• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.949-958
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• 2024

In contrast to all-time flooded small modular reactor (SMR) systems, an in-kind flooding safety system (FSS) has been proposed as a passive safety system applicable to small modular reactors (SMRs) that adopt a metal containment vessel (MCV). Under transient conditions, the FSS can provide emergency cooling to dry reactor cavities and sustain long-term coolability using re-acquired evaporated steam in the reactor building on demand. When designing an FSS, the effect of the flooding flow area is vital as it affects the overall accident sequence and safety. Therefore, in this study, a MELCOR model of a reference SMR is developed and numerical analysis is performed under postulated accident scenarios. Without flooding, the MCV pressure of the reactor module exceeds the design pressure before core damage. To prevent core damage, an emergency flooding strategy is devised using various flow path parameters and requirements to ensure an adequate emergency coolant supply before the core damage is investigated. The results indicate that a flow area exceeding 0.02 m2 is required in the FSS to prevent MCV overpressure and core damage. This study is the first to report a strategic analysis for appropriately sizing an FSS flooding valve applicable to innovative SMRs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.538-545
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• 2020

This study measured the economic impact (from 2012 through the end of 2017) of the KOR-USA FTA (Free Trade Agreement) on the Korean citrus industry according to importing orange from the USA after the implementation of the KOR-USA FTA. Citrus fruits were divided into field citrus grown in open fields, house citrus grown in green houses, and late-maturing citrus (including winter season citrus) based on the cultivation methods and the varieties of citrus. We specified the structural and dynamic recursive demand-supply equilibrium models of three citrus fruits to analyze policy simulations. The results showed that for field citrus, due to the impact of some amounts of TRQ, the annual average of the real gross revenue dropped by 2.39 billion KRW between 2012 and 2017. As for house citrus, due to the impact of oranges and cherries, the annual average of the real gross revenue declined by 3.01 billion KRW between 2012 and 2017, and for late-maturing citrus (including winter season citrus), the annual average of the real gross revenue fell by 15.11 billion KRW between 2012 and 2017. This paper also suggests several policy implications.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.131-138
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• 2019

The world's electricity production ratio is 40% for coal, 20% for natural gas, 16% for hydroelectric power, 15% for nuclear power and 6% for petroleum. Fossil fuels also cause serious problems in terms of price and supply because of the high concentration of resources on the earth. Solar energy is attracting attention as a next-generation eco-friendly energy that will replace fossil fuels with these problems. In this study, we test the charge-operation plan and the discharge operation plan for peak-cut operation by applying the maximum power demand reduction simulation. To do this, we selected the electricity usage from November to February, which has the largest amount of power usage, and applied charge / discharge logic. Simulation results show that the contract power decreases as the peak demand power after the ESS Peak-cut service is reduced to 50% of the peak-target power. As a result, the contract power reduction can reduce the basic power value of the customer and not only the economic superiority can be expected, but also contribute to the improvement of the electric quality and stabilization of the power supply system.

• World Technopolis Review
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• v.8 no.1
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• pp.59-70
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• 2019

Where is a better place to live? In the coming era, this should be more than simply a livable place. It should be an adaptable place that has a flexible system adaptable to any new situation in terms of diversity. Customization and real-time operation are needed in order to realize this technologically. We expect a smart city to have a flexible system that applies technologies of self-monitoring and self-response, thereby being a promising city model towards being a better place to live. Energy demand and supply is a crucial issue concerning our expectations for the flexible system of a smart city because it is indispensable to comfortable living, especially city living. Although it may seem that energy diversification, such as the energy mix of a country, is a matter of overriding concern, the central point is the scale of place to build grids for realizing sustainable urban energy systems. A traditional hard energy path supported by huge centralized energy systems based on fossil and nuclear fuels on a national scale has already faced difficult problems, particularly in terms of energy flexibility/resilience. On the other hand, an alternative soft energy path consisting of small diversified energy systems based on renewable energy sources on a local scale has limitations regarding stability, variability, and supply potential despite the relatively light economic/technological burden that must be assumed to realize it. As another alternative, we can adopt a holonic path incorporating an alternative soft energy path with a traditional hard energy path complimentarily based on load management. This has a high affinity with the flexible system of a smart city. At a system level, the purpose of all of the paths mentioned above is not energy itself but the service it provides. If the expected energy service is fixed, the conclusive factor in choosing a more appropriate system is accessibility to the energy service. Accessibility refers to reliability and affordability; the former encompasses the level of energy self-sufficiency, and the latter encompasses the extent of energy saving. From this point of view, it seems that the small diversified energy systems of a soft energy path have a clear advantage over the huge centralized energy systems of a hard energy path. However, some insuperable limitations still remain, so it is reasonable to consider both energy systems continuing to coexist in a multiplexing energy system employing a holonic path to create and maintain reliable and affordable access to energy services that cover households'/enterprises' basic energy needs. If this is embodied in a smart city concept, this is nothing else but smart energy inclusion. In Japan, following the Fukushima nuclear accident in 2011, a trend towards small diversified energy systems of a soft energy path intensified in order to realize a nuclear-free society. As a result, the Government of Japan proclaimed in its Fifth Strategic Energy Plan that renewable energy must be the main source of power in Japan by 2050. Accordingly, Sony vowed that all the energy it uses would come from renewable sources by 2040. In this situation, it is expected that smart energy inclusion will be achieved by the Japanese version of a smart grid based on the concept of a minimum cost scheme and demand response.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.275-285
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• 2013

As the world economy has been changed into the knowledge-based society, all economic activities have globalized and intensified competition in the marketplace, and the forces of these changes are even more aggressively pressuring today's business. According to many businesses are focused on the core competence and various functions are outsourced by service providers, many firms pay heavily attention to business service. Although the importance of business service, domestic business service industry shows a low labor productivity. On the other hand, foreign business service companies in korea take a substantial portion of business service market. Thus, domestic business service needs to increase a competitiveness because of potential growth opportunities. This study attempts to find out the ripple effect of business service industry on other industry.

• Journal of Service Research and Studies
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• v.6 no.4
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• pp.75-85
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• 2016

Coal can be divided into thermal coal and coking coal. The price of thermal coal is basically affected by demand and supply. However, many other factors with regard to economic condition such as exchange rate, economy growth rate also make an influence on the price. This study is targeted to develop a forecast model for thermal coal price by using System Dynamics Method. System dynamics provides results that better reflect the real world by employing an inter-dependent system of variables. This study found out that 8 factors have important influence on the thermal coal price. Most of the data of the variables were acquired from the Bloomberg Database. The period extends to 2 years and 4 months, from May of 2011 to August of 2013. The causal relations among the variables were acquired by regression analysis

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.12
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• pp.1980-1991
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• 2010

This study proposes the O P E N Triad framework as a future set of tools and perspectives for individual members and institutes to further their professional and academic potential as well as prospect and vitalize the future of the Korean Clothing and Textiles discipline through a global perspective. The millennial generation desires On-demand, Personal, Engaging, and Networked (O P E N) experiences effecting cultural change for creative and influential interaction in transactions, communication, and education. O P E N Individuals offers a WebSphere model as a holistic learning system that has a synergizing value of education across academic courses, industries, and cultures. Through a digitalized and virtualized class, it complements relevant technologies already familiar to the student population. By employing environmental scanning approaches, the most influential and viable future global issues related to the clothing and textiles discipline are identified and dialogued within O P E N Institutes. For future clothing and textiles institutes, this scanning allows them to be open to new ideas, to focus on inter-engagements, to collaborate among individuals, to associate as a part of web of people, organizations, and ideas, to personalize an institutes curricula, and to dialogue generative knowledge. O P E N Industries reveals three dominant future issues that cross academia and industry, sustainability, supply chain management, and social networking. In-depth interviews with U.S. industry experts identified interdependent gaps in global consumer experience practices and suggested the following gaps as future research areas: a standardized business model to the entrepreneurial model, strategic management to a sustainable competitive advantage, standardized to differentiated products, services and operations, market segmentation to global consumer clusters, business-driven marketplaces to consumer-engaged marketspaces, and excellent services to optimal experience. This O P E N Triad framework empowers millennial students, universities, and industries to anticipate and prepare for a radically changing world.

• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.560-571
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• 2015

This study aims to examine primary determinant for medical expenditure depending on different age and income brackets. The age and income brackets are simultaneously taken into account for a forming of structural models, and GARCH methodology is utilized in analyzing the model. Empirical evidence reveals that no matter how general medical care system is appropriately operated, medical expenditure is vulnerable in taking care of potential socially-disadvantaged class and the group of catastrophic medical expenditure as long as the age and income brackets concern, simultaneously. It signifies that more elaborately designed medical-related policy seems to be established to improve its effectiveness. On the contrary, ageing society is comparatively well-treated by public health law and act on long-term care insurance for the aged.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.153-160
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• 2020

Energy Consumption Predictions for Industries has a prominent role to play in the energy management and control system as dynamic and seasonal changes are occurring in energy demand and supply. This paper introduces and explores the steel industry's predictive models of energy consumption. The data used includes lagging and leading reactive power lagging and leading current variable, emission of carbon dioxide (tCO2) and load type. Four statistical models are trained and tested in the test set: (a) Linear Regression (LR), (b) Radial Kernel Support Vector Machine (SVM RBF), (c) Gradient Boosting Machine (GBM), and (d) Random Forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used for calculating regression model predictive performance. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model