• Geotechnical Engineering
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• v.13 no.3
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• pp.101-122
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• 1997

A spiting reinforcement system is composed of a series of radially installed reinforcing spites along the perimeter of the tunnel opening ahead of excavation. The reinforcing spill network is extended into the in-situ soil mass both radially and longitudinally The sailing reinforcement system has been successfully used for the construction of underground openings to reinforce weak rock formations on several occasions. The application of this spiting reinforcement system is currently extended to soft ground tunneling in limited occasions because of lack of reliable analysis and design methods. A method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground is presented. The shape of the potential failure wedge for the case of smile-reinforced shallow tunnel is assumed on the basis of the results of three dimensional finite element analyses. A criterion to differentiate the spill-reinforced shallow tunnel from the smile-reinforced deep tunnel is also formulated, where the tunnel depth, soil type, geometry of the tunnel and reinforcing spites, together with soil arching effects, are considered. To examine the suitability of the proposed method of threedimensional stability analysis in practice, overall stability of the spill-reinforced shallow tunnel at facing is evaluated, and the predicted safety factors are compared with results from twotimensional analyses. Using the proposed method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground, a parametric study is also made to investigate the effects of various design parameters such as tunnel depth, smile length and wadial spill spacing. With slight modifications the analytical method of threeiimensional stability analysis proposed may also be extended for the analysis and design of steel pipe reinforced multi -step grouting technique frequently used as a supplementary reinforcing method in soft ground tunnel construction.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.589-597
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• 2016

In this study, we investigated the use of satellite-derived flow (SDF) signals and a data-based model for the estimation of outflow for the river reach where in situ measurements are either completely unavailable or are difficult to access for hydraulic and hydrology analysis such as the upper basin of Imjin River. It has been demonstrated by many studies that the SDF signals can be used as the river width estimates and the correlation between SDF signals and river width is related to the shape of cross sections. To extract the nonlinear relationship between SDF signals and river outflow, Artificial Neural Network (ANN) model with SDF signals as its inputs were applied for the computation of flow discharge at Imjin Bridge located in Imjin River. 15 pixels were considered to extract SDF signals and Partial Mutual Information (PMI) algorithm was applied to identify the most relevant input variables among 150 candidate SDF signals (including 0~10 day lagged observations). The estimated discharges by ANN model were compared with the measured ones at Imjin Bridge gauging station and correlation coefficients of the training and validation were 0.86 and 0.72, respectively. It was found that if the 1 day previous discharge at Imjin bridge is considered as an input variable for ANN model, the correlation coefficients were improved to 0.90 and 0.83, respectively. Based on the results in this study, SDF signals along with some local measured data can play an useful role in river flow estimation and especially in flood forecasting for data-scarce regions as it can simulate the peak discharge and peak time of flood events with satisfactory accuracy.

• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.5-16
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• 2007

The simple linear elastic-perfectly plastic model with soil parameters $s_u,\;E_u$ and n of undrained condition is usually applied to predict the displacement of a constructed diaphragm wall(DW) on soft soils during excavation. However, the application of this soil model for finite element analysis could not interpret the continued increment of the lateral displacement of the DW for the large and deep excavation area both during the elapsed time without activity of excavation and after finishing excavation. To study the characteristic behaviors of soil behind the DW during the periods without excavation, a series of tests on soft Bangkok clay samples are simulated in the same manner as stress condition of soil elements happening behind diaphragm wall by triaxial tests. Three kinds of triaxial tests are carried out in this research: $K_0$ consolidated undrained compression($CK_0U_C$) and $K_0$ consolidated drained/undrained unloading compression with periodic decrement of horizontal pressure($CK_0DUC$ and $CK_0UUC$). The study shows that the shear strength of series $CK_0DUC$ tests is equal to the residual strength of $CK_0UC$ tests. The Young's modulus determined at each decrement step of the horizontal pressure of soil specimen on $CK_0DUC$ tests decreases with increase in the deviator stress. In addition, the slope of Critical State Line of both $CK_0UC$ and $CK_0DUC$ tests is equal. Moreover, the axial and radial strain rates of each decrement of horizontal pressure step of $CK_0DUC$ tests are established with the function of time, a slope of critical state line and a ratio of deviator and mean effective stress. This study shows that the results of the unloading compression triaxial tests can be used to predict the diaphragm wall deflection during excavation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.6
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• pp.369-377
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• 2005

Precise application of topdressing nitrogen (N) fertilizer is indispensible for securing high yield and good quality of rice and minimizing N losses to the environment as well. For precise N management, growth and nitrogen nutrition status (NNS) should be diagnosed rapidly and accurately. The objective of the study was to evaluate the applicability of vegetation index (VI) calculated from hyperspectral canopy reflectance measurement and SPAD reading to nondestructive in situ diagnosis of growth and NNS of rice. Canopy reflectance, SPAD read­ing, growth parameters, and NNS characteristics were measured from various N treatments to evaluate the relationships among them for two cropping seasons from 2001 to 2002. The correlation coefficient of VIs with variables of growth and NNS increased positively as rice canopy became more closed. Regardless of growth stages, VIs had significantly high correlations with LAI, shoot dry weight (DW), shoot N content and nitrogen nutrition index (NNI). Those correlation coefficients increased steadily before heading stage as rice grew up. However, tiller number and leaf N concentration showed significantly high correlations with VIs only at and after panicle initiation stage (PIS). Among the VIs, RVIgreen had significantly higher correlation with the measured parameters than the other VIs: it showed correlation coefficients greater than 0.8 with leaf and shoot N concentration and DW, and much higher coefficients greater than 0.9 with LAI, shoot N content, and NNI. At LAI of below 2.5, VIs had non-significant or low correlations with the growth and NNS indicators due to the background effects. SPAD reading had significantly high correlation with leaf N concentration and NNI at each growth stage. In addition, it had significant correlations with variables of growth and NNS at PIS and booting stage, particularly, at booting stage. Though SPAD reading had a significantly high correlation value at a given growth stage in each year, it showed very weak relationship with variables of growth and NNS when pooled across growth stages and years. In conclusion, RVIgreen was found to be the most reliable VI to estimate the growth and NNS of rice around at PIS, but SPAD reading had much limitations.

• Clean Technology
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• v.29 no.1
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• pp.10-21
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• 2023

Hydrogels that are made of natural polymer-based double networks have excellent biocompatibility, low cytotoxicity, and high water content, assuring that the material has the properties required for a variety of biomedical applications. However, hydrogels also have limitations due to their relatively weak mechanical properties. In this study, hydrogels based on an alginate di-aldehyde (ADA) and gelatin (Gel) double network that is reinforced with additional hydrogen bonds formed between the hydroxyl (-OH) groups of the hyperbranched polymer (HPG) and the functional groups present inside of the hydrogels were successfully synthesized. The enhanced mechanical properties of these synthesized hydrogels were evaluated by varying the amount of HPG added during the hydrogel synthesis from 0 to 25%. In addition, magnetite nanoparticles (Fe₃O₄ NPs) were synthesized within the hydrogels and the structures and the magnetic properties of the hydrogels were also characterized. The hydrogels that contained 15% HPG and Fe₃O₄ NPs exhibited superparamagnetic behaviors with a saturation magnetization value of 3.8 emu g^-1. These particular hydrogels also had strengthened mechanical properties with a maximum compressive stress of 1.1 MPa at a strain of 67.4%. Magnetic hydrogels made with natural polymer-based double networks provide improved mechanical properties and have a significant potential for drug delivery and biomaterial application.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.