• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1098-1108
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• 2019

Korea's first commercial nuclear power plant at Kori site was permanently shut down in 2017 and is currently in transition stage. Preparatory activities for decommissioning such as historical site assessment, characterization, and dismantling design are being actively carried out for successful D&D (Dismantling and Decontamination) at Kori site. The ultimate goal of decommissioning will be to ensure the safety of workers and residents that may arise during the decommissioning of nuclear facilities and, thereby finally returning the site to its original status in accordance with the release criteria. Upon completion of decommissioning, the resident's safety at a site released will be assessed from the evaluation of dose caused by radionuclides expected to be present or detected at the site. Although the U.S. commercial nuclear power plants with decommissioning experience use different site release criteria, most of them are 0.25 mSv/y. In Korea, both the unrestricted and restricted release criteria have been set to 0.1 mSv/y by the Nuclear Safety and Security Commission. However, since the dose is difficult to measure, measurable concentration guideline levels for residual radionuclides that result in dose equivalent to the site release criteria should be derived. For this derivation, site reuse scenario, selection of potential radionuclides, and systematic methodology should be developed in planning stage of Kori site decommissioning. In this paper, for calculation of a preliminary site-specific Derived Concentration Guideline Levels (DCGLs) for the Nuclear Power Plant site, a novel approach has been developed which can fully reflect practical reuse plans of the Kori site by taking into account multiple site reuse scenarios sequentially, thereby striking a remarkable distinction with conventional approaches which considers only a single site scenario.

• Fourth Industrial Review
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• v.1 no.1
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• pp.1-10
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• 2021

Purpose - This case study analyzes the internationalization strategy and innovation strategy as key factors contributing to the business success of CAP, a small and medium-sized manufacturing company in Korea producing auto parts such as wipers. This study describes the diversification strategies conducted by CAP Corporation and highlights the company's core competencies that have largely contributed to their global competitive success. Research design, data, and methodology - This paper provides in-depth case study on how CAP was able to grow into a hidden champion company, focusing on their strategies since its establishment. In particular, by analyzing the success factors centering on CAP's aggressive innovation strategy and internationalization strategy, it presents guidelines for small and medium-sized enterprises in Asian countries to become a Hidden Champion company. Result - CAP's product technology has successfully established innovative system on their product called 'vertebra spring' to distribute uniform pressure to the rubber to ensure performance as well as durability of their products. In order to continue benefiting from utilizing core competence and to continue pursuing technological advancement in the wiper industry, CAP has launched a wide range of products (flat blade, conventional blade, hybrid blade) applicable to 95% of the vehicle in the market. Conclusion - Taken together, CAP has many aspects of a hidden champion company by investing in R&D up to 8% of its annual sales to R&D investment even during the crises situation. This number is about 3.36 times higher than the average ratio of listed companies in Korea. Furthermore, the leadership of the management team as well as their vision toward the global market and strong commitment to innovation enabled CAP to become the world's fifth-largest wiper and Asia's No. 1 wiper manufacturer.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• Composites Research
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• v.35 no.3
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• pp.188-195
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• 2022

This paper proposes a multiscale process-structural analysis methodology and applies to a battery housing part made of the short fiber-reinforced and fabric-reinforced composite layers. In particular, uncertainties of the material properties within the microscale representative volume element (RVE) were considered. The random spatial distribution of matrix properties in the microscale RVE was realized by the Karhunen-Loeve Expansion (KLE) method. Then, effective properties of the RVE reflecting on spatially varying matrix properties were obtained by the computational homogenization and mapped to a macroscale FE (finite element) model. Morever, through the hybrid process simulation, a FE (finite element) model mapping residual stress and fiber orientation from compression molding simulation is combined with one mapping fiber orientation from the draping process simulation. The proposed method is expected to rigorously evaluate the design requirements of the battery housing part and composite materials having various material configurations.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of Korea Trade
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• v.26 no.3
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• pp.23-44
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• 2022

Purpose - Recent issues such as vessel enlargement, strengthening of environmental regulations, and port smartization are expected to increase costs and intensify competition in the port industry. In the new normal era, when external growth has reached its limit, the efficient operation of ports is becoming indispensable for achieving sustainable growth. This study aims to identify the determinants of inefficiency by examining the cost structure and efficiency of container terminals in Korea and furthermore propose the political implications to derive the maximization of efficiency. Design/methodology - This study estimates the cost function of container terminal operators and identifies the efficiency of container terminals using stochastic cost frontier (SCF) in the first stage. In the second step, the SCF results are compared with the data envelopment analysis (DEA). Last, this paper proposes efficiency determinants on container terminal operation to establish appropriate strategies. Out of the 29 container terminal operators in South Korea, 13 operators participated in the survey. The translog cost function was estimated utilizing a total of 116 observations collected over the 2007-2017 period. Findings - Empirical analysis shows that economies of scale exist in Korea's container ports, which provides a rationale for the government's policy to establish the global terminal operator by integrating small terminal operators to enhance competitiveness. In addition, as a result of the determinants analysis, container throughput, weight of direct employment costs, and labour cost share have positive effects on improving cost efficiency, while inefficiency increases as the length of quay increases. More specifically, cost efficiency improves as the proportion of direct employment costs to outsourcing service costs increases. Originality/value - This study contributes to analyzing the inefficiency factors of container terminals through efficiency analysis with respect to a cost function. In addition, this study proposes the practical and political implications, such as establishing a long-term manpower pool, the application of the hybrid liner terminal system, and the construction of a statistical data system, to improve the cost inefficiency of terminal operators.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.51-56
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• 2022

Purpose: By applying an ultrasonic mechanical device to the liquid fertilizer storage in the pig dropping treatment plant, the initial odor of the odor source is reduced, and the air dilution drainage of the complex odor is fundamentally recognized to facilitate odor treatment on the mechanical and chemical biological treatment devices at the rear. Research design, data and methodology: The odor concentration on the site boundary was measured to confirm the state of reduction. In order to prevent the spread of odor from the collection of the pig dropping treatment plant, it was measured by installing an ultrasonic generator inside the installation wall after installing the sealing wall. Results: The average value of the March and April measurement data remained close to neutral at 8.2 after 8.6 treatment before pH treatment, decreased 97.3% from 462 mg/L before SS treatment to 10.5 mg/L after treatment, and the composite odor was reduced by 85% from 20 to 3 before treatment. It was confirmed that ammonia (NH3) was reduced by 99% from 5.8 ppm to 0.09 ppm, and general bacteria were also reduced by 99% from 3,200 CFU/mL to 57 CFU/mL Conclusion: Applying the ultrasonic air ejector hybrid system and zigzag air complex module development product to resource circulation centers or sewage treatment facilities is thought to reduce inconvenience to residents due to odors caused.

• Nuclear Engineering and Technology
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• v.27 no.4
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• pp.571-581
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• 1995

The generation, verification and validation of Emergency Procedures for Nuclear Power Plant is a difficult and complex process. Atomic Energy Control Board(AECB) requires that emergency procedure and plan be produced before obtaining the Operating License, that is, detailed plans and procedures to handle emergency situations for both on-site actions and off-site actions be developed. In this report Emergency Operating Procedures Standard for Canadian Nuclear Utilities which makes reference to U. S. practices and the current direction of emergency procedures for CAN-DU reactors are reviewed and compared based on scope(events covered), methodology (event-oriented or symptom-oriented or hybrid) and format(method of presentation) preponderantly, and an attempt is made to integrate these procedures and as a result the recommended strategy for Wolsong unit 2, 3, & 4 is presented as event-specific procedures, generic procedures(when event is not diagnosed) and whose format is combination of logic diagram and text.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.420-426
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• 2024

This study proposes an innovative methodology for developing flexible printed circuit boards (FPCBs) capable of conforming to three-dimensional shapes, meeting the increasing demand for electronic circuits in diverse and complex product designs. By integrating a traditional flat plate-based fabrication process with a subsequent three-dimensional thermal deformation technique, we have successfully demonstrated an FPCB that maintains stable electrical characteristics despite significant shape deformations. Using a modified polyimide substrate along with Ag flake-based conductive ink, we identified optimized process variables that enable substrate thermal deformation at lower temperatures (~130℃) and enhance the stretchability of the conductive ink (ε ~30%). The application of this novel FPCB in a prototype 3D-shaped sensor device, incorporating photosensors and temperature sensors, illustrates its potential for creating multifunctional, shape-adaptable electronic devices. The sensor can detect external light sources and measure ambient temperature, demonstrating stable operation even after transitioning from a planar to a three-dimensional configuration. This research lays the foundation for next-generation FPCBs that can be seamlessly integrated into various products, ushering in a new era of electronic device design and functionality.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.