• The Journal of Engineering Geology
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• v.17 no.3
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• pp.435-443
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• 2007

This study shows the prediction of the engineering properties of weathered zone bearing corestones through the engineering geological surveys and the scale model test in the laboratory. The window survey and the observation on the borehole core were peformed on three natural slopes in corestones area in order to analyse the distribution pattern and the geometrical properties of corestones. Natural corestones were crushed and abrased for the scale model test into less than 5 mm in maximum-2mm in average by the scale reduction ratio based on the size of natural corestones and the specimen size. Scale model tests were carried out on soil and plaster model specimens with different corestone content ratio - 0%, 10%, 20%. The direct shear test on soils shows that shear strength is increased by the increase of corestone content ratio. The increase of cohesion is, however, more important factor to the shear strength of soil for 20% corestone content ratio due to interlocking of crushed corestone particles. The plaster model test shows a tendance of increase of UCS and modulus of elasticity with increase of corestone content. The variation ratio of specimen property by change of corestone content ratio in plaster model test was applied to in situ properties in order to estimate the properties of weathered zone bearing corestones. So it could be predicted that the increase of corestone content to 10% and to 20% produce about 18% and 30% UCS's increase respectively.

• Earthquakes and Structures
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• v.17 no.6
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• pp.557-566
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• 2019

The evaluation of the seismic hazard for a given site is to estimate the seismic ground motion at the surface. This is the result of the combination of the action of the seismic source, which generates seismic waves, the propagation of these waves between the source and the site, and site local conditions. The aim of this work is to evaluate the sensitivity of dynamic response of extended structures to spatial variable ground motions (SVGM). All factors of spatial variability of ground motion are considered, especially local site effect. In this paper, a method is presented to simulate spatially varying earthquake ground motions. The scheme for generating spatially varying ground motions is established for spatial locations on the ground surface with varying site conditions. In this proposed method, two steps are necessary. Firstly, the base rock motions are assumed to have the same intensity and are modelled with a filtered Tajimi-Kanai power spectral density function. An empirical coherency loss model is used to define spatial variable seismic ground motions at the base rock. In the second step, power spectral density function of ground motion on surface is derived by considering site amplification effect based on the one dimensional seismic wave propagation theory. Several dynamics analysis of a curved viaduct to various cases of spatially varying seismic ground motions are performed. For comparison, responses to uniform ground motion, to spatial ground motions without considering local site effect, to spatial ground motions with considering coherency loss, phase delay and local site effects are also calculated. The results showed that the generated seismic signals are strongly conditioned by the local site effect. In the same sense, the dynamic response of the viaduct is very sensitive of the variation of local geological conditions of the site. The effect of neglecting local site effect in dynamic analysis gives rise to a significant underestimation of the seismic demand of the structure.

• Smart Structures and Systems
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• v.30 no.6
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• pp.601-612
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• 2022

The prediction of structural mechanical behaviors is vital important to early perceive the abnormal conditions and avoid the occurrence of disasters. Especially for underground engineering, complex geological conditions make the structure more prone to disasters. Aiming at solving the problems existing in previous studies, such as incomplete consideration factors and can only predict the continuous performance, the deep attention fused temporal convolution network (DATCN) is proposed in this paper to predict the spatial mechanical behaviors of structure, which integrates both the temporal effect and spatial effect and realize the cross-time prediction. The temporal convolution network (TCN) and self-attention mechanism are employed to learn the temporal correlation of each monitoring point and the spatial correlation among different points, respectively. Then, the predicted result obtained from DATCN is compared with that obtained from some classical baselines, including SVR, LR, MLP, and RNNs. Also, the parameters involved in DATCN are discussed to optimize the prediction ability. The prediction result demonstrates that the proposed DATCN model outperforms the state-of-the-art baselines. The prediction accuracy of DATCN model after 24 hours reaches 90 percent. Also, the performance in last 14 hours plays a domain role to predict the short-term behaviors of the structure. As a study case, the proposed model is applied in an underwater shield tunnel to predict the stress variation of concrete segments in space.

• Tunnel and Underground Space
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• v.22 no.2
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• pp.93-105
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• 2012

This paper compares the two- and three-dimensional (2D and 3D) approaches for the numerical determination of the equivalent mechanical properties of fractured rock masses. Both orthogonally-fractured model and discrete fracture networks (DFN) were used for the geometry and 2D models were cut in various directions from 3D model to compare their mechanical properties. Geological data were loosely based on the data available from Sellafield, UK. Analytical method based on compliance tensor transformation was used for investigation in orthogonally fractured rock and numerical experiments were conducted on fractured rock mass with DFN geometry. It is shown that 2D approach always overestimates the elastic modulus of fractured rock masses by a factor of up to around two because fractures are assumed to be perpendicular to the model plane in 2D problems. Poisson ratios tend to have larger values in 2D analysis while there is opposite trend in some sections. The study quantitatively demonstrates the limitation of the 2D approach that uses the simplified model from true 3D geometry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.217-225
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• 2004

Introduction of wave model, considered the effect of shoaling, refraction, diffraction, partial reflection, bottom friction, breaking at the coastal waters of complex bathymetry, is a very important factor for most coastal engineering design and disaster prevention problems. As waves move from deeper waters to shallow coastal waters, the fundamental wave parameters will change and the wave energy is redistributed along wave crests due to the depth variation, the presence of islands, coastal protection structures, irregularities of the enclosing shore boundaries, and other geological features. Moreover, waves undergo severe change inside the surf zone where wave breaking occurs and in the regions where reflected waves from coastline and structural boundaries interact with the incident waves. Therefore, the application of mild-slope equation model in this field would help for understanding of wave transformation mechanism where many other models could not deal with up to now. The purpose of this study is to form a extended mild-slope equation wave model and make comparison and analysis on variation of harbor responses in the vicinities of Ulsan Harbor and Ulsan New Port, etc. due to construction of New Port in Ulsan Bay. This type of trial might be a milestone for port development in macro scale, where the induced impact analysis in the existing port due to the development could be easily neglected.

• The Journal of Engineering Geology
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• v.14 no.4 s.41
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• pp.451-460
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• 2004

The strength of sliding plane is usually assigned on the whole sliding plane with same value in 2D limit equilibrium slope stability method. However, the potential sliding plane is divided into two or three parts which have different sliding resistances. According to the calculation results of 3D slope stability analyses using 4 types of slope cutting models, marginal sliding resistance could affect the safety of slope significantly. In this calculation two kinds of the sliding plane strengths were applied differently to the parts of bottom and margin of the model slope. The effect of marginal resistance was calculated quantitatively. In case of lower sliding resistance of the bottom, the safety factor becomes low in a margin cutting model. However, in case of higher sliding resistance of the bottom, the safety factor decreased slightly in a lower part cutting model and increased in a upper margin cutting model.

• Geomechanics and Engineering
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• v.14 no.1
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• pp.9-17
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• 2018

Brazilian splitting tests, uniaxial compression tests and triaxial compression tests are carried out on the coal samples cored from Shanxi group $II_1$ coal seam of Jiaozuo coal mine, Henan province, China, to obtain their property parameters. Considering the bedding has notable effect on the property parameter of coal, the samples with different bedding angles are prepared. The effects of bedding on the anisotropic characteristics of the coal seam are investigated. A geological geomechanical model is built based on the geology characteristics of the Jiaozuo coal mine target reservoir to study the effects of bedding on the fracture propagations during hydraulic fracturing. The effects of injection pressure, well completion method, in-situ stress difference coefficient, and fracturing fluid displacement on the fracture propagations are investigated. Results show bedding has notable effects on the property parameters of coal, which is the key factor affecting the anisotropy of coal. The hydraulic cracks trends to bifurcate and swerve at the bedding due to its low strength. Induced fractures are produced easily at the locations around the bedding. The bedding is beneficial to form a complicated fracture network. Experimental and numerical simulations can help to understand the effects of bedding on hydraulic fracturing in coalbed methane reservoirs.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.9-23
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• 2002

The purpose of this research was to develop a model that minimizes time and money for deriving topographical property factors and hydro-meteorological property factors, which are used in interpreting flood flow, and that makes it possible to forecast rainfall-runoff using a least number of factors. That is, the research aimed at suggesting a runoff interpretation method that considers the river branching characteristics but not the topographical and geological properties and the land cover conditions, which had been referred in general. The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM). According to the result of examining calculated peak runoff, the Clark Model and the GIUH Model showed relative errors of 1.9~23.9% and 0.8~11.3%, respectively and as a whole, the peak values of hydrograph appeared high. In addition, according to the result of examining the time when peak runoff took place, the relative errors of the Clark Model and the GIUH Model were 0.5~1 and 0~1 hour respectively, and as a whole, peak flood time calculated by the GIUH Model appeared later than that calculated by the traditional Clark Model.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.27-36
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• 2008

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.