• Structural Engineering and Mechanics
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• v.59 no.3
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• pp.455-473
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• 2016

Methods for the seismic demands evaluation of structures require iterative procedures. Many studies dealt with the development of different inelastic spectra with the aim to simplify the evaluation of inelastic deformations and performance of structures. Recently, the concept of inelastic spectra has been adopted in the global scheme of the Performance-Based Seismic Design (PBSD) through Capacity-Spectrum Method (CSM). For instance, the Modal Pushover Analysis (MPA) has been proved to provide accurate results for inelastic buildings to a similar degree of accuracy than the Response Spectrum Analysis (RSA) in estimating peak response for elastic buildings. In this paper, a simplified nonlinear procedure for evaluation of the seismic demand of structures is proposed with its applicability to multi-degree-of-freedom (MDOF) systems. The basic concept is to write the equation of motion of (MDOF) system into series of normal modes based on an inelastic modal decomposition in terms of ductility factor. The accuracy of the proposed procedure is verified against the Nonlinear Time History Analysis (NL-THA) results and Uncoupled Modal Response History Analysis (UMRHA) of a 9-story steel building subjected to El-Centro 1940 (N/S) as a first application. The comparison shows that the new theoretical approach is capable to provide accurate peak response with those obtained when using the NL-THA analysis. After that, a simplified nonlinear spectral analysis is proposed and illustrated by examples in order to describe inelastic response spectra and to relate it to the capacity curve (Pushover curve) by a new parameter of control, called normalized yield strength coefficient (${\eta}$). In the second application, the proposed procedure is verified against the NL-THA analysis results of two buildings for 80 selected real ground motions.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.2
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• pp.122-129
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• 2014

Identification of the whipping response out of the combined wave-vibration response of a flexible sea going vessel is one of the most interesting research topic from ship designer's point of view. In order to achieve this goal, a novel methodology based on the wavelet cross-correlation technique was proposed in this paper. The cross-correlation of the wavelet power spectrum averaged across the frequency axis was introduced to check the similarity between the combined wave-vibration response and impulse response. The calculated cross-correlation of the wavelet power spectrum was normalized by the auto-correlation of the each spectrum with zero time lag, eventually providing the cross-correlation coefficient that stays between 0 and 1, precisely indicating the existence of the impulse response buried in the combined wave-vibration response. Additionally, the weight function was introduced while calculating the cross-correlation of the two spectrums in order to filter out the signal of lower frequency so that the accuracy of the similarity check becomes as high as possible. The validity of the proposed methodology was checked through the application to the artificially generated ideal combined wave-vibration signal, together with the more realistic signal obtained by running 3D hydroelasticity program WISH-Flex. The correspondence of the identified whipping instances between the results, one from the proposed method and the other from the calculated slamming modal force, was excellent.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.495-502
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• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.166-174
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• 2009

The liquid column trajectory and column breakup length characteristics have been experimentally studied in angled jets injected into subsonic crossflow. Pulsed shadowgraph photography and Planar Liquid Laser Induced Fluorescence measurements were used to determine the angled effects. And the main objectives of this research are to get a empirical formula of liquid column trajectory and breakup length with below the $90^{\circ}$ degree injection angle conditions, and were compared with previous results. It was also found that the empirical formula, which reversed injection conditions of air stream. As the result, This has been shown that liquid column trajectories and column breakup length were spatially dependent on various injection angle, normalized injector exit diameter, air-stream and fuel injection velocity. Furthermore, the empirical formula of liquid column trajectories and breakup length has been some different of drag coefficient results between normal angled injection and reversed injection in subsonic crossflow.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.1
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• pp.16-28
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• 2014

This paper presents a novel high-power-factor circuit topology of AC to AC current-fed type high frequency resonant inverter which includes the function of power factor correction(PFC) in the proposed inverter to operate the AC input block with high power factor. The proposed circuit topology of AC to AC current fed type high resonant inverter removes DC link electrolytic capacitor and has also the one of power factor correction(PFC) in the inverter circuit without an additional PFC circuit since the input current by constituting it in parallel as an unit inverter, which assumes the class-E high frequency resonant inverter of conventional current-fed type, flows in the form of the resultant current flowing through each constant current reactor($L_{d1}$, $L_{d2}$). The circuit analysis of proposed inverter is generally described by adopting the normalized parameters and the evaluation of its operating characteristics are conducted by using the parameters such as the ratio of switching and resonant frequency(${\mu}$), coupling coefficient(k) and so on. An example of procedure for circuit design based on the characteristic values obtained from the theoretical analysis is presented. To confirm the validity of the theoretical analysis, the experimental results are also presented. In the future, the proposed inverter shows it can be practically used as power supply system for induction heating application, DC-DC converter etc.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.6 no.2
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• pp.165-175
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• 1996

Fourteen(14) large commercial buildings located in Seoul with friable sprayed-on surface insulation material on ceiling were investigated for fiber types in bulk material and for airborne fiber concentrations in buildings by transmission electron microscopy (TEM) in order to compare the results with those by polarized light microscopy (PLM) and phase contrast microscopy (PCM). The results were as follows: 1. Chrysotile asbestos was found in one bulk sample out of total 14 bulk samples collected. Glass fiber and mineral wool were the two major constituents of the bulk samples. 2. The Na-Mg-Si-Ca-Fe-Al ratios of the EDX spectra which were normalized with the Si peak were 0-1.0-10-8.3-4.0-4.0 in mineral wool and 0-5-10-21-0-0 in chrysotile asbestos, respectively. 3. Airborne fiber concentrations were log-normalcy distributed and the geometric mean (geometric standard deviation) fiber concentrations by TEM in the underground parking lots and inside buildings were 0.0048 f/cc(1.93) and 0.0040 f/cc(2.27), respectively with no statistical difference. In the outdoor ambient air, statistically significantly lower concentration of 0.0018 f/cc(2.04) was measured. 4. The TEM/PCM ratios of airborne fiber concentrations ranged 0.5 - 2.0 for 80 % of airborne samples analyzed, end the regression equation between TEM and PCM was PCM=-0.2724+1.1355(TEM) with the coefficient of determination $R^2=0.52$. The results of this study confirmed that the sprayed-on surface insulation material found in some commercial buildings may possibly be contaminated with asbestos fiber. Since statistically significant relationship of fiber concentrations measured by PCM and TEM inside buildings and ambient air was found, previous results by PCM in ambient air could be used to estimate the ambient fiber concentrations in knowing the ratio of TEM/PCM.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.297-304
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• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.153-153
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• 2019

Evapotranspiration (ET) is an important component of hydrological processes. Accurate estimates of ET variation are of vital importance for natural hazard adaptation and water resource management. This study first developed a soil water index (SWI)-based Priestley-Taylor algorithm (SWI-PT) based on the enhanced vegetation index (EVI), SWI, net radiation, and temperature. The algorithm was then compared with a modified satellite-based Priestley-Taylor ET model (MS-PT). After examining the performance of the two models at 10 flux tower sites in different land cover types over East Asia and Australia, the daily estimates from the SWI-PT model were closer to observations than those of the MS-PT model in each land cover type. The average correlation coefficient of the SWI-PT model was 0.81, compared with 0.66 in the original MS-PT model. The average value of the root mean square error decreased from $36.46W/m^2$ to $23.37W/m^2$ in the SWI-PT model, which used different variables of soil moisture and vegetation indices to capture soil evaporation and vegetative transpiration, respectively. By using the EVI and SWI, uncertainties involved in optimizing vegetation and water constraints were reduced. The estimated ET from the MS-PT model was most sensitive (to the normalized difference vegetation index (NDVI) in forests) to net radiation ($R_n$) in grassland and cropland. The estimated ET from the SWI-PT model was most sensitive to $R_n$, followed by SWI, air temperature ($T_a$), and the EVI in each land cover type. Overall, the results showed that the MS-PT model estimates of ET in forest and cropland were weak. By replacing the fraction of soil moisture ($f_{sm}$) with the SWI and the NDVI with the EVI, the newly developed SWI-PT model captured soil evaporation and vegetation transpiration more accurately than the MS-PT model.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.123-132
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• 2019

This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.