• Structural Engineering and Mechanics
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• v.20 no.4
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• pp.421-434
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• 2005

In this paper, the finite element method is applied to investigate the effect of the lateral boundary in homogenous soil on the seismic response of a superstructure. Some influencing factors are presented and discussed, and several parameters are identified to be important for conducting soil-structure interaction experiments on shaking tables. Numerical results show that the cross-section width L, thickness H, wave propagation velocity and lateral boundaries of soil layer have certain influences on the computational accuracy. The dimensionless parameter L/H is the most significant one among the influencing factors. In other words, a greater depth of soil layer near the foundation should be considered in shaking table tests as the thickness of the soil layer increases, which can be regarded as a linear relationship approximately. It is also found that the wave propagation velocity in soil layer affects the numerical accuracy and it is suggested to consider a greater depth of the soil layer as the wave propagation velocity increases. A numerical study on a soil-structure experimental model with a rubber ring surrounding the soil on a shaking table is also conducted. It is found the rubber ring has great effect on the soil-structure interaction experiments on shaking table. The experimental precision can be improved by reasonably choosing the elastic parameter and width of the rubber ring.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1999.04a
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• pp.75-75
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• 1999

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.

• Proceedings of the Korean Geotechical Society Conference
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• 1994.09a
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• pp.182-190
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• 1994

Mattress foundations using geogrids are often used on soil foundations to increase the supporting capability of a mattress-soil foundation system, in which the mattress foundation trasmits a point load applied above to a wider area of the soil foundation underneath. To examine this load dispersion capability of the mattress foundation, model experiments were carried out on lab-floor. Expecially, the effect of the thickness of the mattress and the subgrade modulus of the soil foundation on load dispersion are considered. The load distribution and the tensile force generated on geogrid of the upper part of the mattress are examined in the paper.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.455-462
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• 2000

In this study seismic response of a base-isolated bridge for soil types is compared. Bilinear model is used for lead rubber bearing(LRB). Accelerograms whose response spectrum matches the design spectrum for soil types are used as earthquake ground excitation. Nonlinear time history analyses using the SAP2000 program is performed. The results show that seismic response of a base-isolated bridge is increased as the soil becomes soft.

• Atmosphere
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• v.15 no.1
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• pp.1-16
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• 2005

Land-surface and soil processes significantly affect mesoscale local weather systems as well as global/regional climate. In this study, characteristics of land-surface models (LSMs) and soil models (SMs) that are frequently coupled into mesoscale meteorological models are investigated. In addition, detailed analyses on three LSMs, employed by the PSU/NCAR MM5, are provided. Some impacts of LSMs on heavy rainfall prediction are also discussed.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.354-355
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• 2003

In this study, a risk-based cleanup approach using the leaching potential was suggested for the soil vapor extraction (SVE) process. A multi-component model was adopted with local equilibrium assumption (LEA), and Raoult's law was applied to estimate the leaching potential for BTEX. Finally, a risk analysis was conducted based on the leaching pontential calculated. To complete the feasibility of this approach, more investigations and discussions will be required in future.

• Journal of Soil and Groundwater Environment
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• v.7 no.3
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• pp.103-114
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• 2002

Knowledge of soil water retention characteristic is essential for many problems involving water flow and organic solute transport in unsaturated soils. A physico-empirical approach based on the translation of the particle-size distribution (PSD) into a corresponding water retention curve has been accomplished by others using the concept that the pore-size distribution is directly related to PSD. This approach implies that details of a PSD curve may affect the estimation of water retention characteristic (WRC). To determine whether the WRC estimation using the Arya-Paris model could be affected by the selection of a PSD model, four PSD models with one to four fitting parameters were used. The Jaky model with only one fitting parameter had greater WRC estimation ability than other models with greater number of fitting parameters. The better performance of the Jaky model may be explained by the effect of soil structure in field soils.

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.133-144
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• 2004

A Tank Model composed of 4 tanks with soil moisture structure was applied to Daecheong Dam and Soyanggang Dam watersheds. Calibration and verification were repeated 332 and 472 times for each watershed using SCE-UA global optimization method for different calibration periods and objective functions. Four different methods of evapotranspiration calculation were used and evaluated. They are pan evaporation, 1963 Penman, FAO-24 Penman-Monteith, and FAO-56 Penman-Monteith methods. Tank model with soil moisture structure showed better results than the standard tank model for daily rainfall-runoff simulation. Two types of objective function for model calibration were found. Proper calibration period are 3 years, in which dry year and flood year are included. If a calibrationperiod has an inadequate runoff rate, the period should be more than 8 years. The four methods of eyapotranspiraton computation showed similar results, but 1963 Penman method was slightly inferior to the other methods.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.