• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1254-1266
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• 2024

This study investigates the application of supercritical carbon dioxide (S-CO₂) direct-cycle micro modular reactors (MMRs) in primary frequency control (PFC), which is a scenario characterized by significant load fluctuations that has received less attention compared to secondary load-following. Using a modified GAMMA + code and a deep neural network-based turbomachinery off-design model, the authors conducted an analysis to assess the behavior of the reactor core and fluid system under different PFC scenarios. The results indicate that the acceptable range for sudden relative electricity output (REO) fluctuations is approximately 20%p which aligns with the performance of combined-cycle gas turbines (CCGTs) and open-cycle gas turbines (OCGTs). In S-CO₂ direct-cycle MMRs, the control of the core operates passively within the operational range by managing coolant density through inventory control. However, when PFC exceeds 35%p, system control failure is observed, suggesting the need for improved control strategies. These findings affirm the potential of S-CO₂ direct-cycle MMRs in PFC operations, representing an advancement in the management of grid fluctuations while ensuring reliable and carbon-free power generation.

• Journal of the Korean Society of Safety
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• v.11 no.2
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• pp.52-59
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• 1996

This paper presents a new approach for assessing the dynamic reliability in a complex system such as a nuclear power plant. The method is applied to a dynamic analysis of the potential accident sequences which may occur during mid-loop operation. Mid-loop operation is defined as an operation to make RCS water level below the top of the flow area of the hot legs at the junction with the reactor vessel for repairs and maintenance of steam generators and reactor coolant pumps for a specific time. The Idea behind this approach consists of both the use of the concept of the performance achievement/requirement correlation and of a dynamic event tree generation method. The assessment of the system reliability depends on the determination of both the required performance distribution and the achieved performance distribution. The quantified correlation between requirement and achievement represents a comparison between two competing variables. It is demonstrated that this method is easily applicable and flexible in that it can be applied to any kind of dynamic reliability problem.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.662-673
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• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

• Journal of Radiation Protection and Research
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• v.24 no.2
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• pp.73-86
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• 1999

The ion-exchange method for the purification of primary coolant has been used broadly in PWR(pressurized water reactor)-type nuclear power plants due to its high decontamination efficiency, simple system, and easy operation. However, its non-selective removal of metal and non-radionuclides shortens its life, resulting in the generation of a large amount of waste ion-exchange resin. In this study, the feasibility of electrodeionization (EDI) was investigated for the purification of primary cooling water using synthetic solutions under various experimental conditions as an alternative method for the ion exchange. The results shows that as the feed flow-rate increased, the removal efficiency increased and the power consumption decreased. The removal rate was observed as a 1000 decontamination factor(DF) at a nearly constant level. For the synthetic solution of 3 ppm TDS (Total Dissolved Solid), the power consumption was 40.3 mWh/L at 2.0 L/min of feed flow rate. The higher removal rate of metal species and lower power consumption were obtained with greater resin volume per diluting compartment. However, the flow rate of the EDI process decreased with the elapsed time because of the hydrodynamic resistivity of resin itself and resin fouling by suspended solids. Thus, the ion-exchange resin was replaced by an ion-conducting spacer in order to overcome the drawback. The system equipped with the ion-conducting spacer resolved the problem of the decreasing flow rate but showed a lower efficiency in terms of the power consumption, the removal rate of metal species and current efficiency. In the repeated batch operation, it was found that the removal efficiency of metal species was stably maintained at DF 1000.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.513-518
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• 1996

This report presents a demonstration of application of realistic evaluation methodology to a posturated cold leg large break LOCA in a Westinghouse three-loop pressurized water reactor with 17$\times$17 fuel. The new method of this analysis can be divided into three distinct step: 1) Best Estimate Code Validation and Uncertainty Quantification 2) Realistic LOCA Calculation 3) Limiting Value LOCA Calculation and Uncertainty Combination RELAP5/MOD3/K ［1］, which was improved from RELAP5/MOD3.1, and CONTEMPT4/MOD5 code were used as a best estimate thermal-hydraulic model for realistic LOCA calculation. The code uncertainties which will be determined in step 1) were quantified already in previous study ［2］, and thus the step 2) and 3) for plant application were presented in this paper. The application uncertainty parameters are divided into two categories, i.e. plant system parameters and fuel statistical parameters. Single parameter sensitivity calculations were performed to select system parameters which would be set at their limiting value in Limiting Value Approach (LVA) calculation. Single run of LVA calculation generated 27 PCT data according to the various combinations of fuel parameters and these data provided input to response surface generation. The probability distribution function was generated from Monte Carlo sampling of a response surface and the upper 95$^{th}$ percentile PCT was determined. Break spectrum analysis was also made to determine the critical break size. The results show that sufficient LOCA margin can be obtained for the demonstration NPP.

• Journal of Technology Innovation
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• v.25 no.2
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• pp.89-125
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• 2017

Complex product systems (CoPs) is a engineering-intensive products with high-ended design technology, which are closely linked with national economic growth and development of social infrastructures. Accordingly, in order to understand the technological evolution of CoPs, it is necessary to identify the macro-environmental drivers surrounding the CoPs and their impact on the technological evolution of the CoPS. Therefore, we investigate the effect of policy, economic and social drivers on the technological evolution of CoPS by implementing the longitudinal case study on nuclear power plant during the periods between 1950 and 2010s. Based on the analysis of various sources of secondary data and primary data through interviews, we found that the technological evolution of nuclear power plant is progressed as "Phase 1: Application research for peaceful utilization of nuclear energy" between 1950s and 1960s, "Phase 2: The first renaissance of nuclear energy" during 1970s, "Phase 3: Enhancement of safety and the catch-up of latecomers in nuclear energy" between 1990s and 2000s, and "Phase 4: Top prioritization of safety and the development of next generation reactors for the second renaissance of nuclear energy" since 2010s. We also found that various kinds of policy, economic and social drivers, such as energy policy, investment in technology development, economic growth and energy demand, social acceptability and environmental concern, have affected the technology evolution of nuclear power plant at each phase. We emphasize the role of macroenvironmental drivers in the technological evolution of CoPS. We also suggest that countries that endeavor to develop CoPs need to utilize those drivers for enhancing competitiveness and sustaining leadership.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Nuclear Engineering and Technology
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• v.40 no.3
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• pp.183-190
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• 2008

Pyroprocessing is the optimal means of treating spent metal fuels from metal fast fuel reactors and is proposed as a potential option for GNEP in order to meet the requirements of the next generation fuel cycle. Currently, efforts for research and development are being made not only in the U.S., but also in Asian countries. Electrorefining, cathode processing by distillation, injection casting for fuel fabrication, and waste treatment must be verified by the use of genuine materials, and the engineering scale model of each device must be developed for commercial deployment. Pyroprocessing can be effectively extended to treat oxide fuels by applying an electrochemical reduction, for which various kinds of oxides are examined. A typical morphology change was observed following the electrochemical reduction, while the product composition was estimated through the process flow diagram. The products include much stronger radiation emitter than pure typical LWR Pu or weapon-grade Pu. Nevertheless, institutional measures are unavoidable to ensure proliferation-proof plant operations. The safeguard concept of a pyroprocessing plant was compared with that of a PUREX plant. The pyroprocessing is better adapted for a collocation system positioned with some reactors and a single processing facility rather than for a centralized reprocessing unit with a large scale throughput.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2516-2533
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• 2023

Several practical methods for accelerating the depletion calculation in a GPU-based Monte Carlo (MC) code PRAGMA are presented including the multilevel spectral collapse method and the vectorized Chebyshev rational approximation method (CRAM). Since the generation of microscopic reaction rates for each nuclide needed for the construction of the depletion matrix of the Bateman equation requires either enormous memory access or tremendous physical memory, both of which are quite burdensome on GPUs, a new method called multilevel spectral collapse is proposed which combines two types of spectra to generate microscopic reaction rates: an ultrafine spectrum for an entire fuel pin and coarser spectra for each depletion region. Errors in reaction rates introduced by this method are mitigated by a hybrid usage of direct online reaction rate tallies for several important fissile nuclides. The linear system to appear in the solution process adopting the CRAM is solved by the Gauss-Seidel method which can be easily vectorized on GPUs. With the accelerated depletion methods, only about 10% of MC calculation time is consumed for depletion, so an accurate full core cycle depletion calculation for a commercial power reactor (BEAVRS) can be done in 16 h with 24 consumer-grade GPUs.