• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.4
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• pp.333-340
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• 2001

This paper presents a calculating method for inductance of the Switched Reluctance Motor(SRM) for torque characteristics and driving by analytical model. The torque generating characteristics of the SRM depend on the phase current and the inductance variation features, but Its nonlinear magnetic characteristics make it difficult to calculating inductance. Recently, The approaches for calculating inductance have taken vary from detailed finite element method(FEM) and Fitting method in magnetization curves using complex nonlinear magnetic circuit models. But those methods have not satisfactory approach for machine performance calculations, because of having a long time and remodeling for analyses, therefore thus an alternative approach is required. So it is suggested simply calculating method of the inductance based on designed data of machinery by analytical model in unaligned and aligned rotor. In order to prove the calculating, there are compare with analytical FEM. direct measurement, this method, and simulation. The compared result is shown to obtain good accuracy.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.2
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• pp.40-46
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• 1989

Recently, the researches on cutting the new material have been done for development of aerospace industrial engineering. Especially, titanium ally is well known as heat resisting, antiwear, anticorrosion and difficult-to-machine materials. Many studies on the analysis of shear angle have been done for improving productivity in cutting these materials. In case of titanium alloy, the saw-toothed type of chip which has wave surface of a triangular form, an eccentric from of a continuous type of chip that is produced in the cutting process, was checked. Nakayama supposed that a maximum shear strewss plane and the shear crack in the free surface made an angle of $45^{\circ}$ .deg. , but it's usually much larger than that. In this paper, the author analyzed the shear conditions of the cutting process in the quick-stopping device with the help SEM-photographs, and measured the hypotenuse angle directly in the photographs of the chips. In conclusion, the author tried to find the shear angle in the cutting process with the saw-toothed chip and compared it with the shear angles which can be calculated from the theories established by others. The results obtained are as follows. 1. In case of the saw-toothed chips, the equivalent cutting ratio can be calculated by using the chip thickness to two-thirds of ramp height. 2. The theory of Ernst-Merchant is not applicable to the titanium and its alloys which does not fractured in accordance with the theory of maximum shear stress. 3. When we cut the titanium alloys which produced the saw-toothed chips, the shear angle can be found with the theories of Rowe-Spick, P.K. Wright and the measurement of hypotenuse angle.

• Progress in Medical Physics
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• v.29 no.2
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• pp.66-72
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• 2018

The proper position of a multi-leaf collimator (MLC) is essential for the quality of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) dose delivery. Task Group (TG) 142 provides a quality assurance (QA) procedure for MLC position. Our study investigated the QA validation of the mechanical leaf gap measurement and the maintenance procedure. Two $VitalBeam^{TM}$ systems were evaluated to validate the acceptance of an MLC position. The dosimetric leaf gaps (DLGs) were measured for 6 MV, 6 MVFFF, 10 MV, and 15 MV photon beams. A solid water phantom was irradiated using $10{\times}10cm^2$ field size at source-to-surface distance (SSD) of 90 cm and depth of 10 cm. The portal dose image prediction (PDIP) calculation was implemented on a treatment planning system (TPS) called $Eclipse^{TM}$. A total of 20 VMAT plans were used to confirm the accuracy of dose distribution measured by an electronic portal imaging device (EPID) and those predicted by VMAT plans. The measured leaf gaps were 0.30 mm and 0.35 mm for VitalBeam 1 and 2, respectively. The DLG values decreased by an average of 6.9% and 5.9% after mechanical MLC adjustment. Although the passing rates increased slightly, by 1.5% (relative) and 1.2% (absolute) in arc 1, the average passing rates were still within the good dose delivery level (>95%). Our study shows the existence of a mechanical leaf gap error caused by a degenerated MLC motor. This can be recovered by reinitialization of MLC position on the machine control panel. Consequently, the QA procedure should be performed regularly to protect the MLC system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1110-1116
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• 2017

Depending on the operating characteristics, track circuit is installed for the purpose of direct or indirect control of the signal device, point switch machine and other security device. These are mainly used for train detection, transmission of information, broken rail detection and transmission of return current. Especially, the return current is related to signal system, power system and catenary line, and track circuit systems. It is one of the most important component shall be dealt for the safety of track side staff and for the protection of railway-related electrical system according to electrification. Therefore, an accurate analysis of the return current is needed to prevent the return current unbalance and the system induced disorder and failure due to an over current condition. Also, if the malfunction occurred by the return current harmonics, it can cause problems including train operation interruption. In this paper, we presented measurement and analysis method at return current and it's harmonics by high speed train operation on the honam high speed line.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.373-378
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• 2002

Metal matrix composites have a great interest in recent years because high specific strength, high specific stiffness characteristics, and application ranges of the composites are extend to variety industry. In this paper, an investigation was performed on the plane strain fracture toughness and slinding wear properties of AC4CH alloy(Al-Si-Mg line) reinforced with 20wt% aluminum borate whisker expect one, which contained a inorganic binder($TiO_2$). the binder led to the formation of strengthen the whisker each other. The test of fracture toughness was using CT(half size) specimen of thickness 12.5mm, width 25mm. and test of slinding wear of using tribo a pin-on-disk machine and lubricant is used without paraffine 8.2CST at room temperature. As results, Fracture toughness $K_{IC}$ is $8.7MPa-m^{05}$ for ABOw/AC4CH, $9.28MPa-m^{05}$ for ABOw/AC4CH added $TiO_2$. but AC4CH alloy was violated the critical stipulated by ASTM standard for valid measurement of $K_{IC}$. In case of, it was performed $J_{IC}$ test instead of $K_{IC}$ based on ASTM E 1820.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• The Journal of Engineering Geology
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• v.32 no.3
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• pp.363-376
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• 2022

An area under construction for a living facility collapsed around 12:48 KST on 13 January 2021 in Sa-dong, Ansan-si, Gyeonggi-do. There were no casualties due to the rapid evacuation measure, but part of the temporary retaining facility collapsed, and several cracks occurred in the adjacent road on the south side. This study used the potential of synthetic aperture radar (SAR) satellite for surface property changes that lies in backscattering characteristic to map the collapsed structure. The interferometric SAR technique can make a direct measurement of the decorrelation among different acquisition dates by integrating both amplitude and phase information. The damage proxy map (DPM) technique has been employed using four high-resolution Constellation of Small Satellites for Mediterranean basin Observation (COSMO-SkyMed) data spanning from 2020 to 2021 during ascending observation to analyze the collapse of the construction. DPM relies on the difference of pre- and co-event interferometric coherences to depict anomalous changes that indicate collapsed structure in the study area. The DPMs were displayed in a color scale that indicates an increasingly more significant ground surface change in the area covered by the pixels, depicting the collapsed structure. Therefore, the DPM technique with SAR data can be used for damage assessment with accurate and comprehensive detection after an event. In addition, we classify the amplitude information using support vector machine (SVM) and maximum likelihood classification algorithms. An investigation committee was formed to determine the cause of the collapse of the retaining wall and to suggest technical and institutional measures and alternatives to prevent similar incidents from reoccurring. The report from the committee revealed that the incident was caused by a combination of factors that were not carried out properly.

• Design & Manufacturing
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• v.17 no.3
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• pp.48-54
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• 2023

In this study, an injection mold with ultra-small surface properties was manufactured using nanosecond laser processing. A superhydrophobic characteristic analysis was performed on the PET specimen manufactured through this. To this end, a hydrophobic pattern was defined using the Cassie-Baxter model. The defined features were selected with a spot diameter of 25um and pitch spacing of 30um and 35um. As a result of the basic experiment, it was confirmed that the fine pattern shape had an aspect ratio of 1:1 when the pitch interval was 35um and 20 iterations. Through the determined processing conditions, a hydrophobic pattern was implemented on the core surface of KP4. A specimen with a hydrophobic pattern was produced through injection molding. The height of the molded hydrophobic pattern is 20 ㎛ less than the depth of the core and the contact angle measurement results are 92.1°. This is a contact angle smaller than the superhydrophobic criterion. Molding analysis was performed to analyze the cause of this, and it was analyzed that the molding was not molded due to the lack of pressure in the injection machine.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.9
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• pp.1632-1642
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• 1992

When a blind hole of small diameter is drilled in the field of residual stress, strain relieved around the hole is function of magnitude of stress, patterns of stress distribution and hole geometry of diameter and depth. Relieved strain coefficients can be calculated from FEM analysis of relieved strain and actual stress. These relieved strain coefficients make it possible to measure residual stress which vary along the depth in the subsurface of stressed material. In this study, the calibration tests of residual stress measurement are carried out by drilling a hole incrementally on the cantilever or on the tensile test bar. Residual stresses can be determined from measured strains around a shallow hole by application of power series method. For the sake of reliable measurement of residual stress, much efforts should be done to measure relieved strains and hole depth more accurately comparing with conventional procedures of gage subject to the external load. Otherwise linear equations converting strains into stresses may yield erratic residual stresses because of ill-conditions of linear equations. With accurate measurements of relieved strains, residual stress even if varying along the depth can be measured. It is also possible to measure residual stress in the thin film of material by drilling a shallow hole.