• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.85-99
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• 2005

The main objective of this paper is to search whether containment vessel's best pressure may increase until how long when loss of coolant accident (LOCA) happened in containment vessel of Ulchin nuclear power plant 1 and 2. Another goal of this research is to find the influential factors that increase containment vessel pressure. Model for this research is Ulchin nuclear power plant 1 with 10 cycles. Data were collected by simulator of Ulchin nuclear power plant 1 and design of experiment was used for data analysis. For the experiment, seven factors that are going to influence in containment vessel pressure were chosen. It was found that fatter which influences in early rise of containment vessel pressure after LOCA is only explosion size. Also, containment vessel's best pressure (3.74 bar.a) was much lower than limit (4.86 bar.a) of FSAR (Final Safety Analysis Report).

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2670-2677
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• 2023

In the nuclear safety studies, a new trend refers to the evaluation of uncertainties as a mandatory component of best-estimate safety analysis which is a modern and technically consistent approach being known as BEPU (Best Estimate Plus Uncertainty). The major objectives of this study consist in performing a study of uncertainties/sensitivities of the major analysis results for a generic CANDU 6 Nuclear Power Plant during Station Blackout (SBO) progression to understand and characterize the sources of uncertainties and their effects on the key figure-of-merits (FOMs) predictions in severe accidents (SA). The FOMs of interest are hydrogen mass generation and event timings such as the first fuel channel failure time, beginning of the core disassembly time, core collapse time and calandria vessel failure time. The outcomes of the study, will allow an improvement of capabilities and expertise to perform uncertainty and sensitivity analysis with severe accident codes for CANDU 6 Nuclear Power Plant.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.814-826
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• 2023

Sensor faults in nuclear power plant instrumentation have the potential to spread negative effects from wrong signals that can cause an accident misdiagnosis by plant operators. To detect sensor faults and make accurate accident diagnoses, prior studies have developed a supervised learning-based sensor fault detection model and an accident diagnosis model with faulty sensor isolation. Even though the developed neural network models demonstrated satisfactory performance, their diagnosis performance should be reevaluated considering real-time connection. When operating in real-time, the diagnosis model is expected to indiscriminately accept fault data before receiving delayed fault information transferred from the previous fault detection model. The uncertainty of neural networks can also have a significant impact following the sensor fault features. In the present work, a pilot study was conducted to connect two models and observe actual outcomes from a real-time application with an integrated system. While the initial results showed an overall successful diagnosis, some issues were observed. To recover the diagnosis performance degradations, additive logics were applied to minimize the diagnosis failures that were not observed in the previous validations of the separate models. The results of a case study were then analyzed in terms of the real-time diagnosis outputs that plant operators would actually face in an emergency situation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2519-2528
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• 2022

The child pick-up behavior of parents during an emergency can cause heavy traffic congestion and failing to evacuate an affected area successfully. In this study, we analyzed the effect of child pick-up behavior using, as an example, a nuclear power plant accident caused by an earthquake, which is a typical no-notice emergency. A quake was assumed to occur near the Shin-Kori nuclear power plant in Ulsan, Korea, resulting in a nuclear power plant accident. An agent-based dynamic simulation model using VISSIM was employed to conduct sensitivity analyses with different child pick-up rates. The results confirmed that parents are a major cause of congestion and a vulnerable class in an emergency evacuation. The child pick-up behavior caused significant traffic congestion, and parents who pick up their children showed a higher evacuation failure rate.

• Journal of Power System Engineering
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• v.22 no.6
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• pp.5-10
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• 2018

Nuclear energy issues such as safety and social acceptance can not only influence the production costs of generating nuclear power, but also the external costs that are not reflected in market prices. Consequently, the social issues affiliated with nuclear power, beyond a severe accident, require some form of financial expense. The external social issues considered here are accident risk and realization, regulatory costs, and nuclear energy policy costs. Through several calculations and analyses of these external costs for nuclear power generation, it is concluded that these costs range from 7 to 27 \/kWh. Considering external costs are required for making energy plans, it could have an influence on generation costs.

• Nuclear Engineering and Technology
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• v.45 no.5
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• pp.597-604
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• 2013

Containment Filtered Vent Systems (CFVSs) have been mainly equipped in nuclear power plants in Europe and Canada for the controlled depressurization of the containment atmosphere under severe accident conditions. This is to keep the containment integrity against overpressure during the course of a severe accident, in which the radioactive gas-steam mixture from the containment is discharged into a system designed to remove the radionuclides. In Korea, a CFVS was first introduced in the Wolsong unit-1 nuclear power plant as a mitigation measure to deal with the threat of over pressurization, following post-Fukushima action items. In this paper, the overall features of a CFVS installation such as risk assessments, an evaluation of the performance requirements, and a determination of the optimal operating strategies are analyzed for the Wolsong unit 1 nuclear power plant using a severe accident analysis computer code, ISAAC.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.620-635
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• 2017

This study was intended to identify the main factors responsible for the decline in purchase of imported agricultural and fish products after Japan's nuclear power plant accident in 2011 and to compare the effects on imported agricultural produce and imported fish products. Logit model and multiple regression model analyses were performed using consumers' survey data. Psychological and qualitative factors reflecting consumers' food safety awareness and purchasing preferences, which were extracted by Factor analysis, were included as the models' explanatory variables, along with socio-demographic and economic factors. The Logit estimation showed aged, married, and low-income households had significantly higher probability of reducing their purchases of imported agricultural and fish products. However, the multiple regression results pointed out that the actual rate of decrease of imported agricultural and fish products purchases were more significantly affected by non-socio demographic factors such as past experience of purchasing imported agricultural and fish products, future intention to purchasing Japanese agricultural and fish products, and the ratio of imported to domestic agricultural and fish products before the nuclear accident, as well as consumers' feeling of food insecurity and their purchasing preferences. Moreover, the results showed that Korean consumers have reacted more sensitively to the decline in imported fish products than imported agricultural produce after the nuclear accident based on the marginal effects of various socio-demographic and economic factors.

• Nuclear Engineering and Technology
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• v.50 no.8
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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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• v.55 no.10
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• pp.3787-3800
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• 2023

Reactivity Initiated Accident (RIA) scenarios require special attention using advanced simulation techniques due to their complexity and importance for nuclear power plant (NPP) safety. While the conservative approach has traditionally been used for safety analysis, it may lead to unrealistic results which calls for the use of best estimate plus uncertainty (BEPU) approach, especially with the current advances in computational power which makes the BEPU analysis feasible. In this work an Uncontrolled Control Element Assembly (CEA) Withdrawal at Full Power accident scenario is analyzed using the BEPU approach by loosely coupling the thermal hydraulics best-estimate system code (RELAP5/SCDAPSIM/MOD3.4) to the statistical analysis software (DAKOTA) using a Python interface. Results from the BEPU analysis indicate that a realistic treatment of the accident scenario yields a larger safety margin and is therefore encouraged for accident analysis as it may enable more economic and flexible operation.