• Geomechanics and Engineering
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• v.29 no.3
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• pp.301-310
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• 2022

Accurate prediction of mixed ground conditions ahead of a tunnel face is of vital importance for safe excavation using tunnel boring machines (TBMs). Previous studies have primarily focused on electrical resistivity surveys from the ground surface for geotechnical investigation. In this study, an FE (finite element) numerical model was developed to simulate electrical resistivity surveys for the prediction of risky mixed ground conditions in front of a tunnel face. The proposed FE model is validated by comparing with the apparent electrical resistivity values obtained from the analytical solution corresponding to a vertical fault on the ground surface (i.e., a simplified model). A series of parametric studies was performed with the FE model to analyze the effect of geological and sensor geometric conditions on the electrical resistivity survey. The parametric study revealed that the interface slope between two different ground formations affects the electrical resistivity measurements during TBM excavation. In addition, a large difference in electrical resistivity between two different ground formations represented the dramatic effect of the mixed ground conditions on the electrical resistivity values. The parametric studies of the electrode array showed that the proper selection of the electrode spacing and the location of the electrode array on the tunnel face of TBM is very important. Thus, it is concluded that the developed FE numerical model can successfully predict the presence of a mixed ground zone, which enables optimal management of potential risks.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.85-88
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• 2002

This paper presents the result of the Water Erosion Prediction Project(WEPP) watershed scale model's application for prediction of sediment yield from a watershed which is comprised of hillslopes and channels and analyses of the soil loss from hillslopes and channels with crop practice and shape. To evaluate the model's application, the model is applied to a watershed that comprised of six hillslope and one channel, and the result was a good agreement with the observed values. The soil loss from hillslope was increased as the hills lope was under fallow conditions and slope length was longer. The soil loss from the channel was increased at the downstream for the concentration of flow.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.93-101
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• 2019

The objective of this study is to develop a model which can predict the seismic performance of the slope relatively accurately and efficiently by using artificial neural network(ANN) technique. The quantification of such the seismic performance of the slope is not easy task due to the randomness and the uncertainty of the earthquake input and slope model. Under these circumstances, probabilistic seismic fragility analyses of slope have been carried out by several researchers, and a closed-form equation for slope seismic performance was proposed through a multiple linear regression analysis. However, a traditional statistical linear regression analysis has shown a limit that cannot accurately represent the nonlinearistic relationship between the slope of various conditions and seismic performance. In order to overcome these problems, in this study, we attempted to apply the ANN to generate prediction models of the seismic performance of the slope. The validity of the derived model was verified by comparing this with the conventional multi-linear and multi-nonlinear regression models. As a result, the models obtained through the ANN basically showed excellent performance in predicting the seismic performance of the slope, compared to the models obtained by the statistical regression analyses of the previous study.

• Journal of Korean Society of societal Security
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• v.1 no.4
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• pp.57-64
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• 2008

Korea has been suffered from serious damages of lives and properties, due to landslides that are triggered by heavy rains in every monsoon season. This study developed the physically based landslide prediction model which consists of 3 parts, such as slope stability analysis model, groundwater flow model and soil depth model. To evaluate its applicability to the prediction of landslides, the data of actual landslides were plotted on the areas predicted on the GIS map. The matching rate of this model to the actual data was 84.8%. The relation between hydrological and landform factors and potential landslide were analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.364-371
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• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.

• Journal of agriculture & life science
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• v.46 no.3
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• pp.47-58
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• 2012

This study was carried out to develop assessment model for the optimal site prediction of Dendropanax morbifera, Evergreen broad-leaved trees in warm temperate zone according to climate change. It was created criterion for assessment model of the optimal site prediction by quantification method to possible analysis of quantitative and qualitative data, through study relationship between growth of tree and site environmental factors. A program of the optimal site prediction was developed using program version 3.2, an Avenue and Dialog Designer tool of ESRI as GIS(geographic information system) engine. Developed program applied to test accuracy of the optimal site prediction in study area of Wando, Jeollanam-do, having a various evergreen broad-leaved trees of warm temperate zone. In the results from analysis of the optimal site prediction on Dendropanax morbifera, the characteristics of optimal site were analyzed site environmental features with 401~500m of altitude, $15^{\circ}$ of slope, hillside of local topography, alluvium of deposit type, convex of slope type and south of aspect. The mapping area per grade of the optimal site prediction in the Dendropanax morbifera showed 1,487.2ha(25.4%) of class I, 1,020.3ha(17.4%) of class II, 2,231.8ha(38.2%) of class III and 1,110.5ha(19.0%) of class IV.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.2
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• pp.1-9
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• 2008

The objective of the study is 10 know the relation of landslide occurrence with using TPI (Topographic Position Index) in the Pyungchang County. Total 659 landslide scars were detected from aerial photographs. To analyze TPI, 100m SN (Small-Neighborhood) TPI map, 500m LN (Large-Neighborhood) TPI map, and slope map were generated from the DEM (Digital Elevation Model) data which are made from 1 : 5,000 digital topographic map. 10 classes clustered by regular condition after overlapping each TPI maps and slope map. Through this process, we could make landform classification map. Because it is only to classify landform, 7 classes were finally regrouped by the slope angle information of landslide occurrence detected from aerial photography analysis. The accuracy of reclassified map is about 46%.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.137-153
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• 2016

The price of agricultural products has changed from year to year, the m ajor c ause o f price fluctuation is the imbalance of supply and demand. Materials which are mainly used in korean cabbage production volume is the forecast model, using the cadastral result, slope calculation is impossible to achieved. For this reason, this implies the drastic decrease of prices and the prediction of supply and demand of field crops that is cultivated in a highland slope area, this situation is being repeated. Therefore, the target area of this research is the slopes of high land, by using 2D and 3D Lidar data for the analysis of the cultivated area. Experiment was carried out in the same area to compare the data differences. The rate of change in the area of slope is quantitatively increasing presented by the regression model. An alternative methodology that can improve the reliability of the calculated slope area using 2D is through cadastral map.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.567-573
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• 2006

An efficient typhoon wave-generating model is applied to northeast Asia sea zone presented that can be used by civil defense agencies for real-time prediction and fast warnings on typhoon-generated wind wave and storm surge. Instead of using commercialized wave models such as WAM, SWAN, the wind waves are simulated by using a new concept of wavelength modulation to enhance broader application of the hyperbolic wave model of the mild-slope equation type. The results simulated along the Korean coasts during Typhoon Nabi (2005) showed reasonable agreement with the recorded wind waves.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.574-578
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• 2006

Tidal amplification by construction of the sea-dike and sea-walls had been detected not only near Mokpo Harbor but also at Chungkye Bay which is connected with Mokpo Harbor by a narrow channel. This brings about increase of tidal flat area and in particular increase of surge-wave combined runup during storms. The purpose of this study is to examine an efficient operational model that can be used by civil defense agencies for real-time prediction and fast warnings on wind waves and storm surges. Instead of using commercialized wave models such as WAM, SWAN, the wind waves are simulated by using a new concept of wavelength modulation to enhance broader application of the hyperbolic wave model of the mild-slope equation type. Furthermore, The predicting system is composed of easy and economical tools for inputting depth data of complex bathymetry and enormous tidal flats such as Mokpo coastal zone. The method is applied to Chungkye Bay, and possible inundation features at Mokpo Harbor are analyzed.