• Journal of the Korean Geophysical Society
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• v.8 no.4
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• pp.201-205
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• 2005

Turbulent fluxes of heat, water vapor, and CO2 have been measured since August, 2003 at Dasan Station (78o 55’ N, 11o50’E) in the Arctic. These data can allow us to better understand the interactions between the Polar ecosystems and the atmosphere together with those at King Sejong Station in the Antarctic. Due to the buildings and measurement platforms around the flux tower, it is required to evaluate how they influence measured flux data. By using one-year turbulence statistics data and footprint model, flux footprint climatology was analyzed together with data availability. The upwind distance of source area ranged from 150 to 300 m, where the buildings and measurement platforms existed. However, flow distortion due to them may be not a major factor to reduce the data availability significantly. Based on, the dominant wind direction of SW and footprint climatology, the location of flux tower is considered suitable for flux measurement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.47-56
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• 2018

Providing high-quality meteorological observation data at sites that represent actual farming environments is essential for useful agrometeorological services. The Automated Agricultural Observing System (AAOS) of the Korean Meteorological Administration, however, has been deployed on lawns rather than actual farm land. In this study, we show the inaccuracies that arise in AAOS data by analyzing temporal and vertical variation and by comparing them with data recorded by the National Center for AgroMeteorology (NCAM) tower that is located at an actual farming site near the AAOS tower. The analyzed data were gathered in August and October (before and after harvest time, respectively). Observed air temperature and water vapor pressure were lower at AAOS than at NCAM tower before and after harvest time. Observed reflected shortwave radiation tended to be higher at AAOS than at NCAM tower. Soil variables showed bigger differences than meteorological observation variables. In August, observed soil temperature was lower at NCAM tower than at AAOS with smaller diurnal changes due to irrigation. The soil moisture observed at NCAM tower continuously maintained its saturation state, while the one at AAOS showed a decreasing trend, following an increase after rainfall. The trend changed in October. Observed soil temperature at NCAM showed similar daily means with higher diurnal changes than at AAOS. The soil moisture observed at NCAM was continuously higher, but both AAOS and NCAM showed similar trends. The above results indicate that the data gathered at the AAOS are inaccurate, and that ground surface cover and farming activities evoke considerable differences within the respective meteorological and soil environments. We propose to shift the equipment from lawn areas to actual farming sites such as rice paddies, farms and orchards, so that the gathered data are representative of the actual agrometeorological observations.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.109-120
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• 2015

Spatial heterogeneous characteristics of solar radiation energy from Climate Change gives rise to energy imbalance in the general ecological system including water resources. This study is to estimate the $CO_2$ flux of South Korea using Terra MODIS image and to assess the reliability of MODIS data from the ground measured $CO_2$ flux by eddy covariance flux tower data at 3 locations (two at mixed forest area and one at rice paddy area). The MODIS Gross Primary Productivity (GPP) product (MOD17A2), 8-day composite at 1-km spatial resolution was adopted for the spatial $CO_2$ flux generation. The MOD17A2 data by noise like cloud and snow in a day were tried to fill by Inverse Distance Weighted (IDW) method from valid pixels and the damping effect of MOD17A2 data were corrected by Quality Control (QC) flag. The MODIS $CO_2$ flux was estimated as the sum of GPP and Re (ecosystem respiration) by Lloyd and Taylor method (1994). The determination coefficient ($R^2$) between MODIS $CO_2$ and flux tower $CO_2$ for 3 years (2011~2013) showed 0.55 and 0.60 in 2 mixed forests and 0.56 in rice paddy respectively. The $CO_2$ flux generally fluctuated showing minus values during summer rainy season (from July to August) and maintaining plus values for other periods. The MODIS $CO_2$ flux can be a useful information for extensive area, for example, as a reliable indicator on ecological circulation system.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.443-458
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• 2012

The structural health monitoring (SHM) benchmark study on optimal sensor placement problem for the instrumented Canton Tower has been launched. It follows the success of the modal identification and model updating for the Canton Tower in the previous benchmark study, and focuses on the optimal placement of vibration sensors (accelerometers) in the interest of bettering the SHM system. In this paper, the sensor placement problem for the Canton Tower and the benchmark model for this study are first detailed. Then an information entropy based sensor placement method with the purpose of damage detection is proposed and applied to the benchmark problem. The procedure that will be implemented for structural damage detection using the data obtained from the optimal sensor placement strategy is introduced and the information on structural damage is specified. The information entropy based method is applied to measure the uncertainties throughout the damage detection process with the use of the obtained data. Accordingly, a multi-objective optimal problem in terms of sensor placement is formulated. The optimal solution is determined as the one that provides equally most informative data for all objectives, and thus the data obtained is most informative for structural damage detection. To validate the effectiveness of the optimally determined sensor placement, damage detection is performed on different damage scenarios of the benchmark model using the noise-free and noise-corrupted measured information, respectively. The results show that in comparison with the existing in-service sensor deployment on the structure, the optimally determined one is capable of further enhancing the capability of damage detection.

• Atmosphere
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• v.26 no.3
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• pp.483-492
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• 2016

We have examined the random error of eddy covariance (EC) measurements on the basis of two-tower approach during daytime. Two EC towers were placed on the grassland with different vegetation density near Gumi-weir. We calculated the random error using three different methods. The first method (M1) is two-tower method suggested by Hollinger and Richardson (2005) where random error is based on differences between simultaneous flux measurements from two towers in very similar environmental conditions. The second one (M2) is suggested by Kessomkiat et al. (2013), which is extended procedure to estimate random error of EC data for two towers in more heterogeneous environmental conditions. They removed systematic flux difference due to the energy balance deficit and evaporative fraction difference between two sites before determining the random error of fluxes using M1 method. Here, we introduce the third method (M3) where we additionally removed systematic flux difference due to available energy difference between two sites. Compared to M1 and M2 methods, application of M3 method results in more symmetric random error distribution. The magnitude of estimated random error is smallest when using M3 method because application of M3 method results in the least systematic flux difference between two sites among three methods. An empirical formula of random error is developed as a function of flux magnitude, wind speed and measurement height for use in single tower sites near Nakdong River. This study suggests that correcting available energy difference between two sites is also required for calculating the random error of EC data from two towers at heterogeneous site where vegetation density is low.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.61-70
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• 2019

The modified Kling-Gupta efficiency fusion method to merge actual evapotranspiration was proposed and compared with the simple Taylor skill's score method using Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16), and the flux tower on three different land cover types over the Korean peninsula and China. In the results of the weights estimated from two actual evapotranspiration merging techniques (i.e., STS and KGF), the weights of reanalysis data (i.e, GLDAS and GLEAM) in cropland and grassland showed similar performance, while the results of weights are different according to the merging techniques in forest. Both two merging techniques showed better results than original dataset in grassland and forest. However, there were no improvement in cropland compared to the other land cover types. The results of the KGF method slightly improved compared to those of the STS in grassland and forest.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1019-1039
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• 2015

Shanghai Tower is a composite structure building with a height of 632 m. In order to verify the structural properties and behaviors in construction and operation, a structural health monitoring project was conducted by Tongji University. The monitoring system includes sensor system, data acquisition system and a monitoring software system. Focusing on the health monitoring in construction, this paper introduced the monitoring parameters in construction, the data acquisition strategy and an integration structural health monitoring (SHM) software. The integration software - Structural Monitoring/ Analysis/ Evaluation System (SMAE) is designed based on integration and modular design idea, which includes on-line data acquisition, finite elements and dynamic property analysis functions. With the integration and modular design idea, this SHM system can realize the data exchange and results comparison from on-site monitoring and FEM effectively. The analysis of the monitoring data collected during the process of construction shows that the system works stably, realize data acquirement and analysis effectively, and also provides measured basis for understanding the structural state of the construction. Meanwhile, references are provided for the future automates construction monitoring and implementation of high-rise building structures.

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.185-193
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• 2018

In this study, low- and high-frequency structure behaviors were identified and a systematic analysis procedure was proposed using noisy GPS data from a 165-m-high tower in ${\dot{I}}stanbul$, Turkey. The raw GPS data contained long- and short-periodic position changes and noisy signals at different frequencies. To extract the significant results from this complex dataset, the general structure and components of the GPS signal were modeled and analyzed in the time and frequency domains. Uncontrolled jumps and deviations involving the signal in the time domain were pre-filtered. Then, the signal was converted to the frequency domain after applying low- and high-pass filters, and the frequency and periodic component values were calculated. The spectrum of the tower motion obtained from the filtered GPS data had dominant peaks at a low frequency of $1.15572{\times}10-4Hz$ and a high frequency of 0.16624 Hz, consistent with two equivalent GPS datasets. Then, the signal was reconstructed using inverse Fourier transform with the dominant low frequency values to obtain filtered and interpretable clean signals. With the proposed sequence, processing of noisy data collected from the GPS receivers mounted very close to the structure is effective in revealing the basic behaviors and features of buildings.

• International Journal of High-Rise Buildings
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• v.6 no.3
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• pp.207-216
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• 2017

Installing accelerometers in a building is an effective way to know how the building shakes when an earthquake happens. In this paper, we will introduce an example of an analysis that captures the acceleration reduction effect of the vibration damping device using data observed by the accelerometer at Roppongi Hills Mori Tower in Minato-ku, Tokyo, during the Great East Japan Earthquake on March 11, 2011. Moreover, as the latest effort, from the standpoint of a developer who builds and operates a number of high-rise buildings in Japan, where frequent earthquakes are experienced, a system for real-time processing of accelerometer data was developed to instantly diagnose the degree of damage to high-rise buildings, and the actual system of earthquake damage health monitoring is discussed. This system is currently in operation in twelve high-rise buildings including Roppongi Hills Mori Tower.