• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.451-458
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• 2002

This paper presents the prediction of deep excavation-induced ground surface movements using artificial neural network, which is of prime importance in the perspective of damage assessment of adjacent buildings. A finite element model, which can realistically replicate deep-excavation-induced ground movements was employed and validated against available large-scale model test results. The validated model was then used to perform a parametric study on deep excavations with emphasis on ground movements. Using the result of the finite element analysis, Artificial Neural Network(ANN) system is formed, which can be used in the prediction of deep exacavation-induced ground surface displacements. The developed ANN system can be effecting used for a first-order prediction of ground movements associated with deep-excavation.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.293-305
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• 2023

To ensure the safety of underground infrastructures, ground can sometimes be first treated by cement slurry and then stabilized using artificial ground freezing (AGF) technique before excavation. The hydration heat produced by cement slurry increases the soil temperature before freezing and results in an extension of the active freezing time (AFT), especially when the Metro Jet System (MJS) treatment is adopted due to a high cement-soil ratio. In this paper, by taking advantage of an on-going project, a case study was performed to evaluate the influence of MJS and AGF on the ground temperature variation through on-site measurement and numerical simulation. Both on-site measurement and simulation results reveal that MJS resulted in a significant increase in the soil temperature after treatment. The ground temperature gradually decreases and then stabilized after completion of MJS. The initiation of AGF resulted in a quick decrease in ground temperature. The ground temperature then slowly decreased and stabilized at later freezing. A slight difference in ground temperature exists between the on-site measurements and simulation results due to limitations of numerical simulation. For the AGF system, numerical simulation is still strongly recommended because it is proven to be cost-effective for predicting the ground temperature variation with reasonable accuracy.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.575-592
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• 2011

For seismic resistant design of critical structures, a dynamic analysis, either response spectrum or time history is frequently required. Owing to the lack of recorded data and the randomness of earthquake ground motion that may be experienced by structure in the future, usually it is difficult to obtain recorded data which fit the requirements (site type, epicenteral distance, etc.) well. Therefore, the artificial seismic records are widely used in seismic designs, verification of seismic capacity and seismic assessment of structures. The purpose of this paper is to develop a numerical method using Artificial Neural Network (ANN) and wavelet packet transform in best basis method which is presented for the decomposition of artificial earthquake records consistent with any arbitrarily specified target response spectra requirements. The ground motion has been modeled as a non-stationary process using wavelet packet. This study shows that the procedure using ANN-based models and wavelet packets in best-basis method are applicable to generate artificial earthquakes compatible with any response spectra. Several numerical examples are given to verify the developed model.

• Journal of the Korean GEO-environmental Society
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• v.20 no.3
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• pp.15-20
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• 2019

A large amount of site investigation data is essential to obtain reliable design value. However, site investigations are generally insufficient due to economic problems. It is important to estimate the ground profile information in unboring region for accurate earthwork-volume prediction, and such ground profile information can be estimated by using the geo-statistical approach. Furthermore, the ground profile information in unboring region can be estimated by training a model via machine learning technique such as artificial neural network. In this paper, artificial neural network-based model estimated the ground profile information in unboring region, and this results were compared with that of ordinary kriging technique, which is referred to the geo-statistical approach. Accordingly, a total of 84 ground profile information in an actual bridge environment was split into 75 training and 9 test databases. The observed ground profile information of the test database was compared with those of the ordinary kriging technique and artificial neural network.

• Korean Journal of Environment and Ecology
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• v.11 no.1
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• pp.46-60
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• 1997

The purposes of this research are to select the appropriate kinds of landscape woody plants for afforestation artificial ground and to find out the way of developing planting-tree area of artificial ground through test planting and case study. The summary of the research is as follows; As a result of observing the state of trees' growth, trees on artificial grounds grow as well as, or even better than those on natural grounds. The kinds of trees which represent better growth states on artificial soil of rooftop test area are Thuja occidentalis, Prunus armericana var. ausu, Acer palmatum, Viburnum sargentii for. sterile, Buxus microphylla var. koreana, etc. In addition, soils than on natural soils. As a result of investigating the tree's growth state according to soil beds of artificial soils, shrubs don't represent distinct differences. They show that shrubs can be planted on 30cm soil bed. The rest of trees no differences according to the variation of soil beds, and they are in normal condition or have slight damage. This means that though arbor planting area of artificial ground is made 45~60cm, it is possible for trees to grow on it. In consequence of analyzing the cases on areas of landscaping artificial grounds, as the appropriate kinds of trees for afforestation artificial ground, Diospyros kaki, Hibiscus syriacus, Syringa dilatata, Magnolia kobus, Acer ginnala and cornus alba are selected in Capital region, and Nandina domestica, Taxus cuspidata, Ilex crenata, Viburnum awabuki, Aucuba japonica and Euonymus japonica are selected in southern region. In addition, Juniperus chinensis, Zelkova serrata, Juniperus chinensis var. kaizuka, etc. are selected regardless of regional character. In accordance with the state of soil it shows great difference, namely, fertilization once or more a year and irrigation for drought is advantageous to tree's growth. This research represents that it is necessary that standards related to landscaping artificial grounds are subdivided. In addition to it, the plan for revising related to regulation is drawn up.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.04a
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• pp.61-68
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• 1999

In the nonlinear dynamic structural analysis the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary modulation function and a power spectral density function to describe such non-stationary characteristics. Satio and Wen(1994) proposed a non-stationary stochastic process model to generate earthquake ground motions which are compatible with design reponse spectrum at sites in Japan. this paper shows the process to modify power spectrum compatible with target design response spectrum for generating of nonstationary artificial earthquake ground motions. Target reponse spectrum is chosen by ATC14 to calibrate the response spectrum according to a give recurrence period.

• Journal of the Korean GEO-environmental Society
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• v.14 no.9
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• pp.31-37
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• 2013

In this study installation diameter, interval, area replacement ratio and ground hardness of applicable ground in C.G.S method should be mastered through surrounding ground by conducting modeling. Optimum artificial neural network was selected through the study of the parameter of artificial neural network and prediction model was developed by the relationship with numerical analysis and artificial neural network. As this result, C.G.S pile settlement and ground settlement were found to be equal in terms of diameter, interval, area replacement ratio and ground hardness, presented in a single curve, which means that the behavior pattern of applied ground in C.G.S method was presented as some form, and based on such a result, learning the artificial neural network for 3D behavior was found to be possible. As the study results of artificial neural network internal factor, when using the number of neural in hidden layer 10, momentum constant 0.2 and learning rate 0.2, relationship between input and output was expressed properly. As a result of evaluating the ground behavior of C.G.S method which was applied to using such optimum structure of artificial neural network model, is that determination coefficient in case of C.G.S pile settlement was 0.8737, in case of ground settlement was 0.7339 and in case of ground heaving was 0.7212, sufficient reliability was known.

• Journal of the Korean Geosynthetics Society
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• v.18 no.3
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• pp.23-32
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• 2019

This study investigated the scour characteristics of artificial reef according to unreinforced and reinforced artificial reefs through laboratory test and numerical analysis. In this study, geogrid was used as a reinforcement of seabed. Three different reinforced areas were selected; one time, three times and five times bottom area of artificial reef. Two-dimensional water channel test was carried out to investigate scour patten of sand and silt grounds. Numerical analysis was also performed to see the velocity vector and scouring patten around artificial reef which was same condition with experiment. The numerical results were in good agreements with the experimental test results. It was found that the geogrid-installed soft ground under artificial reef tends to reduce scour, compared to unreinforced soft ground.

• Journal of the Korean Geotechnical Society
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• v.36 no.12
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• pp.17-25
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• 2020

The artificial ground freezing method is a ground amelioration technology that does not have a permanent effect on the ground. One of the key factors that determine the efficiency and design criteria of the artificial ground freezing is the groundwater flow. Therefore, in order to accurately evaluate the behavior of the artificial ground freezing, studies on the effect of water flow on the formation of ice walls must be preceded. In this paper, experimental and numerical analyses were conducted using only pure water to maximize the effect of water flow on the formation of ice walls. A hydro-thermal coupled model for freezing behavior was proposed and the accuracy of the model was verified. Through the numerical and experimental studies, the flow rate dominates not only the formation time but also the shape of the ice wall. In addition, this study proposes a method to indirectly predict the ice wall formation time, which is expected to be highly useful for a practical application where it is difficult to visually identify ice walls.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.4
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• pp.17-31
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• 2004

How far of natural regeneration of the city and improvement on the urban environment will be possible in the replanting on the impermeable surface? The replanting of what kind of form will be obtained in order to realize it? The regeneration of the nature is possible, if it can be realized at the thin soil layer in which the result of being equivalent to the natural soil function. Using the light artificial soil with the water retentiveness, it is possible that green on the artificial ground reinforces the green skeleton of the city. The green of artificial ground improves the thermal ambience of the city and demonstrates stormwater runoff depression effect. It is necessary to built the landscape which continues with the surrounding green. Ecologically stabilizing green has the high amenity. The development of replanting technology of the artificial ground which fosters the city culture is desired.