• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.26-33
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• 2005

Inversion of multi-mode surface-wave phase velocity for shallow engineering site investigation has received much attention in recent years. A sensitivity analysis and inversion of both synthetic and field data demonstrates the greater effectiveness of this method over employing the fundamental mode alone. Perturbation of thickness and shear-wave velocity parameters in multi-modal Rayleigh wave phase velocities revealed that the sensitivities of higher modes: (a) concentrate in different frequency bands, and (b) are greater than the fundamental mode for deeper parameters. These observations suggest that multi-mode phase velocity inversion can provide better parameter discrimination and imaging of deep structure, especially with a velocity reversal, than can inversion of fundamental mode data alone. An inversion of the theoretical phase velocities in a model with a low velocity layer at 20 m depth can only image the soft layer when the first higher mode is incorporated. This is especially important when the lowest measurable frequency is only 6 Hz. Field tests were conducted at sites surveyed by borehole and PS logging. At the first site, an array microtremor survey, often used for deep geological surveying in Japan, was used to survey the soil down to 35 m depth. At the second site, linear multichannel spreads with a sledgehammer source were recorded, for an investigation down to 12 m depth. The f-k power spectrum method was applied for dispersion analysis, and velocities up to the second higher mode were observed in each test. The multi-mode inversion results agree well with PS logs, but models estimated from the fundamental mode alone show f large underestimation of the depth to shallow soft layers below artificial fill.

• Journal of Soil and Groundwater Environment
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• v.22 no.5
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• pp.128-134
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• 2017

This work presents the adsorption capability of green tea and ginseng leaves to adsorb heavy metals such as Cd(II), Cu(II), and Pb(II) in aqueous solution. FT-IR analysis indicates the presence of oxygen containing functional groups (carboxyl groups) in two kinds of leaves. High pH condition was favorable to the adsorption of heavy metal ions due to the enhanced electrostatic attraction and the precipitation reaction of metal ions. The adsorption of Cd(II), Cu(II), and Pb(II) reached equilibrium within 10 min, achieving high removal efficiencies of 80.3-97.5%. The adsorption kinetics data of heavy metal ions were fitted well with the pseudo-second-order kinetic model. The maximum adsorption amounts of Cd(II), Cu(II), and Pb(II) ions were 8, 3.5, and 15 mg/g, respectively, in the initial concentration range from 0.15 to 0.75 mM. Based on the fitting data obtained from isotherm models, heavy metal adsorption by green tea and ginseng leaves could occur via multi-layer sorption.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.587-598
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• 2008

In the trackbed design using elastic multi-layer model, the stress-dependent resilient modulus is an important input parameter, which reflects substructure performance under repeated traffic loading. The resilient moduli of crushed stone and weathered granite soil were developed using nonlinear dynamic stiffness, which can be measured by in-situ and laboratory seismic tests. The prediction models of resilient modulus varying with the deviatoric or bulk stress were proposed (Park et al., 2008). To investigate the performance of the prediction models proposed herein, the elastic response of the test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement during the passages of freight and passenger trains. The material types of the test sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 1mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation. The prediction models proposed for resilient modulus were verified by the comparison of the calculated vertical displacements with measured ones during train passages.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1712-1723
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• 2008

In the trackbed design using an elastic multi-layer model, the stress-dependent resilient modulus is the key input parameter, which reflects substructure performance under repeated traffic loading. The prediction models of resilient modulus of crushed stone and weathered granite soil were developed from nonlinear dynamic stiffness, which can be combined by in-situ and laboratory seismic measurements. The models accommodate the variation with the deviatoric and/or bulk stresses. To investigate the performance of the prediction models proposed, the elastic response of the test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement caused by the passages of freight and passenger trains. The material types of the test sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 1mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation.

• The Journal of Engineering Geology
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• v.14 no.3 s.40
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• pp.301-311
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• 2004

This study is suggested a new dielectric tracer test method to understand geological structure of porous media and groundwater flow to use the dielectric constant which is one of electrical special quality of various geological materials. To measure their parameters, tracer material is made an ethanol mixing liquid(EML) having a same specific gravity of water. Also, soil materials are prepared a dielectric tracer test using the FDR system that could measure dielectric constant for saturated standard sand and river sand layers which have different initial porosity. To compare with their results, we discussed with the concentration variation of saline water having a saline concentration $3\%$ which is general tracer material by using the electro multi-meter system in the laboratory or field test. In two tracer experiment results, EML tracer test could confirm definitely EML concentration variation from each saturated soil layer as standard and river sands. However, tracer test of saline water $3\%$ concentration could not confirm permeating movement of water by degree of salinity change because these are settled at lower part column in a whole column area continuously. These causes are that specific gravity of saline water is heavier than water. That is, it could know that deposition of saline water is composed of lower part of soil column continuously independently of the direction of water into saturated soil material.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.441-464
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• 2017

The determination of the mixture parameters of stabilization has become a great concern in geotechnical applications. This paper presents an effort about the application of artificial intelligence (AI) techniques including radial basis neural network (RBNN), multi-layer perceptrons (MLP), generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) in order to predict the unconfined compressive strength (UCS) of silty soil stabilized with bottom ash (BA), jute fiber (JF) and steel fiber (SF) under different freeze-thaw cycles (FTC). The dosages of the stabilizers and number of freeze-thaw cycles were employed as input (predictor) variables and the UCS values as output variable. For understanding the dominant parameter of the predictor variables on the UCS of stabilized soil, a sensitivity analysis has also been performed. The performance measures of root mean square error (RMSE), mean absolute error (MAE) and determination coefficient ($R^2$) were used for the evaluations of the prediction accuracy and applicability of the employed models. The results indicate that the predictions due to all AI techniques employed are significantly correlated with the measured UCS ($p{\leq}0.05$). They also perform better predictions than nonlinear regression (NLR) in terms of the performance measures. It is found from the model performances that RBNN approach within AI techniques yields the highest satisfactory results (RMSE = 55.4 kPa, MAE = 45.1 kPa, and $R^2=0.988$). The sensitivity analysis demonstrates that the JF inclusion within the input predictors is the most effective parameter on the UCS responses, followed by FTC.

• Advances in Computational Design
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• v.3 no.3
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• pp.269-288
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• 2018

180 different 2D numerical analyses have been carried out to estimate the factor of safety (FOS) for rooted slopes. Four different types of vegetated coverage and a variety of slope geometry considering three types of soil have been evaluated in this study. The highly influenced parameters on the slope's FOS are determined. They have been chosen as the input parameters for developing a new practical relationship to estimate the FOS with an emphasis on the roots effects. The dependency of sliding mode and shape considering the soil and roots-type has been evaluated by using the numerical finite element model. It is observed that the inclination and height of the slope and the coverage type are the most important effective factors in FOS. While the soil strength parameters and its physical properties would be considered as the second major group that affects the FOS. Achieved results from the developed relationship have shown the acceptable estimation for the roots slope. The extracted R square from the proposed relationship considering nonlinear estimation has been achieved up to 0.85. As a further cross check, the achieved R square from a multi-layer neural network has also been observed to be around 0.92. The numerical verification considering different scenarios has been done in the current evaluation.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.939-944
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• 2002

In this paper, we propose and apply new classification method to the remotely sensed image acquired from airborne multi-spectral scanner. This is a neuro-fuzzy image classifier derived from the generic model of a 3-layer fuzzy perceptron. We implement a classification software system with the proposed method for land cover image classification. Comparisons with the proposed and maximum-likelihood classifiers are also presented. The results show that the neuro-fuzzy classification method classifies more accurately than the maximum likelihood method. In comparing the maximum-likelihood classification map with the neuro-fuzzy classification map, it is apparent that there is more different as amount as 7.96% in the overall accuracy. Most of the differences are in the "Building" and "Pine tree", for which the neuro-fuzzy classifier was considerably more accurate. However, the "Bare soil" is classified more correctly with the maximum-likelihood classifier rather than the neuro-fuzzy classifier.

• Journal of the Korean Geotechnical Society
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• v.18 no.3
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• pp.33-41
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• 2002

Soil nailing type of retaining structures has been widely used in Korea far the purpose of the temporary and permanent support in excavations and slope stability. The important factors in application of soil nailing systems in urban excavation site nearby the existing structures are the displacement of the wall and tensile farce of the nails, etc. In this paper, the fled back analyses are carried out at 11 excavation sites to investigate the behavior of tensile farce of nails at stepwise excavation in the multi-layered strata including various rock layers. The results of the fled back analysis are less than about 50% of the measured ones. The distance of active zone by measurements are shown almost larger than that of fled back analysis when the distance of active Bone is defined from the surface of wall to the potential failure surface. And the results of fled back analysis are within the range proposed by the project CLOUTERRE and Cartier & Gigan (1983) which were 0.3$H_f$, and 0.5$H_f$, of the final excavation depth ($H_f$,) respectively, but the values of the measurement were larger than these values.

• Journal of the Korean Geotechnical Society
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• v.23 no.5
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• pp.43-51
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• 2007

Frost action may cause extensive damage to building, structures, roads, railways and utility lines in seasonal frost. The research about frost heave of natural ground has been considerably performed. In late years various structures have become complicated with the development of social infrastructure maintenance. Therefore countermeasure to frost heave becomes a matter of great importance from a new viewpoint. This study was aimed at catching natural ground frost heaving force quantitatively. Frost heaving forces on circular steel plates which were set on ground surface were measured in field test. The frost heaving forces arise at freezing front propagates to the structures through frozen soil layer. Besides, a full scale model of multi-anchored retaining wall was installed in field, and the freezing lines, frost heave pressure to act on a wall block, and so on were measured. Finally, the position and shape of frost line were estimated by using numerical simulation and a method to determine replacement range was suggested with soil properties and weather data.