• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.25-32
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• 2021

Geotextile tube technology has been perceived as an economical solution for liquid sludge treatment, and analyzing its consolidation behavior is necessary to be able to evaluate the dewatering capabilities of large geotextile tubes filled with contaminated soil, tailings, sewage sludge, and so on. The objectives of this study are to present a method that can adequately convey the consolidation behavior of geotextile tubes filled with sewage sludge, and to investigate the effects of various geotextile tube consolidation parameters. In this study, variable coefficients of consolidation are utilized to analyze the consolidation process of geotextile tubes filled with sewage sludge. The consolidation solution was verified by comparing the measured and predicted data from a hanging bag test conducted in the literature. After verifying the proposed solution, the consolidation parameters of a geotextile tube composed of a woven polypropylene outer layer and a non-woven polypropylene layer filled sewage sludge were obtained. Using the obtained parameters, the consolidation behavior of a large-scale composite geotextiles tube was predicted.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.349-358
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• 2008

In performing the reliability analysis for predicting the settlement with time of alluvial clay layer at Kobe airport, the uncertainties of geotechnical properties were examined based on the stochastic and probabilistic theory. By using Terzaghi's consolidation theory as the objective function, the failure probability was normalized based on AFOSM method. As the result of reliability analysis, the occurrence probabilities for the cases of the target settlement of ${\pm}10%,\;{\pm}25%$ of the total settlement from the deterministic analysis were 30~50%, 60%~90%, respectively. Considering that the variation coefficients of input variable are almost similar as those of past researches, the acceptable error range of the total settlement would be expected in the range of 10% of the predicted total settlement. As the result of sensitivity analysis, the factors which affect significantly on the settlement analysis were the uncertainties of the compression coefficient Cc, the pre-consolidation stress Pc, and the prediction model employed. Accordingly, it is very important for the reliable prediction with high reliability to obtain reliable soil properties such as Cc and Pc by performing laboratory tests in which the in-situ stress and strain conditions are properly simulated.

• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.7-14
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• 2009

The correlation equation empirically proposed to obtain compression indexes has been proposed to conveniently obtain the value using the soil parameter that can be obtained through simple tests when the number of time of consolidation testing is low or the distribution is large but most of the analyzed regions are limited to certain regions abroad or in the country and multiple data were integrated for use in many cases, thus it is not very reasonable to apply it. Therefore, to establish a new design method considering the uncertainty of the ground, it was selected the Kwangyang port area of which the data have been collected recently thus are relatively more reliable as the subject region of the study in order to maximally reduce the uncertainty of test data. After performing the verification of the normality of the consolidation test data obtained from the selected region and the transformation of variables, a prediction formula was proposed through the regression model with the transformed variables and the proposed regression model with transformed variables was compared with existing empirical equations to verify the suitability of the proposed model formula. After analyzing, it was confirmed that the coefficient of determination was increased after the Box-Cox variable transformation, thus the explanatory power was being enhanced and through the root-mean-square-error method, it was confirmed that the proposed model formula showed the most closed value to the test value.

• Journal of the Korean GEO-environmental Society
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• v.5 no.2
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• pp.51-62
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• 2004

Granular compaction piles have the load bearing capacity of the soft ground increase and have the settlement of foundation built on the reinforced soil reduce. The granular compaction group piles also have the consolidation of the soft ground accelerate and have the liquefaction caused by earthquake prevent using the granular materials such as sand, gravel, stone etc. However, this method is one of unuseful methods in Korea. The Granular compaction piles are constructed by grouping it with a raft system. The confining pressure at the center of bulging failure depth is a major variable in relation to estimate for the ultimate bearing capacity of the granular compaction piles. Therefore, a share of loading is determined considering the effect of load concentration ratio between the granular compaction piles and surrounding soils, and varies the magnitude of the confining pressure. In this study, method for the determination of the ultimate bearing capacity is proposed to apply a change of the horizontal pressure considering bulging failure depth, surcharge and loaded area. Also, the ultimate bearing capacity of the granular compaction piles is evaluated on the basis of previous study on the estimation of the ultimate bearing capacity and compared with the results obtained from laboratory scale model tests. And using the result from laboratory model tests, it is studied increase effect of the bearing capacity on the granular compaction piles and variance of coefficient of consolidation for the ground.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.38 no.4 s.117
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• pp.17-23
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• 2006

Paper has fibers and fines network structure and it is strongly affected by interface bond-ing between fibers. Paper structural properties can be determined depending on the inter-fiber bonding. Fines play an important role in Campbell and consolidation effect through wet pressing and drying operations. The fines are essential for the formation of bonds between fibers and for the improvement of strength properties of papers. Since the fines are components of the pulp, there are always two factors to be considered: the quality and quantity of the fines. The quality of fines might be a potential variable to give a more accurate picture of the papermaking potential of the pulp. The object of this study is to investigate the effect of different types of pulp fines on the properties of paper and to access the potential of fines for controlling the bulk of paper. Refined Sw-BKP, Hw-BKP and BCTMP fines were used to investigate the fines effect. Wet-web strength, breaking length, scattering coefficient, and hydrodynamic specific volume, and drying shrinkage were measured. According to the results, chemical and morphological compositions of fines do not strongly affect to wet-web forming by their similar Campbell effect, but strongly affect to drying operation which forms hydrogen bonding among fiber-fines-fiber matrixes. Paper bulk should be controlled by the extent of hydrogen bonding between fibers during drying operation.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.