• 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.

• Journal of Radiation Protection and Research
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• v.41 no.4
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• pp.368-372
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• 2016

Background: Methodologies for a series of radiological consequence assessments show a distinctive difference according to the design principles of the original nuclear suppliers and their technical standards to be imposed. This is due to the uncertainties of the accidental source term, radionuclide behavior in the environment, and subsequent radiological dose. Both types of PWR and PHWR are operated in Korea. However, technical standards for evaluating atmospheric dispersion have been enacted based on the U.S. NRC's positions regardless of the reactor types. For this reason, it might cause a controversy between the licensor and licensee of a nuclear power plant. Materials and Methods: It was modelled under the framework of the NRC Regulatory Guide 1.145 for light-water reactors, reflecting the features of heavy-water reactors as specified in the Canadian National Standard and the modelling features in MACCS2, such as atmospheric diffusion coefficient, ground deposition, surface roughness, radioactive plume depletion, and exposure from ground deposition. Results and Discussion: An integrated accident consequence assessment code, ACCESS (Accident Consequence Assessment Code for Evaluating Site Suitability), was developed by taking into account the unique regulatory positions for reactor types under the framework of the current Korean technical standards. Field tracer experiments and hand calculations have been carried out for validation and verification of the models. Conclusion: The modelling approaches of ACCESS and its features are introduced, and its applicative results for a hypothetical accidental scenario are comprehensively discussed. In an applicative study, the predicted results by the light-water reactor assessment model were higher than those by other models in terms of total doses.

• Journal of the Korean Society of Safety
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• v.27 no.6
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• pp.192-204
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• 2012

For a severe accident of nuclear power plant, an approach to estimation of the radiological source term using a severe accident code(MELCOR) has been proposed. Although the MELCOR code has a capability to estimate the radiological source term, it has been hardly utilized for the radiological consequence analysis mainly due to a lack of understanding on the relevant function employed in MELCOR and severe accident phenomena. In order to estimate the severe accident source term to be linked with the radiological consequence analysis, this study proposes 4-step procedure: (1) selection of plant condition leading to a severe accident(i.e., accident sequence), (2) analysis of the relevant severe accident code, (3) investigation of the code analysis results and post-processing, and (4) generation of radiological source term information for the consequence analysis. The feasibility study of the present approach to an early containment failure sequence caused by a fast station blackout(SBO) of a reference plant (OPR-1000), showed that while the MELCOR code has an integrated capability for severe accident and source term analysis, it has a large degree of uncertainty in quantifying the radiological source term. Key insights obtained from the present study were: (1) key parameters employed in a typical code for the consequence analysis(i.e., MACCS) could be generated by MELCOR code; (2) the MELOCR code simulation for an assessment of the selected accident sequence has a large degree of uncertainty in determining the accident scenario and severe accident phenomena; and (3) the generation of source term information for the consequence analysis relies on an expert opinion in both areas of severe accident analysis and consequence analysis. Nevertheless, the MELCOR code had a great advantage in estimating the radiological source term such as reflection of the current state of art in the area of severe accident and radiological source term.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.659-664
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• 1998

The importance of input wariables of real-time accident consequence assessment model has been analyzed. Partial correlation coefficients of input variables related to the plume and the ingestion exposure have been estimated using latino hypercube sampling technique. It is known that wind speed and growth dilution rate are the most important variable in plume and ingestion exposure, respectively.

• Journal of the Ergonomics Society of Korea
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• v.22 no.1
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• pp.81-94
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• 2003

The British railway safety research group has developed a risk assessment model for the railway infrastructure and major railway accidents. The major hazardous factors of the railway infrastructure were identified and classified in the model. The frequency rates of critical top events were predicted by the fault tree analysis method using failure data of the railway system components and ratings of railway maintenance experts, The consequences of critical top events were predicted by the event tree analysis method. They classified the Joss of accident due to railway system into personal. commercial and environmental damages. They also classified 110 hazardous event due to railway system into three categories. train accident. movement accident and non-movement accident. The risk assessment model of the British railway system has been designed to take full account of both the high frequency low consequence type events (events occurring routinely for which there is significant quantity of recorded data) and the low frequency high consequence events (events occurring rarely for which there is little recorded data). The results for each hazardous event were presented in terms of the frequency of occurrence (number of events/year) and the risk (number of equivalent fatalities per year).

• 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.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.

• 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.

• 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 Korea Safety Management & Science
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• v.4 no.1
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• pp.49-56
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• 2002

In this case study, results of the explosion accident at MEK-PO factory were analysed by using the consequence analysis of quantitative hazard assessment and the explosion energy, the burst pressure of vessel, and overpressures at the explosion center and at 300m distance from the explosion center were estimated, respectively. As a result, we found that a cause of accident was the runaway reaction of product(MEK-PO) because of the molecular expansion in vessel and that the possibility of the runaway reaction was classified the mechanical failure(the obstacle of refrigerator or the shutdown valve), design error, and operating error by lack of thermochemical knowledge. Also, the evasive action to prevent accident was suggested.