• Journal of the Korean Geotechnical Society
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• v.24 no.6
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• pp.57-67
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• 2008

Two test methods, nonrepetitive plate loading test (NPLT) and repetitive plate loading test (RPLT) are being used to control the quality of compaction through the evaluation of the stiffness of subgrade soils in the Korea railway industry. Subgrade reaction modulus ($k_{30}$) from the NPLT and strain modulus ($E_v$) from the RPLT are the index values to check them. The methods have similar aspects, but they differ in the modulus evaluation method, the numbers of loading stage, termination procedures, etc. This paper analyses the differences of the two test methods and evaluates the relationship between subgrade reaction modulus and strain modulus. In order to develop the relationship, total 22 tests were performed including the NPLT and the RPLT at the 6 original grounds, and 5 upper or lower subgrades in Kyungbu High Speed Railway II stage construction sites. According to the soil conditions, the relationship between subgrade reaction modulus and strain modulus was proposed with corrections by considering strain states, mean confining pressures, and Poisson's ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.367-377
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• 2008

As part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, resistance factors for static bearing capacity of driven steel pipe piles were calibrated in the framework of reliability theory. The 57 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and these load test piles were sorted into two cases: SPT N at pile tip less than 50, SPT N at pile tip equal to or more than 50. The static bearing capacity formula and the Meyerhof method using N values were applied to calculate the expected design bearing capacities of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative measured bearing capacities with the expected design values. Reliability analysis was performed by two types of advanced methods: the First Order Reliability Method (FORM), and the Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, in consideration of the reliability level of the current design practice, redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure. Resistance factors of driven steel pipe piles were recommended based on the results derived from the First Order Reliability Method and the Monte Carlo Simulation method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1C
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• pp.19-29
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• 2008

As a part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, reliability analyses for driven steel pipe piles are performed and the target reliability indices are selected carefully. The 58 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and analyzed to determine the representative bearing capacities of the piles. The static bearing capacity formula and the Meyerhof method using N values are applied to calculate the expected design bearing capacity of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative bearing capacities with the design values. Reliability analysis was performed by two types of advanced methods: First Order Reliability Method (FORM), and Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The static bearing capacity formula exhibited relatively small variation, whereas the Meyerhof method showed relatively high inherent conservatism in the resistance bias factors. Reliability indices for safety factors in the range of 3 to 5 were evaluated respectively as 1.50~2.89 and 1.61~2.72 for both of the static bearing capacity formula and the Meyerhof method. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, based on the reliability level of the current design practice and considering redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure.

• Journal of Bio-Environment Control
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• v.17 no.4
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• pp.288-292
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• 2008

This study was conducted to identify the effects of irrigation amount to produce high quality melon fruit in fertigation culture. Irrigation amount of during fruit harvesting period was doubled at the low irrigation point ($(-45{\sim}50\;kPa$) treatment as 115 mm as than that of the high irrigation point ($-20{\sim}25\;kPa$) treatment. The plant growth rates such as stem length, leaf weight and plant height were a little diminished at the low irrigation point ($-45{\sim}50\;kPa$) than those of the other treatments. Internode length was however not affected by irrigation amount. Fruit weight was lighter at the low irrigation point ($-45{\sim}50\;kPa$) than that of at the high irrigation point and fruit height was shorter, but fruit diameter was not affected by irrigation amount. Fruit soluble solid was $0.9^{\circ}Bx$ higher at the low irrigation point ($-45{\sim}50\;kPa$) than at the high irrigation point ($-20{\sim}25\;kPa$) and net index was higher. Total marketable yield was highest by 3,937 kg/10a at the high irrigation point ($-20{\sim}25\;kPa$), but the excellent marketable yield was highest by 2,531 kg/10a at the low irrigation point ($-45{\sim}50\;kPa$). Inorganic contents of the soil N, K, Ca and Mg were not affected by irrigation amount. It was therefore thought that optimum irrigation point to produce high quality melon fruit by fertigation culture was $-45{\sim}50\;kPa$ at ripening stage.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.5
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• pp.408-419
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• 2006

A pot experiment was conducted for two years to evaluate the effects of purified Si fertilization combined with $^{15}N$ on the nutrient uptake, plant growth characteristics, and photosynthetic characteristics of rice in water melon cultivated soil. In 2002, plant height was positively affected at 25 DAT (Day After Transplanting) by Si fertilization in 100%N treatment. However, in 2003, plant height at 25 DAT was negatively affected by Si fertilization in low N level but it was reversed in high N level with initial increase of plant height. Tiller number per pot was positively affected by N and Si fertilization level, especially for high N fertilized treatment. Leaf color was positively affected by Si fertilizatlon in no N fertilized pots, however, Si was not effected in 50%N and 100%N fertilized treatments. N harvest index (NHI) increased with increased Si fertilization in no N plots, however it decreased with increasing of N fertilization level. Nitrogen use efficiency (NUE) decreased with increasing of fertilized N but Si fertilization increased NUE in 50%N plots, however, it was not different by the Si fertilization level in 100%N plots. In 50%N+200%Si plots, NUE was greatest with 130 and shoot N content was $16.2g-N/m^{2}$. N content ($g/m^{2}$) in rice plant increased with increasing Si fertilization in no N plots at panicle initiation stage, 50 and 100%N plots at heading stage and all N treatment at harvesting time. This was mostly more efficient in late growth stage than early growth stage. The concentration (%) of P and K increased with increasing N fertilization level at heading and harvesting but it was not significantly different by the Si fertilization treatment except a little decreasing with increasing Si fertilization level at heading. Potassium content was also not significantly related with N fertilization level except increasing with Si fertilization level at panicle initiation stage. Plant Ca content (%) decreased with increasing of Si fertilization at heading stage and Si fertilization increased Ca content at panicle initiation stage and heading stage and it increased with increasing of Si fertilization level. Photosynthetic activity was not directly related with Si fertilization amount, however, Fluorescent factors, Fv'/Fm' and PsII, were positively affected by Si fertilization level. In conclusion, N fertilization in Si 200% fertilized condition should be reduced by about 50% level of recommended N fertilization for rice cropping in green-house water-melon cultivated paddy field. However, improvement of Ps by Si fertilization could not be attributed to Ps activity in the same leaf area but because of increased total leaf area per pot improved fluorescent characteristics.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.