• Proceedings of the KSR Conference
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• 2002.05a
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• pp.597-602
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• 2002

This study reviews several of the procedures that have been used to predict ground-born vibration. The vibration responses are measured at three sites that have different soil qualities. The measured vibration levels are compared with the predicted results by previously used vibration level prediction models. In this study a numerical method, which is based on explicit differential method, is used to compensate tot existing prediction models. Although numerically computed results are not quantitatively in good agreement with the measured results, the trends are comparable in the sense that vibration level does not decrease monotonically with distance. Also, The site with the deepest tunnel gives the highest vibration level.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.198-200
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• 2009

This paper presents the numerical simulation results on the moving type electrodynamic suspension (EDS) simulator. Superconducting EDS system is generated by the interaction between the magnetic field made by the induced the eddy current in the ground conductor and the moving magnetic field made by onboard superconducting magnet. The levitation force of EDS system, which is proportional to the strength of the moving magnetic field, becomes saturated according to the increase of the velocity Especially, the levitation force is influenced by the structure of HTS magnet and ground conductor. The 3-D numerical analysis with FEM was used to find the distribution of the magnetic field, the optimal coil structure, and the calculation of the levitation force.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.583-584
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• 2005

In this work, a novel hybrid FL sensor consisting of two Rogowski coils has been designed for the installation on the ground wire of the transmission tower. The operation range of these coils is as follows: 30kA for the fault current comingfrom the ground fault or short-circuit and for the lightning current up to 150kA over 500kHz. Thus, two important functions could be provided: one is to detect the fault current and the other one is to find the fault location between towers or the location of induced lightning stroke. The on-site investigation at 800kV test yard has been under progress for its on-site application.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.358-365
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• 2006

In this study, fragility curves of continuous buried pipelines subjected to transverse PGD (permanent ground deformation) due to liquefaction are proposed. For the waterworks system, continuos buried pipelines made of ductile iron, poly ethylene, and poly vinyl chloride are analyzed and fragility curves are drawn. Fragility curves are based on the repetitive analyses results and formulated with the dominant factors of behaviour of buried pipeline. With the use of fragility curves, engineers can estimate the status of damage of buried pipeline without overall knowledge of relevant features. Especially, fragility curves proposed in this study will act as a major module of earthquake loss estimation method. Moreover, critical value of magnitude and width of transverse PGD (by which the full damage status of buried pipelines are induced) are estimated. With the use of regression curves of these values, pre evaluation of seismic safety of buried pipelines located within liquefaction hazardous region will be possible.

• Journal of Ship and Ocean Technology
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• v.12 no.3
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• pp.14-25
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• 2008

Recently, there has been a serious effort to design a wing in ground effect (WIG) craft. Vehicles of this type might use low aspect ratio wings defined as those with smaller than 3. Design and prediction techniques for fixed wings of relatively large aspect ratio are reasonably well developed. However, Aerodynamic problems related to vortex lift on wings of low aspect ratio have made it difficult to use existing techniques. In this work, we firstly focus on understanding aerodynamic characteristics of low aspect ratio wings and comparing the results from experimental measurements and currently available numerical predictions for both inviscid and viscous flows. Second, we apply an improved numerical method, "B-spline based high panel method with wake roll-up modeling", to the same problem.

• Journal of the Korean Geotechnical Society
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• v.31 no.10
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• pp.49-60
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• 2015

Since previous studies on the 3-dimensional earth pressure have been conducted focusing on the stability of wall, it is very difficult to find a study on the load transfer to the adjacent ground induced by the 3-dimensional active displacement. Therefore, in this study, we tried to find out the load transfer to the adjacent ground induced by the 3-dimensional active displacement depending on the size of rectangular wall which was defined by the aspect ratio, that is, the ratio of the height to the width of the wall. 3-dimensional model tests were performed in order to measure the distribution and the magnitude of load transfer to surrounding grounds. The transferred load was 17.9~30.6% less than the difference between the 3-dimensional active earth pressure and earth pressure at rest. The transferred load of both vertical and horizontal was maximum at the boundary of the active wall. The load transfer range depended on the normalized height of the active wall, and it was 0.67~1.29w in horizontal direction and 1.0~3.0h in vertical direction. The transferred load in horizontal was maximum at the height of the wall. As the aspect ratio increases the location of the maximum transferred load points becomes higher. The ratio of the transferred load area of 56~79% at 0.25w in horizontal direction and 50~58% at 1.0~1.5 in vertical direction. Diagrams showing the distribution and the magnitude of the transferred load depending on the aspect ratio were suggested.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.493-502
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• 2016

This study examines how rock condition affects the variation of the chargeability and electrical resistivity of the rock. In the theoretical study, the relationship correlating chargeability with the variables affecting it is derived. A parametric study utilizing the derived relationship reveals that the size of narrow pores ($r_1$) is the most influential factor on chargeability, and the salinity of pore water ($C_0$) is the second. In the laboratory experiments, small scale rock fracturing zone is modelled using sand stone. Chargeability and resistivity are measured by changing the size of the joint aperture, the location of fractured zone and the existence of clay gouge and/or clay layer which shows lower chargeability than the sand stone layer in the multi-layered ground. Test results show that chargeability is controlled not by the rock fracturing condition but by the size of narrow pore ($r_1$) where each line of current flow passes through. Also, the chargeability decreases with increase of the pore water salinity ($C_0$). In conclusion, the ground condition can be identified more efficiently by measuring the induced polarization along with the electrical resistivity; identifying the existence of sea water, the layered ground and/or the fractured rock becomes more reliable.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Geotechnical Engineering
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• v.14 no.2
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• pp.107-126
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• 1998

Ground settlements induced by tunnel excavation cause the foundations of the neighboring building structures to deform. An expert system called NESASS( Neural network Expert System for Adjacent Structure Safety analysis) was developed to analyze the structural safety of such building structures. NESASS predicts the trend of ground settlements resulting from tunnel excavation and carries out a safety analysis for building structures on the basis of the predicted ground settlements. Using neural network technique. the NESASS learns the database consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. The NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure. and in turn, determines the safety of the structure. In addition, the NESASS predicts the patterns of cracks to be formed in the structure, using Dulacska model for crack evaluation. In this study, the ground settlements measured from Seoul subway construction sites were collected and classified with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to select the optimal neural network model for the database. A comparison of the ground settlement predicted by the NESASS with the measured ones indicates that the NESASS leads to reasonable predictions. The results of confidence evaluation for safety evaluation system of the NESASS are presented in this paper.

• Explosives and Blasting
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• v.17 no.4
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• pp.67-88
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• 1999

Ground settlements induced by tunnel excavation cause the foundations of the neighboring superstructures to deform. An expert system called NESASS was developed to analyze the structural safety of such superstructures. NESASS predicts the trend of ground settlements to be resulted from tunnel excavation and carries out a safety analysis for superstructures on the basis of the predicted ground settlements. Using neural network techniques, NESASS learns a data base consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure and, in turn, determines the safety of the structure. In addition, NESASS predicts the patterns of cracks to be formed on the structure using Dulacskas model for crack evaluation. In this study, the ground settlements measured from the Seoul subway construction sites were collected and sorted with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to verify the reliability of the proposed neural network structure. A comparison of the ground settlement trends predicted by NESASS with the measured ones indicates that NESASS leads to reasonable predictions. An examples is presented in this paper where NESASS is used to evaluate the safety of a structure subject to deformation due to tunnel excavation near to the structure.