• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.2
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• pp.115-128
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• 2006

The structural anisotropy and heterogeneity of rock mass, caused by discontinuities and weak zones, have a great influence on the deformation behavior of a tunnel. A tunnel construction in these complex ground conditions is very difficult. No matter how excellent a geological investigation is, local uncertainties of rock mass conditions still remain. Under these uncertain circumstances, an accurate forecast of the ground conditions ahead of the advancing tunnel face is indispensable to a safe and economic tunnel construction. This paper presents the effect of anisotropy and heterogeneity of the rock masses to be excavated by numerical analysis. The influences of distance from weak zone, the size or dimension, the different stiffness and the orientation of weak zones are analysed by 3-D finite element analysis. By analysing these numerical results, the tunnel behavior due to excavation can be well understood and the prediction of rock mass condition ahead of the tunnel face can be possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.383-390
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• 2006

In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

• Journal of Korean Society on Water Environment
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• v.40 no.3
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.126-133
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• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.42-55
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• 2008

To evaluate the accuracy of currents measured by HF radar in the coastal sea off Keum River estuary, we compared the facing radial vectors of two HF radars, and HF radar-derived currents with in-situ measurement currents. Principal component analysis was used to extract regression line and RMS deviation in the comparison. When two facing radar's radial vectors at the mid-point of baseline are compared, RMS deviation is 4.4 cm/s in winter and 5.4 cm/s in summer. When GDOP(Geometric Dilution of Precision) effect is corrected from the RMS deviations that is analyzed from the comparison between HF radar-derived and current-metermeasured currents, the error of velocity combined by HF radar-derived current is less than 5.1 cm/s in the stations having moderate GDOP values. These two results obtained from different method suggest that the lower limit of HF radar-derived current's accuracy is 5.4 cm/s in our study area. As mentioned in previous researches, RMS deviations become large in the stations located near the islands and increase as a function of mean distance from the radar site due to decrease of signal-to-noise level and the intersect angle of radial vectors. We found that an uncertain error bound of HF radar-derived current can be produced from the separation process of RMS deviations using GDOP value if GDOP value for each component is very close and RMS deviations obtained from current component comparison are also close. When the current measured in the stations having moderate GDOP values is separated into tidal and subtidal current, characteristics of tidal current ellipses analyzed from HF radar-derived current show a good agreement with those from current-meter-measured current, and time variation of subtidal current showed a response reflecting physical process driven by wind and density field.