• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.5 s.39
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• pp.65-77
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• 2004

In this study, the base isolation systems for equipment in the NPP are presented and the responses of each isolation system are investigated. As for the base isolation systems, a natural rubber bearing (NRB) and a high damping rubber bearing (HDRB) are selected. As input motions, artificial time histories enveloping the US NRC RG 1.60 spectrum and the probability-based scenario earthquake spectra developed for the Korean nuclear power plant site as well as a typical near-fault earthquake record are used. Uniaxial, biaxial, and triaxial excitations are conducted with PGAs of 0.1, 0.2 and 0.25g. The reduction of the seismic forces transmitted to the equipment models are determined for different isolation systems and input motions.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.13 no.1
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• pp.45-53
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• 2015

Since the commercial operation of Kori Unit #1 nuclear power plant(NPP) started in 1978, 23 units at present are operating in Korea. Radioactive wastes will be steadily generated from these units and accumulated. In addition, the life-extension of NPPs, construction of new NPPs and decontamination and decommissioning research facilities will cause radioactive wastes to increase. Recently, Korea has revised the new classification criteria as was proposed by IAEA. According to the revised classification criteria, low-level, very-low-level and exempt waste are estimated to about 98% of total disposal amount. In this paper, current status of overseas cases and disposal method with new classification criteria are analyzed to propose the most reasonable method for estimating the amount of decommissioning waste when applying the new criteria.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.1
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• pp.45-52
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• 2017

This study evaluated the durability of nuclear power plant concrete. The main parameters were the water-to-binder ratio and admixture type. The results revealed that high-volume ground granulated blast-furnace slag(GGBS) concrete had lower initial strength, while the strength reached higher after 28 days. On the other hand, the initial strength of fly ash blended concrete was high, but the long-term strength of the robbery was low. The measured durability of GGBS blended concrete was found to be better than that of the existing concrete mix for use in the construction of nuclear power plants. Especially, the GGBS blended concrete was more durable than the fly ash blended concrete in terms of chloride attack, carbonation resistivity and freezing-thawing durability in low compressive strength. The effects of concrete compressive strength according to gamma rays were minor.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.84-96
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• 2022

In the worst case, a temporary ignition source (also known as transient combustibles) between two electrical panels can damage both panels. Mitigation strategies for electrical panel fires were previously developed using fire modeling and risk analysis. However, since they do not comply with deterministic fire protection requirements, it is necessary to analyze the boundary values at which combustibles may damage targets depending on various factors. In the present study, a sensitivity analysis of input variables related to the damage threshold of two electrical panels was performed for dimensionless geometry using a Fire Dynamics Simulator (FDS). A new methodology using a damage evaluation map was developed to assess the damage of the electrical panel. The input variables were the distance between the electrical panels, the vertical height of the fuel, the size of the fire, the wind speed and the wind direction. The heat flux was determined to increase as the vertical distance between the fuel and the panel decreased, and the largest heat flux was predicted when the vertical separation distance divided by one half flame length was 0.3-0.5. As the distance between the panels increases, the heat flux decreases according to the power law, and damage can be avoided when the distance between the fuel and the panel is twice the length of the panel. When the wind direction is east and south, to avoid damage to the electrical panel the distance must be increased by 1.5 times compared to no wind. The present scale model can be applied to any configuration where combustibles are located between two electrical panels, and can provide useful guidance for the design of redundant electrical panels.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3717-3729
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• 2024

Accurately predicting evacuation time in a ventilated main control room (MCR) during fire emergencies is crucial for ensuring the safety of personnel at nuclear power plants. This study proposes to use neural networks alongside consolidated fire and smoke transport (CFAST) simulations to serve as a surrogate model for physics-based simulation tools. Our neural networks can promptly predict the evacuation time in MCRs, proving to be a valuable asset in fire emergencies and eliminating the need for time-consuming rollouts of the CFAST simulations. The CFAST model simulates fire and evacuation scenarios in a ventilated MCR with variations in input parameters such as door conditions, ventilation flow rate, leakage area, and fire propagation time. Target output parameters, such as hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD), are used alongside standardized evacuation variables to train a machine learning model for predicting evacuation time. The findings suggest that high ventilation flow rates help to dilute smoke and discharge hot gas, leading to lower target output parameters and quicker evacuation. Standardized evacuation variables exceed the required abandonment criteria for all door conditions, indicating the importance of proper evacuation procedures. The results show that neural networks can generate evacuation times close to those obtained from CFAST simulations.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.158-166
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• 2004

The optimal conditions are obtained for the decomposition of solid radioactive wastes, including ion exchange resin, zeolite, active charcoal, and sludge from nuclear power plant. In the process of decomposing the radioactive wastes were used the microwave acid digestion method with mixed acid. The solution after acid digestion by the following method was colorless and transparent. Each solution was analyzed with ICP-AES and AAS and the recovery yield for 5 different elements added the simulated radioactive wastes were over 94%. As an effective pre-treatment, the proposed microwave acid digestion conditions concerning the chemical trait of each radioactive waste are expected to be generally applied to above-mentioned radioactive wastes from nuclear power plant hereafter.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.421-426
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• 2009

The emissivity is different because the emitted angle changes according to the position of the infrared thermography camera and object. Because of this, the temperature distribution expressed when measuring the temperature by using the infrared thermography system is not the accuracy temperature. Although the real surface temperature is constant, the temperature measured by using infrared thermography camera have error in accordance with the value of emissivity. In this paper, the temperatures of the round cylindrical object and the flat square object that heated to the equal temperature were measured by infrared thermography camera. The emissivity calibration formula and correction table are made with the affect of the view angle and emission angle form the surface temperature value. The error of measured temperature values are corrected by using the emissivity calibration formula and correction table, and apply to defect detection of the nuclear power plant pipe. From the calibration method, reliability surface temperature values were obtained.

• Fire Science and Engineering
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• v.19 no.3 s.59
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• pp.20-27
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• 2005

This paper evaluates the fire safety level of eight pump rooms in the nuclear power plant using a fire model, CFAST We estimate the Conditional Core Damage Probability (CCDP) of each room based on the analyzed results of CFAST Eight rooms located on the primary auxiliary building of the nuclear power plant are high pressure safety injection pump room A/B, low pressure safety injection pump room Am. containment sprdy pump room A/B, and motor-driven auxiliary feed water pump room A/B. The upper layer gas temperature of each room is estimated and the integrity of cable is reviewed. Based on the results, the integrity of the cable located at the upper part of compartment is maintained without thermal damage. The Conditional Core Damage Probability Is reduced to half of the old values. Accordingly, the fire safety assessment for eight pump rooms using the fire model will be capable of reducing the uncertainty and to develop a more realistic model.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.6
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• pp.379-389
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• 2016

This study intends to evaluate the conservativeness of the fixed-base analysis as compared to the soil-structure interaction (SSI) analysis for the seismically isolated model of a nuclear power plant in Korea. To that goal, the boundary reaction method (BRM), combining frequency-domain and time-domain analyses in a twofold process, is adopted for the SSI analysis considering the nonlinearity of the seismic base isolation. The program KIESSI-3D is used for computing the reaction forces in the frequency domain and the program MIDAS/Civil is applied for the nonlinear time-domain analysis. The BRM numerical model is verified by comparing the results of the frequency-domain analysis and time-domain analysis for the soil-structure system with an equivalent linear base isolation model. Moreover, the displacement response of the base isolation and the horizontal response at the top of the structure obtained by the nonlinear SSI analysis using BRM are compared with those obtained by the fixed-base analysis. The comparison reveals that the fixed-base analysis provides conservative peak deformation for the base isolation but is not particularly conservative in term of the floor response spectrum of the superstructure.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.95-103
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• 2022

Quick and accurate understanding of the situation in a severe accident is essential for conducting the appropriate accident management and response using the accident diagnosis information. This study employed deep learning technology to diagnose severe accidents through the major safety parameters transferred from a nuclear power plant (NPP) to AtomCARE. After selecting the major accident scenarios to consider, a learning database was established for particular scenarios affiliated with major scenarios by performing a large number of severe accident analyses using MAAP5 code. The severe accident diagnosis technology, which classifies detailed accident scenarios using the major safety parameters from NPPs, was developed by training it with the established database . Verification and validation were conducted by blind test and principal component analysis. The technology developed in this study is expected to be extended and applied to all severe accident scenarios and be utilized as a base technology for quick and accurate severe accident diagnosis.