• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.632-637
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• 2017

Even though the potential for an accident in nuclear power plants is very low, multiple emergency plans are necessary because the impact of such an accident to the public is enormous. One of these emergency plans involves a robotic system for investigating accidents under conditions of high radiation and contaminated air. To develop a robot suitable for operation in a nuclear power plant, we focused on eliminating the three major obstacles that challenge robots in such conditions: the disconnection of radio communication, falling on uneven floors, and loss of localization. To solve the radio problem, a Wi-Fi extender was used in radio shadow areas. To reinforce the walking, we developed two- and four-leg convertible walking, a floor adaptive foot, a roly-poly defensive falling design, and automatic standing recovery after falling methods were developed. To allow the robot to determine its location in the containment building, a bar code landmark reading method was chosen. When a severe accident occurs, this robot will be useful for accident condition monitoring. We also anticipate the robot can serve as a workman aid in a high radiation area during normal operations.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1261-1270
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• 2022

This study was conducted to investigate the possibility of using gaze entropy to evaluate an operator's situation awareness in an emergency accident situation of a nuclear power plant. Gaze entropy can be an effective measure for evaluating an operator's situation awareness at a nuclear power plant because it can express gaze movement as a single comprehensive number. In order to determine the relationship between situation awareness and gaze entropy for an emergency accident situation of a nuclear power plant, an experiment was conducted to measure situation awareness and gaze entropy using simulators created for emergency accident situations LOCA, SGTR, SLB, and LOV. The experiment was to judge the accident situation of nuclear power plants presented in the simulator. The results showed that situation awareness and Shannon, dwell time, and Markov entropy had a significant negative correlation, while visual attention entropy (VAE) did not show any significant correlation with situation awareness. The results determined that Shannon entropy, dwell time entropy, and Markov entropy could be used as measures to evaluate situation awareness.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.579-588
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• 2022

In order to meet the needs of domestic reactor severe accident analysis program, a MIDAC (Module Invessel Degraded severe accident Analysis Code) is developed and maintained by Xi'an Jiaotong University. As the accuracy of the calculation results of the analysis program is of great significance for the formulation of severe accident mitigation measures, the article select three experiments to evaluate the updated severe accident models of MIDAC. Among them, QUENCH-06 is the international standard No.45, QUENCH-16 is a test for the analysis of air oxidation, and FROMA is an out-of-pile fuel rod melting experiment recently carried out by Xi'an Jiaotong University. The heating and melting model with lumped parameter method and the steam oxidation model with Cathcart-Pawel and Volchek-Zvonarev correlations combination in MIDAC could better meet the needs of severe accident analysis. Although the influence of nitrogen still need to be further improved, the air oxidation model with NUREG still has the ability to provide guiding significance for engineering practice.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.999-1008
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• 2023

Deformed fuel rods can cause a partial blockage of the flow area in a subchannel. Such flow blockage will influence the core coolant flow and further the core heat transfer during the reflooding phase and subsequent severe accidents. Nevertheless, most of the system analysis codes simulate the accident process based on the assumed flow blockage ratio, resulting in inconsistencies between simulated results and actual conditions. This paper aims to study the influence of flow blockage in severe accident scenario of the CAP1400 reactor. First, the flow blockage model of ISAA code is improved based on the FRTMB module. Then, the ISAA-FRTMB coupling system is adopted to model and calculate the QUENCH-LOCA-0 experiment. The correctness and validity of the flow blockage model are verified by comparing the peak cladding temperature. Finally, the DVI Line-SBLOCA accident is induced to analyze the influence of flow blockage on subsequent CAP1400 reactor core heat transfer and core degradation. From the results of the DVI Line-SBLOCA accident analysis, it can be concluded that the blockage ratio is in the range of 40%-60%, and the position of severe blockage is the same as that of cladding rupture. The blockage reduces the circulation area of the core coolant, which in turn impacts the heat exchange between the core and the coolant, leading to the early failure and collapse of some core assemblies and accelerating the core degradation process.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.723-730
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• 2019

Acquiring instrumentation signals generated from nuclear power plants (NPPs) is essential to maintain nuclear reactor integrity or to mitigate an abnormal state under normal operating conditions or severe accident circumstances. However, various safety-critical instrumentation signals from NPPs cannot be accurately measured on account of instrument degradation or failure under severe accident circumstances. Reactor vessel (RV) water level, which is an accident monitoring variable directly related to reactor cooling and prevention of core exposure, was predicted by applying a few signals to deep neural networks (DNNs) during severe accidents in NPPs. Signal data were obtained by simulating the postulated loss-of-coolant accidents at hot- and cold-legs, and steam generator tube rupture using modular accident analysis program code as actual NPP accidents rarely happen. To optimize the DNN model for RV water level prediction, a genetic algorithm was used to select the numbers of hidden layers and nodes. The proposed DNN model had a small root mean square error for RV water level prediction, and performed better than the cascaded fuzzy neural network model of the previous study. Consequently, the DNN model is considered to perform well enough to provide supporting information on the RV water level to operators.

• 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.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.464-470
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• 1997

Severe accident analysis has been performed for the Wolsung nuclear power plants in Korea to investigate severe accident phenomena of CANDU-600 reactors as a part of Level II PSA study. The accident sequence analyzed in this paper is loss of active heat sinks(LOAH) which is caused by loss of off-site power, diesel generators, and DC power. ISAAC (Integrated Severe Accident Analysis Code)computer code developed by KAERI (Korea Atomic Energy Research Institute) was used in this analysis. This paper describes the important thermal-hydraulics and source term behaviors in the primary system and inside containment, and the failure mechanism of calandria vessel and containment. In addition, some insights for accident management program(AMP) are also given.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.453-458
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• 2012

A major issue for all nuclear stakeholders is to keep the probability of circumstances that could lead to core damage as low as possible. In addition, for NPP, appropriate accident management provisions are to be implemented to limit the consequences associated with an accident. Development and application of L2 PSA is a structured way to demonstrate that such objectives are achieved. The paper presents the efforts recently done in Europe to harmonize some best-practices in that field, from research area to risk assessment. The Fukushima Daiichi accident reiterated the importance of these activities and the need to efficiently reinforce the NPP safety based on risk assessment conclusions. New perspectives in Europe are briefly presented.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.335-341
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• 1997

The generic analysis method for core flow instability is suggested to confirm that the core flow instability would not occur on PWR conditions. For the confirmation, the stability criteria of each fuel type are provided. Instability investigations in various accident conditions prove that the locked rotor accident is the most limiting case to instability. Parametric Effects are surveyed and in good agreement with available studies. The effects of heat flux distribution become negligible as the subcooling number is decreased. The power margin to instability is calculated quantitatively in various accident conditions.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.702-710
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• 2016

Global concern and interest in the safety of nuclear power plants have increased considerably since the Fukushima accident. In the event of a severe accident, the reactor vessel water level cannot be measured. The reactor vessel water level has a direct impact on confirming the safety of reactor core cooling. However, in the event of a severe accident, it may be possible to estimate the reactor vessel water level by employing other information. The cascaded fuzzy neural network (CFNN) model can be used to estimate the reactor vessel water level through the process of repeatedly adding fuzzy neural networks. The developed CFNN model was found to be sufficiently accurate for estimating the reactor vessel water level when the sensor performance had deteriorated. Therefore, the developed CFNN model can help provide effective information to operators in the event of a severe accident.