.3 (Echinodermata, chordata)-194.9 ${\mu}g/kg$ (fish). Others categories investigated were alcoholic beverages (0.7 ${\mu}g/kg$) and processed food (4.4 ${\mu}g/kg$). The mean and 95th percentile for exposure to dietary mercury were 4.29 and 12.48 ${\mu}g/day$, corresponding to 13.6% and 39.7% of PTWI (Provisional Tolerable Weekly Intake), respectively. Therefore, overall level of mercury exposure for Koreans through food intake is below levels recommended by JECFA, indicating the least possibility of risk, and is less than or similar to levels reported in other countries.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.853-865
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• 2014

Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship need to be established to quantify various uncertainties associated modeling process and inputs. However, the systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, two major innovations are introduced to address this situation. The first is the use of a Hierarchical Bayesian model based regional frequency analysis to better convey uncertainties associated with the parameters of probability density function to the dam risk analysis. The second is the use of Bayesian model coupled HEC-1 rainfall-runoff model to estimate posterior distributions of the model parameters. A reservoir routing analysis with the existing operation rule was performed to convert the inflow scenarios into water surface level scenarios. Performance functions for dam risk model was finally employed to estimate hydrologic dam risk analysis. An application to the Dam in South Korea illustrates how the proposed approach can lead to potentially reliable estimates of dam safety, and an assessment of their sensitivity to the initial water surface level.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.