• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• Nuclear Engineering and Technology
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• v.50 no.8
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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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• v.53 no.11
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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.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3336-3346
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• 2022

In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2221-2229
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• 2020

After the Fukushima Daiichi nuclear power plant (NPP) accident, level 3 probabilistic safety assessment (PSA) has emerged as an important task in order to assess the risk level of the multi-unit NPPs in a single nuclear site. Accurate calculation of the radionuclide concentrations and exposure doses to the public is required if a nuclear site has multi-unit NPPs and large number of people live near NPPs. So, there has been a great need to develop a new method or procedure for the fast and accurate offsite consequence calculation for the multi-unit NPP accident analysis. Since the multi-unit level 3 PSA is being currently performed assuming that all the NPPs are located at the same position such as a center of mass (COM) or base NPP position, radionuclide concentrations or exposure doses near NPPs can be drastically distorted depending on the locations, multi-unit NPP alignment, and the wind direction. In order to overcome this disadvantage of the COM method, the idea of a new multiple location (ML) method was proposed and implemented into a new tool MURCC (multi-unit radiological consequence calculator). Furthermore, the MURCC code was further improved for the multi-unit level 3 PSA that has the arbitrary number of multi-unit NPPs. The objectives of this study are to (1) qualitatively and quantitatively compare COM and ML methods, and (2) demonstrate the strength and efficiency of the ML method. The strength of the ML method was demonstrated by the applications to the multi-unit long-term station blackout (LTSBO) accidents at the four-unit Vogtle NPPs. Thus, it is strongly recommended that this ML method be employed for the offsite consequence analysis of the multi-unit NPP accidents.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.4
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• pp.423-434
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• 2016

The importance of severe nuclear accidents and probabilistic safety assessment (PSA) were brought to international attention with the occurrence of severe nuclear accidents caused by the extreme natural disaster at Fukushima Daiichi nuclear power plant in Japan. In Korea, studies on level 3 PSA had made little progress until recently. The code systems of level 3 PSA, MACCS2 (MELCORE Accident Consequence Code System 2, US), COSYMA (COde SYstem from MAria, EU) and OSCAAR (Off-Site Consequence Analysis code for Atmospheric Releases in reactor accidents, JAPAN), were reviewed in this study, and the disadvantages and limitations of MACCS2 were also analyzed. Experts from Korea and abroad pointed out that the limitations of MACCS2 include the following: MACCS2 cannot simulate multi-unit accidents/release from spent fuel pools, and its atmospheric dispersion is based on a simple Gaussian plume model. Some of these limitations have been improved in the updated versions of MACCS2. The absence of a marine and aquatic dispersion model and the limited simulating range of food-chain and economic models are also important aspects that need to be improved. This paper is expected to be utilized as basic research material for developing a Korean code system for assessing off-site consequences of severe nuclear accidents.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.386-392
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• 2021

MACCS (MELCOR Accident Consequence Code System), WinMACCS, and MelMACCS now facilitate a multi-unit consequence analysis. MACCS evaluates the consequences of an atmospheric release of radioactive gases and aerosols into the atmosphere and is most commonly used to perform probabilistic safety assessments (PSAs) and related consequence analyses for nuclear power plants (NPPs). WinMACCS is a user-friendly preprocessor for MACCS. MelMACCS extracts source-term information from a MELCOR plot file. The current development can combine an arbitrary number of source terms, representing simultaneous releases from a multi-unit facility, into a single consequence analysis. The development supports different release signatures, fission product inventories, and accident initiation times for each unit. The treatment is completely general except that the model is currently limited to collocated units. A major practical consideration for performing a multi-unit PSA is that a comprehensive treatment for more than two units may involve an intractable number of combinations of source terms. This paper proposes and evaluates an approach for reducing the number of calculations to be tractable, even for sites with eight or ten units. The approximation error introduced by the approach is acceptable and is considerably less than other errors and uncertainties inherent in a Level 3 PSA.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.144-156
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• 2018

Level 3 Probabilistic Safety Assessment (PSA) is performed for the risk assessment that calculates radioactive material dispersion to the environment. This risk assessment is performed with a tool of MELCOR Accident Consequence Code System (MACCS2 or WinMACCS). For the off-site consequence analysis of multi-unit nuclear power plant (NPP) accident, the single location (Center Of Mass, COM) method has been usually adopted with the assumption that all the NPPs in the nuclear site are located at the same COM point. It was well known that this COM calculation can lead to underestimated or overestimated radionuclide concentration. In order to overcome this underestimation or overestimation of radionuclide concentrations in the COM method, Multiple Location (ML) method was developed in this study. The radionuclide concentrations for the individual NPPs are separately calculated, and they are summed at every location in the nuclear site by the post-processing of radionuclide concentrations that is based on two-dimensional Gaussian Plume equations. In order to demonstrate the efficiency of the ML method, radionuclide concentrations were calculated for the six-unit NPP site, radionuclide concentrations of the ML method were compared with those by COM method. This comparison was performed for conditions of constant weather, yearly weather in Korea, and four seasons, and the results were discussed. This new ML method (1) improves accuracy of radionuclide concentrations when multi-unit NPP accident occurs, (2) calculates realistic atmospheric dispersion of radionuclides under various weather conditions, and finally (3) supports off-site emergency plan optimization. It is recommended that this new method be applied to the risk assessment of multi-unit NPP accident. This new method drastically improves the accuracy of radionuclide concentrations at the locations adjacent to or very close to NPPs. This ML method has a great strength over the COM method when people live near nuclear site, since it provides accurate radionuclide concentrations or radiation doses.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.302-310
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• 2018

Despite the accident rate for fishing vessels accounts for 70% of all maritime accidents, few studies on such accidents have been done and most of the them mainly focus on causes and mitigation policies to reduce that accident rate. Thus, this risk analysis on sea accidents is the first to be performed for the successful and efficient implementation of accident reducing measures. In risk analysis, risk is calculated based on the combination of frequency and the consequence of an accident, and is usually expressed as a single number. However, there exists uncertainty in the risk calculation process if one uses a limited number of data for analysis. Therefore, in the study we propose a probabilistic simulation method to forecast risk not as a single number, but in a range of possible risk values. For the capability of the proposed method, using the criteria with the ALARP region, we show the possible risk values spanning across the different risk regions, whereas the single risk value calculated from the existing method lies in one of the risk regions. Therefore, a decision maker could employ appropriate risk mitigation options to handle the risks lying in different regions. For this study, we used fishing vessel accident data from 1988 to 2016.

• Nuclear Engineering and Technology
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• v.47 no.4
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• pp.461-471
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• 2015

Recently, the estimation of the social cost of energy sources has been emphasized as various novel energy options become feasible in addition to conventional ones. In particular, the social cost of introducing measures to protect power-distribution systems from power-source instability and the cost of accident-risk response for various power sources must be investigated. To account for these risk factors, an integrated societal risk assessment framework, based on power-uncertainty analysis and accident-consequence analysis, is proposed. In this study, we applied the proposed framework to nuclear power plants, solar photovoltaic systems, and wind-turbine generators. The required capacity of gas-turbine power plants to be used as backup power facilities to compensate for fluctuations in the power output from the main power source was estimated based on the performance indicators of each power source. The average individual health risk per terawatt-hours (TWh) of electricity produced by each power source was quantitatively estimated by assessing accident frequency and the consequences of specific accident scenarios based on the probabilistic risk assessment methodology. This study is expected to provide insight into integrated societal risk analysis, and can be used to estimate the social cost of various power sources.