• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.3
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• pp.332-344
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• 1996

The vertical profiles of the natural $^{210}Po,\;^{210}Pb\;and\;^{234}Th$, activities were measured at the upper 150 m or 200 m of water column from west-east intersection in the east-southern coastal area of the Korea Peninsula during the period from 26 to 29 April 1994 to compare the removal rates (residence time) and removal processes for $^{210}Po\;and\;^{234}Th$. At the inshore stations, the $^{210}Po$ activity was generally higher in the thermocline and its under layer than in the surface mixed layer, while represented the reversed pattern at the offshore stations. However, the $^{210}Pb$ activity decreased generally with depth. Also, the activity of $^{210}Po$ relative to its parent $^{210}Pb$ was deficient in the water column above the main thermocline, but was slightly excess or close to equilibrium in the thermocline and its under layer. The vertical profiles for the activity of $^{210}Pb$ relative to its parent $^{226}Ra$ showed the reversed pattern with the vertical variation of $^{210}Po$ excess (or deficiency). The $^{234}Th$ activity was significantly lower in the surface mixed layer and thermocline than in the deeper layer. The residence time of $^{210}Po$ ranged from 1 to 4 years at the five stations except station E8 that showed yet long residence time (approximately 10 years). The long residence time at the station E8 may resulted from the thicker surface mixed layer and subsequent the vertical mixing of $^{210}Po$ which was recycled in the lower surface mixed layer compared to at the other stations. Also, the residence time of $^{210}Po$ was shorter at the inshore stations than at the offshore stations. However, the residence time of $^{234}Th$ ranged from 52 to 74 days at all station without the significant variation, was very much shorter relative to the residence time of $^{210}Po$. The correlation between the removal rate of dissolved $^{234}Th$ and the concentration of total suspended matter (TSM) was generally positive. Therefore, it seems that the major route of the removal mechanism of $^{234}Th$ from seawater in the surface mixed layer is via adsorption onto suspended particle surfaces (most likely inorganic particles) and subsequent settling to the bottom layer. Between the removal rate of dissolved $^{210}Po$ and the concentration of chlorophyll-a was positively good correlation. Consequently, most likely the removal of $^{210}Po$ may be occurred by uptake to organisms (mainly such as planktonic debris or fecal pellets) and subsequent settling.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.29-40
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• 2010

Car simulation by TRANSIMS is able to rapidly analyze the broad area based on CA(Cellular Automata) theory, which is the great advantage compared to other existing programs. As the source code of TRANSIMS is open, it may be modified by incorporating the network and traffic characteristics. This study uses the traffic thematic map built in the Korean National Traffic DB(KTDB) center among input date used for building network data of TRANSIMS. However, because the traffic thematic map is not composed as the type required by TRANSIMS, it was corrected and complemented to build a network, and the traffic volume at arterial roads and the traffic volume at each direction of the intersection was calculated through simulation for the area of Suseong-Gu, Daegu Metro. This was compared to the actual traffic volume. As a result of the simulation, it shows error from 14% to 42% at intersection, and from 3% to 8% at arterial roads. This result is very satisfactory because the entire traffic volume of Daegu Metro was not considered, and the tendency of drivers avoiding path due to construction on certain section, the status of road surface and chronic congestion was not reflected.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.7
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• pp.1064-1072
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• 2001

It is very important to evaluate material degradation like temper and carbide embrittlements to secure the reliable and efficient operational conditions and to prevent brittle failure in service. The extent of material deterioration can be accurately evaluated by mechanical test such as impact test or creep test. But it is almost impossible to sample a large specimen from in-service plants. Thus, the material degradation evaluation by a non-destructive method is earnestly required. Recently the non-destructive test technique which uses the grain boundary etching characteristics owing to the variation of material structures has been proposed. However the program for material degradation evaluation using the grain boundary etching method(GEM) in Windows 98 domain doesnt be developed now. The aims of this paper are to develop the program and to complete the new master curve equations for the evaluation of material degradation on in-serviced high temperature components.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.115-122
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• 2012

Automobile collision analysis is composed of various shapes, and the speed variation working to the vehicle during collision are utilized as a very important factor in evaluating the degree of vehicle collision or passenger safety. So, the method of analyzing result values on the speed variation utilizing collision analysis program become necessary. This study utilized PC-Crash program in order to compare actual values and analyzed values of braking distance with the friction coefficient of road surface according to vehicle velocity. As a result, the smaller friction coefficient found to be larger error, and the maximum error range of collision velocity in case of each different vehicles (MATIZ, SONATA, or BUS) at the intersection showed 1.2%, 1.8%, 3.1% according to the difference of vehicle weight. Moreover, an accidental fall at IN-CHEON large bridge in order to reappear was verified with practicing simulation which has a slight error.

• Tunnel and Underground Space
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• v.14 no.3
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• pp.188-202
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• 2004

If an underground research facility for the validation of disposal concept is constructed in KAERI, it is expected to have a thick weathered zone and varying surface topology. In this study, the influence of different geological conditions, tunnel slope, tunnel size, and sequential excavation is investigated by 3D mechanical analysis using FLAC3D. Around the tunnel, it is not expected to develop any plastic zone and the maximum stress might be as high as 5 ㎫. The maximum compressive stress will be developed at about 20 m to e dead end of the tunnel. There is no difference on stress and displacement distributions between the cases with and without sequential excavation. It is expected to have stress release in the roof and floor after the excavation of the tunnel. There is no significant influence of weathered zone size, tunnel size, and tunnel slope on the stress and displacement distributions. The modeling for the intersection shows the minimum factor of safety is above 3, when the in situ stress ratio K is 3. From the study, it was possible to demonstrate that the small scale disposal research tunnel in KAERI will be mechanically stable.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.1-12
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• 2015

Intrusive Vehicle Detectors have excellent detection performance compared to other types of detector, but disadvantages of high installation and maintenance costs, short life time due to greater damage to roads and paving materials. In contrast, Non-Intrusive Vehicle Detectors attached to the stationary pole have advantages because it does not damage the road surface and easy and less expensive to maintain. Despite these advantages, Non-Intrusive type detectors are still not been widely used in traffic signal control systems because of the low detection performance. In this study, a FMCW(Frequency Modulated Continuous Wave) radar Vehicle Detector was designed as an alternative detector for the signalized intersection, and the performance evaluation was presented by purpose applicability.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.1
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• pp.67-81
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• 2000

An accurate and efficient numerical method for two-dimensional nonlinear radiation problem has been developed. The wave motion due to a moving body is described by the assumption of ideal fluid flow, and the governing Laplace equation can be effectively solved by the higher-order boundary element method with the help of the GMRES (Generalized Minimal RESidual) algorithm. The intersection or corner problem is resolved by utilizing the so-called discontinuous elements. The implicit trapezoidal rule is used in updating solutions at new time steps by considering stability and accuracy. Traveling waves caused by the oscillating body are absorbed downstream by the damping zone technique. It is demonstrated that the present method for time marching and radiation condition works efficiently for nonlinear radiation problem. To avoid the numerical instability enhanced by the local gathering of grid points, the regriding technique is employed so that all the grids on the free surface may be distributed with an equal distance. This makes it possible to reduce time interval and improve numerical stability. Special attention is paid to the local flow around the body during time integration. The nonlinear radiation force is calculated by the "acceleration potential technique". Present results show good agreement with other numerical computations and experiments.