• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.2
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• pp.36-46
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• 2009

The objective of this study is to analyze the effect of artificial soil ground on a structure. When the artificial soil ground is planted, the technical factors to be considered will be the load for buildings and the growth of plants. There are no current studies of the effect of artificial soil ground on a structure and this study will analyze the load effects of artificial soil ground, which mixes both pearlite and natural soil on structures. The load affecting the structures due to artificial soil ground will be maximized when the artificial soil ground becomes saturated, and which would occur when the rainfall intensity exceeds the infiltration capacity of the artificial soil ground. In order to determine whether the artificial soil ground has reached saturation or not, a 10 years frequency and 10 minutes rainfall intensity which is used for in urban drain design, is utilized. The hydraulic conductivity of artificial soil and mixed soil has been changed depending on the proportion of the mix, It has a range of fluctuation in the degree of hardening, in particular, but does not exceed the 10 minutes rainfall intensity over 10 years frequency in the most cases. Therefore, it would be efficient to apply the saturated unit weight of artificial soil ground as the design load of a structure.

• Explosives and Blasting
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• v.36 no.4
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• pp.16-25
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• 2018

In order to reduce ground vibration during tunnel excavation, a free surface blasting method has been applied in which a partial free surface is formed on the excavation surface and controlled blasting is performed. In this study, the ground vibration reduction due to artificial joints was evaluated by forming artificial joints on center cut using diamond wire saw and comparing the ground vibration caused by center cut blasting. As a result of comparison, ground vibration was reduced by artificial joints center cut blasting more than normal center cut blasting, and the ground vibration reduction effect of horizontal artificial joints center cut blasting was evaluated more than that of vertical artificial joint center cut blasting.

• Land and Housing Review
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• v.6 no.1
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• pp.31-39
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• 2015

Most landscape areas in apartment complex have been changing. Increasing the area of underground parking lots have an effect on apartment's circumstance. Natural ground was decreased so that the most space in apartment complex were converted into an artificial ground. To suggest the soil quality management, this study examined the actual situation about the soil quality of planting ground such as the quality standard as artificial soil, the difference of natural ground, and the difference of soil quality according to the work classification. As a result, the soil quality of the apartment complex with a large underground parking lot had low quality of soil. Soil physical properties were relatively fine but soil chemical properties needed the quality control. The soil quality of natural ground and artificial ground was not statistically significant and the soil quality by the work classification also had no statistical significance. Therefore, we established improvements about standards of the chemical properties for quality management, the soil quality in the natural ground and applying the equivalent standard according to the work classification.

• Proceedings of the Korean Geotechical Society Conference
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• 1992.10a
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• pp.87-94
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• 1992

근래 인공섬은 그 수가 많아지고 또 그 크기도 방대해지고 있다. 이 논문은 인공섬의 완성에 앞선 각과정에 대한 제반 문제점들에 대한 지반공학적 분석결과를 포함한다. 최근 인공섬 형성 과정에 사용하는 신공법에 개발되었다. 인공섬의 형성은 단일 공법에 의한 것이 아니고 여러가지 공법의 홍용의한다. 따라서 각 공법에 대한 완벽한 이해는 사업자체의 성공적인 완료와 경제성에 지대한 영향을 준다. 인공섬은 해성퇴적층에 위치하게 된다. 따라서 해성퇴적층의 형성과정, 환경, 퇴적 후의 변화 그리고 지반공학적인 자료가 채취되어야하고 분석되어야 한다. 해성퇴적층에 위치할 인공섬 완료에 필요한 조사, 설계 및 시공에서 반드시 고려되어야 할 과정이 실무자들이 이해하고 사용할수 있는 형식으로 제시되었다. 불완전한 자료, 또 그것에 근거한 설계 및 시공이 줄 수 있는 결과에 관해 기술했다.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.914-921
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• 2010

When industrial structures are constructed on soft ground, ground subsidence is occurred by problems of bearing capacity. To protect ground subsidence have to improve soft ground, and have to predict settlement estimation for reasonable construction. Artificial Neural Networks(ANN) is adopted for prediction of settlement of construction during the initial design. In the study, Artificial Neural Networks are applied to predict the settlement estimation of initial condition ground and ground improved by D.C.M method. Also, this study compares results of Artificial Neural Networks and results of continuum analysis using Mohr-Coulomb models. In result, settlements of initial condition ground decreased over 0.7 times. Also, by comparing ANN and continuum analysis, coefficient of determination was comparatively high value 0.79. Thought this study, it was confirmed that settlements of improvement ground is predicted using laboratory experiment data.

• Journal of the Korean Geotechnical Society
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• v.21 no.2
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• pp.5-16
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• 2005

Tn this study, model soil deposits are prepared in large test chambers to minimize the scale effects. Also, slurry of mixture containing 50 percent kaolin clay and 50 percent silica has been consolidated to simulate the process of natural soil deposit formation and to reduce the consolidation time. To provide a more detailed description of varying soil properties along the soil profile of model clay deposits and to compare the in-situ test results with those from prototype tests, miniature in-situ tests, including vane shear, piezoprobe, and cone penetration tests were conducted in each of the clay deposits. The current results indicate that consistent soil deposits were prepared for the current and previous test programs. Also, reasonable predicting methods of prototype behavior based on model in-situ test results were suggested in this study by examining differences between the test results from both the model and prototype tests.

• Journal of the Korean GEO-environmental Society
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• v.17 no.6
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• pp.33-41
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• 2016

This study attempted to investigate drain capacity and vegetation potential of made-planting soil via finite element simulations. Engineering drain capacity of made-planting soil can be evaluated by an analysis of unsaturated soils. In a perspective for vegetation landscape, it is necessary to check whether the minimum amount of water in the made-planting soil can be supplied for the survival of plants. Herein, 1-m high soil column covered by made-planting soil were numerically simulated. Numerical results showed that how the coefficient of permeability of saturated soil and soil-water characteristics of unsaturated soil are considered significantly influences the drain capacity of soils. Variation in the volumetric water content within the Least Limiting Water Range (LLWR) provides us with information on whether the soil can contain a sufficient amount of water for the plants to survive the drought.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.148-148
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• 2017

본 연구에서는 합성개구레이더(Synthetic Aperture Radar, SAR) 인공위성 영상을 활용한 풍수해 피해지역 감지 기법을 제안하고자 한다. SAR 인공위성 자료를 분석하여 풍수해 피해 중 지반의 변화량 및 변화양상 감지를 분석하였다. 연구지역은 울릉도 전역이며, 2016년 8월 30일 제 10호 태풍 라이언록에 의한 피해를 분석하였다. SAR Interferometry(InSAR) 기법을 적용하여 홍수 전, 후의 지반 변화량을 분석하였다. 분석결과의 정확도를 파악하기 위해 분석결과를 실제 피해사례 및 피해 사진 등과 비교, 분석하여 검증을 실시하였다. 검증결과, 정성적인 지반변화 및 변화양상은 판별되었으나, 정량적인 지반변화량 파악은 어려운 것으로 나타났다. 현재 국내지역에 대해 InSAR 기법을 적용하여 홍수 전, 후의 지반변화 감지를 적용해본 사례가 많지 않은 실정이며, 본 연구는 국내지역에 대해 InSAR 기법을 적용하여 풍수해 피해감지를 하였다는 의미가 있다.

• 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 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.