• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.349-359
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• 2016

In order to analytically evaluate buffeting responses, the analysis of wind characteristics such as turbulence intensity, turbulence length, gust, roughness coefficient, etc must be a priority. Static aerodynamic force coefficients, flutter coefficients, structural damping ratios, aerodynamic damping ratios and natural frequencies affect the analytical responses. The bridge interested in this paper has being been used for 32 years. As the time passes, current terrain conditions around the bridge are different markedly from the conditions it was built 32 years ago. Also, wind environments were considerably varied by the climate change. For this reason, it is necessary to evaluate the turbulence intensity, length, spectrum and roughness coefficient of the bridge site from full-scale measurements using the structural health monitoring system. The evaluation results indicate that wind characteristics of bridge site is analogous to that of open terrain although the bridge is located on the coastal area. To calculate buffeting responses, the analysis variables such as damping ratios, static aerodynamic force coefficients and natural frequency were evaluated from measured data. The analysis was performed with regard to 4 cases. The evaluated variables from measured data are applied to the first and second analysis cases. And the other analysis cases were performed based on Design Guidelines for Steel Cable Supported Bridges. The calculated responses of each analysis cases are compared with the buffeting response measured at less than 25m/s wind speed. It is verified that the responses by the numerical analysis applying the estimated variables based on full-scale measurements are well agreed with the measured actual buffeting responses under wind speed 25m/s. Also, the extreme wind speed corresponding to a recurrence interval 200 years is derived from Gumbel distribution. The derived wind speed for return period of 200 years is 45m/s. Therefore the buffeting responses at wind speed 45m/s is determined by the analysis applying the estimated variables.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.30-40
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• 2022

Wildfires, which occur sporadically and irregularly worldwide, are distinct natural disturbances in combustible vegetation areas, important parts of the global carbon cycle, and natural disasters that cause severe public emergencies. While many previous studies have investigated the variability and changes in wildfires globally based on fire emissions, burned areas, and fire weather indices, studies on East Asia are still limited. Here, we explore the characteristics of variability and changes in wildfire danger over East Asia by analyzing the fire weather index for the 40 years-1981-2020. The first empirical orthogonal function (EOF) mode of fire weather index variability represents an increasing trend in wildfire danger over most parts of East Asia over the last 40 years, accounting for 29% of the total variance. The major contributor is an increase in the surface temperature in East Asia associated with global warming and multidecadal ocean variations. The effect of temperature was slightly offset by the increase in soil moisture. The second EOF mode exhibits considerable interannual variability associated with the El Nino-Southern Oscillation, accounting for 17% of the total variance. The increase (decrease) in precipitation in East Asia during El Nino (La Nina) increases (decreases) soil moisture, which in turn reduces (increases) wildfire danger. This dominant soil moisture effect was slightly offset by the temperature increase (decrease) during El Nino (La Nina). Improving the understanding of variability and changes in wildfire danger will have important implications for reducing social, economic, and ecological losses associated with wildfire occurrences.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.111-121
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• 2018

Many problems in rotating machinery such as aircraft engines, wind turbines and motors are caused by bearing defects. The abnormalities of the bearing can be detected by analyzing signal data such as vibration or noise, proper pre-processing through a few signal processing techniques is required to analyze their frequencies. In this paper, we introduce the condition monitoring method for diagnosing the failure of the rotating machines by analyzing the vibration signal of the bearing. From the collected signal data, the normal states are trained, and then normal or abnormal state data are classified based on the trained normal state. For preprocessing, a Hamming window is applied to eliminate leakage generated in this process, and the cepstrum analysis is performed to obtain the original signal of the signal data, called the formant. From the vibration data of the IMS bearing dataset, we have extracted 6 statistic indicators using the cepstral coefficients and showed that the application of the Mahalanobis distance classifier can monitor the bearing status and detect the failure in advance.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.111-120
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• 1999

The relationship between EI Nino-Southern Oscillation(ENSO) and drought in Korea is investigated using the cross correlation analysis. In this paper, Palmer Drought Severity Index(PDSI) is used as an index of drought and nine ENSO indicators are used. To obtain PDSI for Korea, the PDSI equation is derived using monthly precipitation and temperature in Korea. In addition, ENSO composite percentile analyses for PDSI, precipitation and streamflow in Korea are performed to verify the results of the cross correlation. Results of the cross correlation show that the link between drought in Korea and ENSO is statistically significant with 6% of the variance in PDSI for Korea explained by ENSO. The PDSI is negatively correlated with the equatorial Pacific Sea Surface Temperature and the Sea Level Pressure(SLP) at Darwin leading by about 16 months. However, the relationship of the PDSI with the Southern Oscillation Index and the SLP at Tahiti is positive correlation. The ENSO composite percentile analyses show that drought, precipitation and streamflow in Korea are associated with ENSO during 6 months from December of the ENSO ending year

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.5
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• pp.377-388
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• 2016

This study is aimed to evaluate the embedment effect of foundation as compared to the surface foundation on the response of a base-isolated nuclear power plant structure. For this purpose, the boundary reaction method (BRM), which is a two-step frequency domain and time domain technique, is used for the nonlinear SSI analysis considering nonlinear behavior of base isolators. The numerical model of the BRM is verified by comparing the numerical results obtained by the BRM and the conventional frequency-domain SSI analysis for an equivalent linear SSI system. Finally, the displacement response of the base isolation and the horizontal response of the structure obtained by the nonlinear SSI analysis using the moat foundation model are compared with those using the surface foundation model. The comparison showed that the displacement response of the base isolation can be reduced by considering the embedment effect of foundation.

• Journal of the Korean Geophysical Society
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• v.2 no.1
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• pp.57-64
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• 1999

To effectively identify near-surface faults with vertical slips from seismic refraction data, the GRM interpretation technique is tested and investigated in terms of various parameters through computer modeling. A characteristic change in shape of the velocity-analysis function near faults is noticed, and a new strategy of `Slope Variation Indicator (SVI)' is developed and tested in this study. The SVI is defined as a first horizontal derivative of the difference of velocity analysis functions for a large XY value and a small one, respectively. As the dip of refractor decreases and as the difference in XY value increases, the peak value of SVI increases and its duration decreases. Consequently, the SVI indicates accurately the location of buried fault in the test models. The SVI is believed to be an efficient tool in seismic refraction method to investigate location and distribution of shallowly buried faults.

• Journal of the Korean Geotechnical Society
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• v.36 no.11
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• pp.83-95
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• 2020

In order to evaluate the stability of the geo-structure of railway bridge, the response dominant frequency was analyzed based on a series of impact vibration load test results. The specifications of the experiment piers were obtained by referring to the completion design data, and when data was missing, a field study was conducted. The impact vibrations test according to the scouring progress was carried out at one pier scheduled to be abandoned, and it was confirmed that the response dominant frequency can be utilized as an evaluation index for scour. In addition, the response dominant frequency was measured through an impact load test at 46 piers in 5 bridges in operation, and the scour safety of the bridge was evaluated by comparing it with the japanese proposal formula.

• The Journal of the Acoustical Society of Korea
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• v.8 no.1
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• pp.5-12
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• 1989

This paper is concerned with the characteristics on the statistical parameters of vibration signal from bearing with changing its operating conditions as well as the spreading of faults. The rms, Kurtosis, crest factor, probability of exceedance and probability density function have been chose as the statistical parameters. To characterize of each, vibration signals have been recorded from four ball tester at different loads, operation speeds and time. The values of the statistical parameters for each frequency band have been calculated after A/D conversion and digital filtering of the recorded signals. It has been found that unlike rms values the statistical parameters such as Kurtosis etc. are almost unchanging with the change of the operating conditions such as load and speed. This suggests that the statistical parameters may be used for determining the development of faults independent of the operating conditions. In fact, the statistical parameters deviate considerably from their respective normal values when the faults developed under load conditions in the samples, conforming the suggestion.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.3
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• pp.101-107
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• 2014

Damage location and extent of structure could be detected by the inverse analysis on dynamic response properties such as frequencies and mode shapes. The dynamic response of building structures has many noise and affected by nonstructural members and, above all, the behavior of building structure is more complex than civil structure and this makes the damage detection difficult. In recent researches the damage is detected by the indirect index such as sensitivity or assumed values. However, for the more reasonable damage detection, it needs to use the damage index directly induced from dynamic equation. The purpose of this study is to provide the damage detection method on shear building structures by the damage index directly induced from dynamic equation. The provided damage index could be estimated from measured mode shape of undamaged structure and frequency difference between undamaged and damaged structure. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. The damage index at damaged story represents (-) sign and 15 times than other undamaged sories.

• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.45-53
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• 2020

There is an increasing tendency to try to make predictive analysis using measurement data based on machine learning techniques in the railway industries. In this paper, it was predicted that Track quality index (TQI) using vehicle acceleration data based on the machine learning method. The XGB (XGBoost) was the most accurate with 85% in the all data sets. Unlike the SVM model with a single algorithm, the RF and XGB model with a ensemble system were considered to be good at the prediction performance. In the case of the Surface TQI, it is shown that the acceleration of the z axis is highly related to the vertical direction and is in good agreement with the previous studies. Therefore, it is appropriate to apply the model with the ensemble algorithm to predict the track quality index using the vehicle vibration acceleration data because the accuracy may vary depending on the applied model in the machine learning methods.