• Journal of the Society of Naval Architects of Korea
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• v.51 no.4
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• pp.274-282
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• 2014

Time series of the dynamic response of a slender marine structure was predicted using quadratic Volterra series. The wave-structure interaction system was identified using the NARX(Nonlinear Autoregressive with Exogenous Input) technique, and the network parameters were determined through the supervised training with the prepared datasets. The dataset used for the network training was obtained by carrying out the nonlinear finite element analysis on the freely standing riser under random ocean waves of white noise. The nonlinearities involved in the analysis were both large deformation of the structure under consideration and the quadratic term of relative velocity between the water particle and structure in Morison formula. The linear and quadratic frequency response functions of the given system were extracted using the multi-tone harmonic probing method and the time series of response of the structure was predicted using the quadratic Volterra series. In order to check the applicability of the method, the response of structure under the realistic ocean wave environment with given significant wave height and modal period was predicted and compared with the nonlinear time domain simulation results. It turned out that the predicted time series of the response of structure with quadratic Volterra series successfully captures the slowly varying response with reasonably good accuracy. It is expected that the method can be used in predicting the response of the slender offshore structure exposed to the Morison type load without relying on the computationally expensive time domain analysis, especially for the screening purpose.

• Magazine of the Korea Concrete Institute
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• v.2 no.1
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• pp.91-100
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• 1990

In most of the structural members with initial cracks(or initial notches), the strength tends to decmase as the member size increases. This phenomenon is known as size effect. Among the structural materials of glass, metal or concrete, etc., concrete represents the size effect even without initial crack. According to the previous size effect law, the concrete mem¬ber of very large size can resist little stress. Actually, however, even the large size member can resist some stress if there is no initial crack made artificially, consequently showing a rather milder strength reduction compared to the severe strength reduction by tbe previously derived size effect law. In this study, the theoretical size effect law previously derived by Z.P. Bazant was discussed based on nonlinear fracture mechanics of concrete structures With dissimilar initial cracks, and the prediction models are proposed by regression analysis with the existing test data of more large size speciments for splitting tensile strength, shear strength and uniaxial compressive strength tests.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.2
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• pp.91-102
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• 1990

The representative tests in this study are performed at a selected site which has the soil layers to analyze the safety and economy of the dynamic analysis for the variable soil conditions. Crosshole test and downhole test of small strain level tests and triaxial test of large strain level test are performed in the soil layers, and in the rock layers, crosshole test and downhole in-situ tests and laboratory sonic test are performed to measure the dynamic shear modulus, damping ratio, and Poisson$\acute{s}$ ratio of the soil and the rock. The correlations between the dynamic soil properties from the tests and the basic soil properties are determined through the regression analysis. The representative design value of the soil is determined by probability analysis of the test results. It is determined from the nonlinear stress-strain model in soils, and the value at small strain level is computed in rocks according to the distribution of the type of soils and the affecting variables. The constitutive value is systematized to be utilized in the analysis of the test results, and computation of the input soil data.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.84-93
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• 1999

Determination of grain size of heat-treated stainless steel based fm digital ultrasonic signal processing technique is presented. This techniques consist in evidence accumulation with multiple feature parameters, difference absolute mean value(DAMV), variance(VAR), mean frequency (MEANF), auto regressive model coefficient(ARC) and linear cepstrum coefficient(LCC). Feature parameters were extracted from ultrasonic echo signal of heat-treated metals. It was found that a few parameters might not be sufficient to exactly evaluate the grain size of heat-treated metals. The determination of grain size of heat-treated metals was carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. In the work presented, heat-treated stainless steel samples with various grain sizes are examined. The processed experimental results supports the feasibility of the grain size determination technique presented.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.2
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• pp.177-186
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• 2017

This study concerned the analysis on the efficiency of the conversion of water tank type supply system to direct water supply system to examine the feasibility of the conversion, as well as the calculation of optimal conversion range that enables the supply of safe, high-quality water at stable pressure in accordance with the standards of water supply facility. The results of this research showed that when converting water supply system from water tank type supply system to direct water supply system, more nodal points could be properly converted and more reduction of electricity usage was expected in case water pressure rather than residence time was fixed. This means that higher efficacy can be obtained by fixing water pressure when converting water supply system. However, since the number of the locations that received on-spot inspection was small and the electricity usage measured was not exclusively by water supply facility, it is difficult to judge that such reduction of electricity usage accurately represents reduced electricity usage by water supply facility alone. therefore, after having secured on-spot information about a larger number of locations in apartment complexes that have converted water supply system, and utilizing information about electricity usage exclusively by water supply facility, the proposed method of this research could be applied to accurately deducing expected reduction of electricity usage by water supply facilities of various other apartment complexes. It is also considered possible to deduce an effective operation method of water supply system by finding out an area that shows low pressure or low residual chlorine concentration in the optimal conversion range of water supply, followed by estimating the proper location of pumping station or the proper chlorine dosage at the power purification plant that supply water to the target area.

• Atmosphere
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• v.25 no.4
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• pp.669-683
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• 2015

In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

• Journal of the Korean association of regional geographers
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• v.8 no.4
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• pp.529-541
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• 2002

This paper aims to provide a context-specific interpretation on the shifting process of in-house R&D spaces in a large Korean firm in the context of rapidly changing markets and technology. Drawing on the case study of LG Electronics Company, one of the Korea's flagship companies, I examine the causes and mechanisms leading to a shift in domestic R&D spaces and the nature of learning processes between R&D teams and between R&D and other organizational units, particularly manufacturing. It appears that the current reshaping processes of domestic R&D spaces in LGE focus more on the clustering of core R&D laboratories than the geographical integration of conception and execution. However, it should not simply be viewed that such a move would be reduced to the linear model of innovation and organizational learning. Instead, it involves the firm-specific mode of regulating organizational competences. As contextual variables to induce such a firm-specific mode of organizational change, I consider the spatial form of organization, the spatial sources of knowledge and learning, and the powers of relational learning that can be made between distanciated actors and teams.

• Journal of Korean Society of Steel Construction
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• v.21 no.6
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• pp.609-618
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• 2009

This paper proposes a versatile formula which can be used to evaluate the fire resistant time of steel beams under various design conditions. Towards this end, the key parameters which affect the fire performance of steel beams were first determined through thermo-mechanical considerations, and classified into two groups: structural parameters and thermal parameters. Then the degree of influence of each parameter on the fire performance was investigated through a fully coupled thermo-mechanical analysis up to the occurrence of run-away deflection. The accuracy of the numerical model used was verified using an available full-scale fire test before conducting an extensive parametric analysis. Multiple linear regression analysis was performed to obtain the formula which can be used to predict the fire resistance time of steel beams under various design conditions. The statistical analysis showed that the proposed formula is very robust. The application of the formula in practical fire design under the current code was illustrated in detail. The economy and other advantages of the proposed formula were clearly shown.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.2
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• pp.165-169
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• 1999

Experiments were conducted to evaluate a experimental model developed for the protein removal by foam separation. The foam separator was operated in well-mixed tank which would be considered as a completely mixed condition. The feasibility of foam separation to remove protein from sea water was investigated. Protein removal characteristics of the foam separator were obtained by batch experiments. To find the effect of the operating parameter to protein removal rate, the foam separation was carried with variation of initial protein concentration and superficial air velocity. The result indicated that the protein removal efficiency was increased with increasing protein concentration and superficial air velocity. The relationship between operation parameters and protein removal rate were evaluated by non-linear regression as the form of exponential function, Using both relationships, the simplified model was determined. The simplified foam separator operation model was verified by the batch operation. The simulation results showed a good relationship with the experimental data.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.109-127
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• 2011

Atmospheric aerosols, small particles in the atmosphere, are one of the important parameters in climate change and human health. Additionally, accurate estimates of aerosol species are increasingly important in environmental impact assessment studies. Recent advances in global satellite remote sensing provide powerful tool for air quality monitoring. This study explores the potential usage of satellite derived data such as atmospheric aerosols for air quality monitoring as well as climate change study. The objectives of this study is to understand the general features of the global distribution of type dependent aerosols. A detailed spatio-temporal variability of the each different satellite dataset shows the variation of the global zonal average and specific geographical regions where the strong emission sources are located. Especially, significantly large aerosol amounts are observed in Asia and Africa because of the desert dust storm, anthropogenic and biomass burning emissions.