• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.166-173
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• 2022

A variety of input parameters are taken into consideration while performing a Level 3 PSA. Some parameters related to plume segments, spatial grids, and particle size distribution have flexible input formats. Fine modeling performed by splitting a number of segments or grids may enhance the accuracy of analysis but is time-consuming. Analysis speed is highly important because a considerably large number of calculations is required to handle Level 2 PSA scenarios for a single-unit or multi-unit Level 3 PSA. This study developed a sensitivity analysis supporting interface called MACCSsense to compare the results of the trials of plume segmentation with the results of the base case to determine its impact (in terms of time and accuracy) and to support the development of a modeling approach, which saves calculation time and improves accuracy. MACCSense is an automation tool that uses a large amount of plume segmentation analysis results obtained from MUST Converter and Mr. Manager developed by KAERI to generate a sensitivity report that includes impact (time and accuracy) by comparing them with the base-case result. In this study, various plume segmentation approaches were investigated, and both the accuracy and speed of offsite consequence analysis were evaluated using MACCS as a consequence analysis tool. A simultaneous evaluation revealed that execution time can be reduced using multi-threading. In addition, this study can serve as a framework for the development of a modeling strategy for plume segmentation in order to perform accurate and fast offsite consequence analyses.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.905-910
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• 2022

Drowsy driving requires a lot of social attention because it increases the incidence of traffic accidents and leads to fatal accidents. The number of accidents caused by drowsy driving is increasing every year. Therefore, in order to solve this problem all over the world, research for measuring various biosignals is being conducted. Among them, this paper focuses on non-contact biosignal analysis. Various noises such as engine, tire, and body vibrations are generated in a running vehicle. To measure the driver's heart rate and respiration rate in a driving vehicle with a piezoelectric sensor, a sensor plate that can cushion vehicle vibrations was designed and noise generated from the vehicle was reduced. In addition, we developed a system for classifying whether the driver is sleeping or not by extracting the model using the CNN-LSTM ensemble learning technique based on the signal of the piezoelectric sensor. In order to learn the sleep state, the subject's biosignals were acquired every 30 seconds, and 797 pieces of data were comparatively analyzed.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.317-318
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• 2022

In accordance with global decarbonization, optimization and productivity improvement using digital twin are being sought, and software development for optimizing ship and marine energy operation is accelerating by selecting digital twin as a future core technology. In order to reduce the operating cost of ships and strengthen the competitiveness of the shipbuilding industry due to the international strengthening of regulations on carbon emissions, it is necessary to predict the carbon emission of ships in advance and provide a carbon reduction operation solution. A plan was carried out for the development of open digital platform technology and the establishment of an environment to support the securing of carbon transparency of the ship and offshore system.

• Clean Technology
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• v.29 no.4
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• pp.321-326
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• 2023

Recently, there has been a growing interest in clean hydrogen energy that does not emit carbon dioxide during combustion due to the increasing focus on carbon neutral. Research related to hydrogen production continues, and in this study, we applied waste-derived synthesis gas to the water-gas shift reaction to simultaneously treat waste and produce high-purity hydrogen. To enhance catalytic activity in the high-temperature water-gas shift (HT-WGS) reaction, magnesium was used as a support material alongside cerium. Cu-CeO₂-MgO catalysts were synthesized, with copper acting as the active component for the HT-WGS reaction. A study on the catalytic activity based on the preparation method was conducted, and the Cu-CeO₂-MgO catalyst prepared by impregnation method exhibited the highest activity in the HT-WGS reaction. The observed superior performance of the Cu-CeO₂-MgO catalyst prepared through the impregnation method can be attributed to its significantly higher oxygen storage capacity and amount of active Cu species.

• Journal of Surface Science and Engineering
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• v.56 no.6
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• pp.437-442
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• 2023

This research aims to enhance the efficiency of Pt/C catalysts due to the limited availability and high cost of platinum in contemporary fuel cell catalysts. Nano-sized platinum particles were distributed onto a carbon-based support via the polyol process, utilizing the metal precursor H₂PtCl₆·6H₂O. Key parameters such as pH, temperature, and RPM were carefully regulated. The findings revealed variations in the particle size, distribution, and dispersion of nano-sized Pt particles, influenced by temperature and pH. Following sodium hydroxide treatment, heat treatment procedures were systematically executed at diverse temperatures, specifically 120, 140, and 160 ℃. Notably, the thermal treatment at 140 ℃ facilitated the production of Pt/C catalysts characterized by the smallest platinum particle size, measuring at 1.49 nm. Comparative evaluations between the commercially available Pt/C catalysts and those synthesized in this study were meticulously conducted through cyclic voltammetry, X-ray diffraction (XRD), and field-emission scanning electron microscopy-energy dispersive X-ray spectroscopy (FE-SEM EDS) methodologies. The catalyst synthesized at 160 ℃ demonstrated superior electrochemical performance; however, it is imperative to underscore the necessity for further optimization studies to refine its efficacy.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.147-159
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• 2024

Plutonium-238 has always been considered as the one of the promising radioisotopes for space nuclear power supply, which has long half-life, low radiation protection level, high power density, and stable fuel form at high temperatures. The industrial-scale production of ²³⁸Pu mainly depends on irradiating solid ²³⁷NpO₂ target in high flux reactors, however the production process faces problems such as large fission loss and high requirements for product quality control. In this paper, a conceptual design study of producing ²³⁸Pu in a multi-purpose high flux reactor was evaluated and analyzed, which includes a sensitivity analysis on ²³⁸Pu production and a further study on the irradiation scheme. It demonstrated that the target structure and its location in the reactor, as well as the operation scheme has an impact on ²³⁸Pu amount and product quality. Furthermore, the production efficiency could be improved by optimizing target material concentration, target locations in the core and reflector. This work provides technical support for irradiation production of ²³⁸Pu in high flux reactors.

• The Korean Journal of Food And Nutrition
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• v.37 no.3
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• pp.162-170
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• 2024

The domestic swine industry is currently facing a threat due to the recent increase in pork imports. This study aims to determine what factors influence consumers' intention to consume imported pork and suggest measures to support the domestic pork industry. To achieve this, we analyzed data from the Korea Rural Economic Institute's Food Consumption Behavior Survey using a binary logistic regression model. The results revealed that a higher intention to consume imported pork is linked to a higher intention to consume imported rice, purchasing meat online, frequent purchases of HMR, and procuring U.S. beef, especially among urban residents. On the other hand, a lower intention to consume imported pork is associated with a higher awareness of animal welfare certification, frequently dining out, and older age. Based on these findings, we propose the following response measures for the domestic swine industry: implementing educational programs, marketing, and advertising specifically targeting urban residents to improve their perception of domestic agricultural products; enhancing price competitiveness through distribution optimization; and developing policies to promote the use of domestic pork as an ingredient in processed foods.

• Advances in nano research
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• v.16 no.6
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• pp.623-638
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• 2024

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.382-393
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• 2024

The Microplotter system with a fluid dispensing method, sprays fluid based on ultrasonic pumping through piezoelectric devices. This technique can possible for various materials with a wide range of viscosities to be printed in microscale. In this paper, we introduces dispenser printing technology as well as aim to understand and apply various processes using the equipment. In addition, we will explain how to optimize the equipment by adjusting parameters such as spray intensity, tip height during printing, and patterning speed. By utilizing Microplotter's advantage of being compatible with a wide range of fluids, including metal nanoparticles, carbon nanotubes, DNA, and proteins, it is expected to be used in various fields such as printed electronics, biotechnology, and chemical engineering.