• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.713-718
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• 1997

In the TMI-2 accident, approximately twenty(20) tons of molten core material drained into the lower plenum. Early advanced light water reactor (LWR) designs assumed a lower head failure and incorporated various measures for ex-vessel accident mitigation. However, one of the major findings from the TMI-2 Vessel Investigation Project was that one part of the reactor lower head wall estimated to have attained a temperature of 1100$^{\circ}C$ for about 30 minutes has seemingly experienced a comparatively rapid cooldown with no major threat to the vessel integrity. In this regard, recent empirical and analytical studies have shifted interests to such in-vessel retention designs or strategies as reactor cavity flooding, in-vessel flooding and engineered gap cooling of the vessel Accurate thermohydrodynamic and creep deformation modeling and rupture prediction are the key to the success in developing practically useful in-vessel accident/risk management strategies. As an advanced in-vessel design concept, this work presents the COrium Attack Syndrome Immunization Structures (COASIS) that are being developed as prospective in-vessel retention devices for a next-generation LWR in concert with existing ex-vessel management measures. Both the engineered gap structures in-vessel (COASISI) and ex-vessel (COASISO) are demonstrated to maintain effective heat transfer geometry during molten core debris attack when applied to the Korean Standard Nuclear Power Plant(KSNPP) reactor. The likelihood of lower head creep rupture during a severe accident is found to be significantly suppressed by the COASIS options.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.124-133
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• 2017

In-vessel retention by passive external reactor vessel cooling under severe accident conditions is a viable approach for retention of radioactive core melt within the reactor vessel. In this study, a new and versatile coating technique known as "cold spray" that can readily be applied to operating and advanced reactors was developed to form a microporous coating on the outer surface of a simulated reactor lower head. Quenching experiments were performed under simulated in-vessel retention by passive external reactor vessel cooling conditions using test vessels with and without cold spray coatings. Quantitative measurements show that for all angular locations on the vessel outer surface, the local critical heat flux (CHF) values for the coated vessel were consistently higher than the corresponding CHF values for the bare vessel. However, it was also observed for both coated and uncoated surfaces that the local rate of boiling and local CHF limit vary appreciably along the outer surface of the test vessel. Nonetheless, results of this intriguing study clearly show that the use of cold spray coatings could enhance the local CHF limit for downward-facing boiling by > 88%.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05d
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• pp.438-442
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• 1996

The design of the vacuum vessel of KT-2(a large-aspect-ratio, mid-size tokamak) is presented. The KT-2 vacuum vessel provides necessary environments to contain a plasma of double-null configuration with elongation of up to 1.8. The vacuum vessel is designed as an all-metal welded structure. Eddy currents are induced on the vessel during all stages of the plasma operation. Influences of the continuous vessel on the plasma were investigated. No significant effect of the vessel on the plasma in every aspect of null formation, plasma initiation, plasma control was found. Stresses and deformations in the vessel by atmospheric pressure and electromagnetic forces due to the eddy currents were calculated using 3D FEM code.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.373-380
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• 2014

Safety-related parameters are very important for confirming the status of a nuclear power plant. In particular, the reactor vessel water level has a direct impact on the safety fortress by confirming reactor core cooling. In this study, the reactor vessel water level under the condition of a severe accident, where the water level could not be measured, was predicted using a fuzzy neural network (FNN). The prediction model was developed using training data, and validated using independent test data. The data was generated from simulations of the optimized power reactor 1000 (OPR1000) using MAAP4 code. The informative data for training the FNN model was selected using the subtractive clustering method. The prediction performance of the reactor vessel water level was quite satisfactory, but a few large errors were occasionally observed. To check the effect of instrument errors, the prediction model was verified using data containing artificially added errors. The developed FNN model was sufficiently accurate to be used to predict the reactor vessel water level in severe accident situations where the integrity of the reactor vessel water level sensor is compromised. Furthermore, if the developed FNN model can be optimized using a variety of data, it should be possible to predict the reactor vessel water level precisely.

• 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.

• 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.1
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• pp.180-189
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• 2023

We measured the heat load to a reactor vessel with and without the in-vessel debris bed under an IVR-ERVC condition. Mass transfer methodology was adopted based on heat and mass transfer analogy to achieve high Ra'_H of order ~10¹⁵ with compact test rigs. We postulated the in-vessel debris bed has a flat top and particulate debris was simulated as an identical diameter spheres. We conducted experiments varying the height of the debris bed and the results showed that Nusselt numbers decreased in both uppermost and curved surfaces with the increasing bed height. Once the debris bed is formed, it acts as an obstacle to the natural convective flow, which reduces the buoyancy. The reduction of driving force results in the impaired heat transfer in both upward and downward heat transfers.

• Nuclear Engineering and Technology
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• v.28 no.6
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• pp.576-582
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• 1996

The integrity of reactor vessel support system of the Korean Standard Nuclear Power Plant (KSNPP) is investigated for a postulated reactor vessel closure head drop event. The closure head is disassembled from the reactor vessel during refueling process or general inspection of reactor vessel and internal structures, and carried to proposed location by the head lift rig. A postulated closure head drop event could be anticipated during closure head handling process. The drop event may cause an impact load on the reactor vessel and supporting system. The integrity of the supporting system is directly relevant to that of reactor vessel and reactor internals including fuels. Results derived by elastic impact analysis, linear and non-linear buckling analysis and elasto-plastic stress analysis of the supporting system implied that the integrity of the reactor vessel supporting system is intact for a postulated reactor vessel closure head drop event.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1244-1248
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• 2003

This paper describes visual tracking procedure of the underwater mobile robot for nuclear reactor vessel inspection, which is required to find the foreign objects such as loose parts. The yellowish underwater robot body tends to present a big contrast to boron solute cold water of nuclear reactor vessel, tinged with indigo by Cerenkov effect. In this paper, we have found and tracked the positions of underwater mobile robot using the two color information, yellow and indigo. The center coordinates extraction procedures are as follows. The first step is to segment the underwater robot body to cold water with indigo background. From the RGB color components of the entire monitoring image taken with the color CCD camera, we have selected the red color component. In the selected red image, we extracted the positions of the underwater mobile robot using the following process sequences; binarization, labelling, and centroid extraction techniques. In the experiment carried out at the Youngkwang unit 5 nuclear reactor vessel, we have tracked the center positions of the underwater robot submerged near the cold leg and the hot leg way, which is fathomed to 10m deep in depth.