• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.329-338
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• 2019

Suction of unsaturated bentonite buffers is a very important input parameter for hydro-mechanical performance assessment and design of an engineered barrier system. This study analyzed suction measurement techniques and constitutive models of unsaturated porous media reported in the literature, and suggested suction measurement techniques and constitutive models suitable for bentonite buffer in an HLW repository. The literature review showed the suction of bentonite buffer to be much higher than that of soil, as measured by total suction including matric suction and osmotic suction. The measurement methods (RH-Cell, RH-Cell/Sensor) using a relative humidity sensor were suitable for suction measurement of the bentonite buffer; the RH-Cell /Sensor method was more preferred in consideration of the temperature change due to radioactive decay heat and measurement time. Various water retention models of bentonite buffers have been proposed through experiments, but the van Genuchten model is mainly used as a constitutive model of hydro-mechanical performance assessment of unsaturated buffers. The water characteristic curve of bentonite buffers showed different tendencies according to bentonite type, dry density, temperature, salinity, sample state and hysteresis. Selection of water retention models and determination of model input parameters should consider the effects of these controlling factors so as to improve overall reliability.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.193-204
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• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.333-359
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• 2021

Gases such as hydrogen and radon can be generated around the canister in high-level radioactive waste disposal systems due to several reasons including the corrosion of metal materials. When the gas generation rate exceeds the gas diffusion rate in the low-permeability bentonite buffer, the gas phase will form and accumulate in the engineered barrier system. If the gas pressure exceeds the gas entry pressure, gas can migrate into the bentonite buffer, resulting in pathway dilation flow and advective flow. Because a sudden occurrence of dilation flow can cause radionuclide leakage out of the engineered barrier of the radioactive waste disposal system, it is necessary to understand the gas migration behavior in the bentonite buffer to quantitatively evaluate the long-term safety of the engineered barrier. Experimental research investigating the characteristics of gas migration in saturated bentonite and research developing numerical models capable of simulating such behaviors are being actively conducted worldwide. In this technical note, previous gas injection experiments and the numerical models proposed to verify such behaviors are introduced, and the future challenges necessary for the investigation of gas migration are summarized.

• The Mathematical Education
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• v.61 no.4
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• pp.521-537
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• 2022

The unprecedented COVID-19 pandemic has disrupted, interrupted, and changed the way we normally prepare our teacher candidates in teacher preparation programs. In this paper, we, two mathematics teacher educators (MTEs), reflect our own experiences in appropriating, transforming, reconstructing, and modifying our pedagogies of teacher education in making a transition from face-to-face to online environment during the COVID-19 pandemic. Using a collaborative self-study, we discussed issues, challenges, changes, opportunities, and innovations of teaching an elementary mathematics methods course in the online environment. Using a constant comparison method, we explored the following three themes: (1) using virtual manipulatives; (2) creating collaborative, interactive, and shared learning experiences for preservice teachers; and (3) making preservice teachers engaged in student thinking. These findings indicated that online teaching requires transformative knowledge for teacher educators. Transferring face-to-face to online is not a simple matter of putting the existing content to online; it should focus on pedagogical improvement in teaching mathematics rather than technology's sake or how it can be repurposed in a new online environment in a way that students' learning is optimized. The findings of this study provide implications for unpacking MTEs' technological pedagogical content knowledge (TPACK), creating collaborative learning experiences for preservice teachers, and designing a collaborative self-study between MTEs engaged in the community of professional learning.

• Journal of the Korean GEO-environmental Society
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• v.12 no.1
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• pp.41-50
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• 2011

Three-dimensional(3D) numerical analyses have been conducted to study the behaviour of a single pile to adjacent tunnelling conducted in the lateral direction of the pile. In the numerical analyses, the interaction between the tunnel, the pile and the soil next to the pile has been analysed. The study includes the pile settlement, the relative shear displacement between the pile and the soil, the shear stresses at the soil next to the pile and the axial force on the pile. In particular, the shear stress transfer mechanism along the pile related to the tunnel advancement has been rigorously analysed. Due to changes in the relative shear displacement between the pile and the soil next to the pile during the tunnel advancement, the shear stress and the axial force distributions along the pile have been changed. Downward shear stress developed above the tunnel springline (Z/L=0.0-0.7~0.8), while upward shear stress is mobilised below the tunnel springline (Z/L=0.7~0.8-1.0) resulting in compressive force on the pile, where Z is the pile location and L is the pile length. Maximum compressive force of about $0.475P_a$ was developed on the pile after completion of tunnel advancement, where $P_a$ is the allowable pile capacity. Some insights into the pile behaviour to tunnelling obtained from the numerical analyses will be reported and discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.153-160
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• 2022

This study presents the bogie arrangement of the load-out system for on-ground shipbuilding. The load-out system is one of the most important systems to perform the bogie arrangement of the on-ground shipbuilding technique without dry dock facilities, and this system is composed of four pieces of equipment: bogies, driving bogie with motors, trestles, and power packs. Also, the bogie arrangement analysis (BAA) is employed to simply calculate the reaction forces at the trestle for structural safety. In this context, the purpose of this study is to propose an optimal design method to perform the bogie arrangement satisfying structural safety requirements with minimal cost. It is expected that the proposed methodology will contribute to the effective practice as well as to the improvement of competitive capability for shipbuilding companies at the on-ground shipbuilding stage. Furthermore, we describe some problems and their solutions of the deformation that may occur in the bottom of the hull during the load-out process. As a result, it is shown that we applied it to the 114K crude oil tanker (Minimum bogie 54EA) and the 174K CBM LNG carrier (Minimum bogie 88EA), it can minimize the number of bogie and critical risks (Safety rate 1.61) during the load-out of on-ground shipbuilding. Through this study, the reader will be able to learn successful load-out operation and economic shipbuilding in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.6
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• pp.371-383
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• 2021

Steel-concrete single-leaf blast-resistant doors, having steel box and slab inside, are installed on the wall using supporting members such as hinges and latches. Several studies have been conducted on their deflection behavior in the same direction as that of the blast pressure, but studies on their deflection behavior in the opposite direction, that is, studies on negative deflection behavior are relatively insufficient. In this study, we conducted a parameter analysis using finite element analysis on blast-resistant doors, on their rebound behavior in the negative deflection phase. Results revealed that the plastic deformation of the door, and the change in momentum and kinetic energy during rebound, were major factors influencing the rebound behavior. Greater rebound force was developed on the supporting members in the impulsive region, than in the quasi-static region; due to the characteristics in the impulsive region, where the kinetic energy developed relatively greater than the strain energy. In the design process, it is necessary to consider excessive deformation that could occur in the supporting members as the rebound behavior progresses. Additionally, it was found that in the case of steel-concrete blast doors, the rebound force increased relatively more, when the effects of both rebound and negative blast pressure contributed to the negative deflection of the door. Since conditions for the occurrence of this superposition effect could vary depending on structural characteristics and explosion conditions, further investigation may be required on this topic.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.92-99
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• 2021

Light-scattering fine particulate matter monitors can measure particulate matter (PM) concentrations in every second and can be designed in a portable size. They can measure the concentrations of various PM sizes (PM_1.0, PM_2.5, PM_4.0 and PM₁₀) with a single sensor. They measure the number and size of particulate matters and convert them to weight per volume (concentration). These devices show a large error for asian dust. This paper proposes a scheme that compensates the PM_2.5 concenstration error for asian dust by multiple linear regression machine learning in light-scattering PM monitors. This scheme can be effective with only two or three types of PM sizes. The experimental results compare a beta-ray PM monitor of national institute of environmental research and a light-scattering PM monitor during a month. The correlation coefficient (R²) of theses two devices was 0.927 without asian dust, but it was 0.763 due to asian dust during the entire experimental period and improved to 0.944 by the proposed machine learning.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.41-52
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• 2022

Education for an organization is implemented to improve the organizational and each individual's performance. However, the actual results are not as expected. Accordingly, this study is committed to investigate the education related factors that have impact on the organizational performance, which is defined by the trainee's organizational commitment and work performance. Based on the acquired knowledge, we suggest things to consider when designing corporate training for performance creation. First, it is investigated whether the task value and job relevance(educational content characteristics) and the degree of support for education within the company(organizational characteristics) affect learning-transfer of trainees. After that, the causal relationship from the learning-transfer to organizational commitment and work performance(organizational effectiveness) is analyzed. In this overall process, the effect of on-/off-line education is analyzed and compared. As a result, it is found that the task value, the job relevance, and organizational compensation have a significant impact on the learning-transfer, and the learning-transfer has impact on organization commitment and work performance. In addition, the moderating effect of the on-/off- education is identified. This study is conducted only with franchise enterprises and as a future study, a more general sampling is required to extend this work.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.273-282
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• 2023

Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.