• Journal of the Society of Disaster Information
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• v.10 no.2
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• pp.244-252
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• 2014

In this study, seismic responses of the offshore wind tower supported by bucket foundation are analyzed in consideration of soil-structure interaction. The program SASSI is used as analyzing tool and an artificial seismic input for soft soil is used as input motion. The H/R ratio of bucket, the stiffness of bucket foundation and the soil stiffness are considered as parameters and its effects are estimated. The responses of structure are obtained at the base and the nacell. As results, the effects of H/R ratio, the stiffness of bucket and the stiffness of site are generally denoted different response tendency at the base and the nacell. However, these whole responses of the base and the nacell are much lager than that of rock site. Therefore, the consideration of this phemomia affect to the response of offshore wind tower with bucket foundation largely.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.357-360
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• 1997

Abstract: In teleoperation field robotic system such as hydraulically actuated robotic excavator, the maneuverability and convenience is the most important part in the operation of robotic excavator. Particularly the force information is important in dealing with digging and leveling operation in the teleoperated excavator. Excavators are also subject to a wide variation of soil-tool interaction forces. This paper presents a new force reflecting joystick in a velocity-force type bilateral teleoperation system. The master system is electrical joystick and the slave system IS hydraulically actuated cylinder with linear position sensor. Particularly Pneumatic motor is used newly in the master joystick for force reflection and the information of the pressure of salve cylinder is measured and utilized as the force feedback signal. Also force-reflection gain greatly affects the excavation performance of a hydraulically actuated robotic system and it is very difficult to determine it appropriately since slave excavator contacts with various environments such as from soft soil to rock. To overcome this, this paper proposes a force-reflection gain selecting algorithm based on artificial neural network and fuzzy logic.

• Journal of Soil and Groundwater Environment
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• v.7 no.1
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• pp.63-77
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• 2002

Salinization is an important environmental problem encountered in coastal aquifers. In order to evaluate the salinization problem in the western coastal area of Korea, we have performed a regional hydrochemical study on shallow well groundwaters (N=229) collected within 10 km away from the coastline. The concentrations of analyzed solutes are very wide in range, suggesting that the hydrochemistry is controlled by several processes such as water-rock interaction, seawater mixing, and anthropogenic contamination. Based on the graphical interpretation of cumulative frequency curves for some hydrochemical parameters (esp., $Cl^{-}$ and ${NO_3}^-$), the collected water samples were grouped into two major populations (1) a background population whose chemistry is predominantly affected by water-rock interaction, and (2) an anomalous population which records the potential influences by either seawater mixing or anthropogenic pollution. The threshold values obtained are 34.7 mg/l for $Cl^{-}$ and 37.2 mg/l for ${NO_3}^-$, Using these two constituents, groundwaters were further grouped into four water types as follows (the numbers in parenthesis indicate the percentage of each type water) : (1) type 1 waters (38%) that are relatively poor in $Cl^{-}$ and ${NO_3}^-$, which may represent their relatively little contamination due to seawater mixing and anthropogenic pollution; (2) type 2 waters (21%) which are enriched in $Cl^{-}$, Indicating the considerable influence by seawater mixing; (3) ${NO_3}^-$-rich, type 3 waters (11%) which record significant anthropogenic pollution; and (4) type 4 waters (30%) enriched in both $Cl^{-}$ and ${NO_3}^-$, reflecting the effects of both seawater mixing and anthropogenic contamination. The results of the water type classification correspond well with the grouping on a Piper's diagram. On a Br x $10^4$versus Cl molar ratio diagram, most of type 2 waters are also plotted along or near the seawater mixing line. The discriminant analysis of hydrochemical data also shows that the classification of waters into four types are so realistic to adequately reflect the major process(es) proposed for the hydrochemical evolution of each water type. As a tool for evaluating the degree of seawater mixing, we propose a parameter called 'Seawater Mixing Index (S.M.I.)’ which is based on the concentrations of Na, Mg, Cl, and $SO_4$. All the type 1 and 3 waters have the S.M.I. values smaller than one, while type 2 and type 4 waters mostly have the values greater than 1. In the western coastal area of Korea, more than 21% of shallow groundwaters appear to be more or less affected by salinization process.

• Proceedings of the Mineralogical Society of Korea Conference
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• 2001.06a
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• pp.38-39
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• 2001

The seasonal changes in pH, Fe, Al and SO$_4$$\^$2-/ contents of acid drainage released from coal mine dumps play a major role in precipitation of metal hydroxides in the Taebaek coal field area, southeastern Korea. Precipitates in the creeks underwent a cycle of the color change showing white, reddish brown and brownish yellow, which depends on geochemical factors of the creek waters. White precipitates consist of Al-sulfate (basaluminite and hydrobasaluminite) and reddish brown ones are composed of ferrihydrite and brownish yellow ones are of schwertmannite. Goethite coprecipitates with ferrihydrite and schwertmannite. Ferrihydrite formed at higher values than pH 5.3 and schwertmannite precipitated below pH 4.3, and goethite formed at the intermediate pH range between the two minerals. With the pH being increased from acid to intermediate regions, Fe is present both as schwertmannite and goethite. From the present observation, the most favorable pH that basauluminte can precipitate is in the range of pH 4.45-5.95. SEM examination of precipitates at stream bottom shows that they basically consist of agglomerates of spheroid and rod-shape bacteria. Bacteria species are remarkably different among bottom precipitates and, to a less extent, there are slightly different chemical compositions even within the same bacteria. The speciation and calculation of the mineral saturation index were made using MINTEQA2. In waters associated with yellowish brown precipitates mainly composed of schwertmannite, So$_4$ species is mostly free So$_4$$\^$2-/ ion with less AlSo$_4$$\^$+/, CaSo$\sub$(aq)/, and MgSo$\sub$4(aq)/. Ferrous iron is present mostly as free Fe$\^$2+/, and FeSo$\sub$4(aq)/ and ferric iron exists predominantly as Fe(OH)$_2$$\^$+/, with less FeSo$\sub$4(aq)/, Fe(OH)$_2$$\^$-/, FeSo$_4$$\^$-/ and Fe$\^$3+/, respectively Al exists as free Al$\^$3+/, AlOH$_2$$\^$-/, (AlSo$_4$)$\^$+/, and Al(So$_4$)$\^$2-/. Fe is generally saturated with respect to hematite, magnetite, and goethite, with nearly saturation with lepidocrocite. Aluminum and sulfate are supersaturated with respect to predominant alunite and less jubanite, and they approach a saturation state with respect to diaspore, gibbsite, boehmite and gypsum. In the case of waters associated with whitish precipitates mainly composed of basaluminite, Al is present as predominant Al$\^$3+/ and Al(SO$_4$)$\^$+/, with less Al(OH)$\^$2+/, Al(OH)$_2$$\^$+/ and Al(SO$_4$)$\^$2-/. According to calculation for the mineral saturation, aluminum and sulfate are greatly supersaturated with respect to basaluminite and alunite. Diaspore is flirty well supersaturated while jubanite, gibbsite, and boehmite are already supersaturated, and gypsum approaches its saturation state. The observation that the only mineral phase we can easily detect in the whitish precipitate is basaluminite suggests that growth rate of alunite is much slower than that of basaluminite. Neutralization of acid mine drainage due to the dilution caused by the dilution effect due to mixing of unpolluted waters prevails over the buffering effect by the dissolution of carbonate or aluminosilicates. The main factors to affect color change are variations in aqueous geochemistry, which are controlled by dilution effect due to rainfall, water mixng from adjacent creeks, and the extent to which water-rock interaction takes place with seasons. pH, Fe, Al and SO$_4$ contents of the creek water are the most important factors leading to color changes in the precipitates. A geochemical cycle showing color variations in the precipitates provides the potential control on acid mine drainage and can be applied as a reclamation tool in a temperate region with four seasons.