• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1381-1390
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• 2021

Smart grid is a representative convergence new technology in the era of the 4th industry revolution that deals with three broad security areas consisting of control system, the power grid, and the consumer. As it is a convergence new technology of the 4th industrial society, it is true that it can have a positive effect on the country's technological development, growth engine, and economic feasibility in the future. However, since the smart grid is expected to cause enormous damage in the event of a security accident, energy-related organizations must prepare various security measures to predict and respond to the latest security incidents. In this paper, the current status of domestic and foreign smart grids, trends in security standards, vulnerabilities and threats, and prospects for smart grid security technologies are to be considered.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2792-2800
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• 2022

In the core of the WWR-K reactor, a long-term irradiation of tristructural isotopic (TRISO)-coated fuel particles (CFPs) with a UO₂ kernel was carried out under high-temperature gas-cooled reactor (HTGR)-like operating conditions. The temperature of this TRISO fuel during irradiation varied in the range of 950-1100 ℃. A fission per initial metal atom (FIMA) of uranium burnup of 9.9% was reached. The release of gaseous fission products was measured in-pile. The release-to-birth ratio (R/B) for the fission product isotopes was calculated. Aspects of fuel safety while achieving deep fuel burnup are important and relevant, including maintaining the integrity of the fuel coatings. The main mechanisms of fuel failure are kernel migration, silicon carbide corrosion by palladium, and gas pressure increase inside the CFP. The formation of gaseous fission products and carbon monoxide leads to an increase in the internal pressure in the CFP, which is a dominant failure mechanism of the coatings under this level of burnup. Irradiated fuel compacts were subjected to electric dissociation to isolate the CFPs from the fuel compacts. In addition, nondestructive methods, such as X-ray radiography and gamma spectrometry, were used. The predicted R/B ratio was evaluated using the fission gas release model developed in the high-temperature test reactor (HTTR) project. In the model, both the through-coatings of failed CFPs and as-fabricated uranium contamination were assumed to be sources of the fission gas. The obtained R/B ratio for gaseous fission products allows the finalization and validation of the model for the release of fission products from the CFPs and fuel compacts. The success of the integrity of TRISO fuel irradiated at approximately 9.9% FIMA was demonstrated. A low fuel failure fraction and R/B ratios indicated good performance and reliability of the studied TRISO fuel.

• 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 the Korean Geotechnical Society
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• v.26 no.8
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• pp.59-66
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• 2010

In this study, an applicability by using the FEM was investigated for the prediction of both the depth of improvement and the vibration effect when dynamic compaction method is applied. The region was modelled by the field conditions applying dynamic compaction method and the rigid body force was applied to the dynamic load model. Predicted depth of improvement calculated by the vertical peak particle acceleration was compared and analyzed with an existing empirical equation, and the effect of groundwave by deducing the peak particle velocity from vibration sources was compared and analyzed with the results of another existing empirical equation. The results showed that the prediction of the depth of improvement has similar tendency to practice, and the vibration effect has some differences in a particular section from existing equation, but it could predict the safety distance to some degree. The analyzed results are expected to be basic data for the development of reliability of dynamic compaction design with existing empirical method.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.11-19
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• 2024

This paper was studied abouta technology for detecting damage to temporary works equipment used in construction sites with explainable artificial intelligence (XAI). Temporary works equipment is mostly composed of steel or aluminum, and it is reused several times due to the characters of the materials in temporary works equipment. However, it sometimes causes accidents at construction sites by using low or decreased quality of temporary works equipment because the regulation and restriction of reuse in them is not strict. Currently, safety rules such as related government laws, standards, and regulations for quality control of temporary works equipment have not been established. Additionally, the inspection results were often different according to the inspector's level of training. To overcome these limitations, a method based with AI and image processing technology was developed. In addition, it was devised by applying explainableartificial intelligence (XAI) technology so that the inspector makes more exact decision with resultsin damage detect with image analysis by the XAI which is a developed AI model for analysis of temporary works equipment. In the experiments, temporary works equipment was photographed with a 4k-quality camera, and the learned artificial intelligence model was trained with 610 labelingdata, and the accuracy was tested by analyzing the image recording data of temporary works equipment. As a result, the accuracy of damage detect by the XAI was 95.0% for the training dataset, 92.0% for the validation dataset, and 90.0% for the test dataset. This was shown aboutthe reliability of the performance of the developed artificial intelligence. It was verified for usability of explainable artificial intelligence to detect damage in temporary works equipment by the experiments. However, to improve the level of commercial software, the XAI need to be trained more by real data set and the ability to detect damage has to be kept or increased when the real data set is applied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4122-4131
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• 2014

The purpose of this study was to explore the features of virtual currency, which has become a hot topic recently. The characteristics of virtual currency were examined in terms of the effect on consumer acceptance. Therefore, when using the accepted model of the technology, the derived results should be analyzed by SEM. The research results showed that versatility and reliability affect the ease of use and safety is not have an effect. The utility did not have a direct effect on the attitudes and satisfaction, and the ease of use directly affects the ease of use, attitude and satisfaction. Finally, satisfaction with the attitude had a positive impact on the time of use. Effective strategies to manage the effect of the virtual currency will be possible to formulate from the results of this study.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.643-660
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• 2013

In the present work, the capacity ratings of steel truss bridges have been carried out incorporating dynamic effect of moving vehicles and its accumulating effect as fatigue. Further, corrosion in the steel members has been taken into account to examine the rating factor. Dynamic effect has been considered in the rating procedure making use of impact factors obtained from simulation studies as well as from codal guidelines. A steel truss bridge has been considered to illustrate the approach. Two levels of capacity ratings- the upper load level capacity rating (called operating rating) and the lower load level capacity rating (called inventory rating) were found out using Load and Resistance Factor Design (LRFD) method and a proposal has been made which incorporates fatigue in the rating formula. Random nature of corrosion on the steel member has been taken into account in the rating by considering reduced member strength. Partial safety factor for each truss member has been obtained from the fatigue reliability index considering random variables on the fatigue parameters, traffic growth rate and accumulated number of stress cycle using appropriate probability density function. The bridge has been modeled using Finite Element software. Regressions of rating factor versus vehicle gross weight have been obtained. Results show that rating factor decreases when the impact factor other than those in the codal provisions are considered. The consideration of fatigue and member corrosion gives a lower value of rating factor compared to those when both the effects are ignored. In addition to this, the study reveals that rating factor decreases when the vehicle gross weight is increased.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.406-414
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• 2014

In this paper, it is introduced characteristics of FMCW-type Radar Altimeter for KUH, and its defects occurred during ground/flight test in initial product phase. In addition, it is also described 'data/control flow model' based fault analysis results of S/W and processes of verifying improvement design through flight test as well as aircraft system integration test called MEP SIL. As a result of design improvement and verification, it is validated that settling the defects and improving not only safety but also capability of the KUH.

• The Journal of Engineering Geology
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• v.29 no.4
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• pp.417-425
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• 2019

Agricultural groundwater use accounts for 51.8% of total groundwater use, so accurate estimation of groundwater use is important for efficient groundwater management. The purpose of this study is to develop a method for estimating the groundwater use of agricultural (rice farming and dry-field farming) wells using regression tree model based on the measured data of 370 wells. Three input variables of the model were evaluated as being significant: well depth, pipe diameter, and pump capacity, and the importance of each variable was 75% for well depth, 17% for pipe diameter, and 8% for pumping capacity. The daily usage of agricultural (rice farming and dry-field farming) wells by the regression tree model was estimated to be very similar to the actual usage, compared to the previous estimation method proposed by the Ministry of Construction and Transportation. In the future, it is expected that the reliability of the usage statistics will be improved if additional observed data is secured and this classification method is modified.

• Fire Science and Engineering
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• v.27 no.6
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• pp.38-43
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• 2013

As a preliminary study to evaluate the reliability of the calculation method of fire load for residential furniture combustibles, the present study estimates the fire load considering the volume data obtained by the 3D geometrical information of combustibles and material properties based on the literature survey and sample burning test. A kitchen sink cabinet, couch and workstation were investigated for estimating its fire load and real fire test have been performed to measure total energy released from the combustibles. Based on total energy measured from real fire test, the relative error of the estimated fire load due to literature survey and measured material properties showed 6~120% and less than 20%, respectively. It shows that the estimation error of fire load are greatly affected by its material properties as well as geometrical information of combustibles and the present study will be able to contribute to accurate estimation of fire load.