• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• International Journal of Railway
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• v.6 no.2
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• pp.45-52
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• 2013

Railway construction needs vast soil investigation for its infrastructure foundation designs along the planned railway path to identify the design parameters for stability and serviceability checks. The soil investigation data are usually classified and grouped to decide design input parameters per each construction section and budget estimates. Deterministic design method which most civil engineer and practitioner are familiar with has a clear limitation in construction/maintenance budget control, and occasionally produced overdesigned or unsafe design problems. Instead of using a batch type analysis with predetermined input parameters, data population collected from site soil investigation and design load condition can be statistically estimated for the mean and variance to present the feature of data distribution and optimized with a best fitting probability function. Probabilistic approach using entire feature of design input data enables to predict the worst, best and most probable cases based on identified ranges of soil and load data, which will help railway designer select construction method to save the time and cost. This paper introduces two Monte Carlo simulations actually applied on estimation of retaining wall external stability and long term settlement of organic soil in soil investigation area for a recent high speed railway project.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.101-108
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• 2002

This paper presents an input and system identification technique for a free-field system using forced vibration data. Identification is carried out on geotechnical experiment site at Yong-jong Island where Inchon International Airport being constructed. The identified quantities are the input load as well as the shear moduli of the free-field soil regions. The dynamic response analysis on the free-field system is carried out using the finite element method incorporating the infinite element formulation fur the unbounded layered soil medium. The criterion function for the parameter estimation is constructed using the frequency response amplitude ratios of the dynamic responses measured at several points of the free-field, so that the information on the input loading may be excluded. The constrained steepest descent method is employed to obtain the revised parameters. The simulated dynamic responses using the identified parameters and input load show excellent agreements with the measured responses.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.11-20
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• 2017

This study is to estimate the spatial soil moisture using multiple linear regression model (MLRM) and 15 minutes interval Land Surface Temperature (LST) data of Communication, Ocean and Meteorological Satellite (COMS). For the modeling, the input data of COMS LST, Terra MODIS Normalized Difference Vegetation Index (NDVI), daily rainfall and sunshine hour were considered and prepared. Using the observed soil moisture data at 9 stations of Automated Agriculture Observing System (AAOS) from January 2013 to May 2015, the MLRMs were developed by twelve scenarios of input components combination. The model results showed that the correlation between observed and modelled soil moisture increased when using antecedent rainfalls before the soil moisture simulation day. In addition, the correlation increased more when the model coefficients were evaluated by seasonal base. This was from the reverse correlation between MODIS NDVI and soil moisture in spring and autumn season.

• Geomechanics and Engineering
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• v.12 no.2
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• pp.239-255
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• 2017

Various centrifuge model tests on the pile foundations were performed to investigate fundamental characteristics of a pile-soil-foundation system recently, but it is hard to find numerical analysis results of a pile foundation system considering the nonlinear behavior of soil layers due to the dynamic excitations. Numerical analyses for a pile-soil system were carried out to verify the experimental results of centrifuge model tests. Centrifuge model tests were performed at the laboratory applying 1.5 Hz sinusoidal base input motions, and nonlinear numerical analyses were performed utilizing a finite element program of P3DASS in the frequency domain and applying the same input motions with the intensities of 0.05 g~0.38 g. Nonlinear soil properties of soil elements were defined by Ramberg-Osgood soil model for the nonlinear dynamic analyses. Nonlinear numerical analyses with the P3DASS program were helpful to predict the trend of experimental responses of a centrifuge model efficiently, even though there were some difficulties in processing analytical results and to find out unintended deficits in measured experimental data. Also nonlinear soil properties of elements in the system can be estimated adequately using an analytical program to compare them with experimental results.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.28-35
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• 2001

Liquefaction potential on the specific site of nuclear power plant is analyzed and reviewed. The layered site fur this study consists of silt and sand. Based on the limited available soil data, maximum shear strength at critical locations using Seed & Idriss method and computer program SHAKE is calculated, and liquefaction potential is reviewed. Seismic input motion used fur the assessment of liquefaction is the artificial time history compatible with the US NRC regulatory Guider .60. Assessment results of the liquefaction are validated by analyzing to the other typical soil fecundations which can show the effects of foundation depth and soil data.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.115-124
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• 2017

In this paper, a different technique to predict the effects of soil-structure interaction (SSI) on seismic response of building systems is investigated. The technique use a machine learning algorithm called Support Vector Regression (SVR) with technical and analytical results as input features. Normally, the effects of SSI on seismic response of existing building systems can be identified by different types of large data sets. Therefore, predicting and estimating the seismic response of building is a difficult task. It is possible to approximate a real valued function of the seismic response and make accurate investing choices regarding the design of building system and reduce the risk involved, by giving the right experimental and/or numerical data to a machine learning regression, such as SVR. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The results show that the performance of the technique can be predicted by reducing the number of real data input features. Further, performance enhancement was achieved by optimizing the RBF kernel and SVR parameters through grid search.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.771-776
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• 1999

RUSLE was applied to estimate annual soil loss from two small agricultural watersheds in Kangwon-do, Korea. GIS input parameters were prepared by using DEMs and soil maps prepared by the NGIS project and Rural Development Adminstration, respoctively. RUSLE parameters were prepared based on existing data and equations. Estimated annual soil loss was graphically presented to easily visualize the large soil loss area. Uplands and vineyards proved to be the two greatest sources for soil erosion. It was suggested to develop effective management practices to reduce the soil erosion from uplands and vineyards.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1998.11a
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• pp.123-126
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• 1998

We have conducted surface electrical resistivity surveys along with the electrical logging at Bookil-Myun, Chungwon-Goon, Choongchungbuk-Do to determine the depths of basement and water table, and for the purpose of preparing the basic input data for hydrogeologic model combined with GIS. A twenty lines of dipole-dipole array survey and a twenty-five stations of resistivity sounding were performed and ten holes were employed for electrical logging to cross check the surface data. A combined interpretation gave the quantitative information of the shallow geologic structure over the area and we constructed layers using the grid analysis of Arc/info. The constructed layers were turned out to be similar to the geologic structure confirmed from the drilling data and we concluded that the methodology adopted in this study would be applicable to hydrogeologic model setup as a tool of providing the basic input data.