• Title/Summary/Keyword: 시추공 편차

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Determining the Orientation of Accelerograph Stations in South Korea using Ambient Noise Data (배경잡음 자료를 이용한 국내 가속도 관측망의 방위각 보정값 측정)

  • Lee, Sang-Jun
    • Journal of the Korean earth science society
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    • v.42 no.2
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    • pp.195-200
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    • 2021
  • Orientation corrections for the total of 268 accelerograph stations of the Korea Meteorological Administration (KMA) were estimated using ambient noise cross-correlation. As this method uses ambient noise data instead of teleseismic waveforms from earthquakes under certain conditions, reliable orientation corrections can be obtained using only two-month long continuous seismic data from dense seismic networks in the Korean peninsula.Three-component continuous data recorded at the 268 accelerograph stations from January to February 2020 were used to estimate orientation corrections. The results are comparable to the previous results obtained from teleseismic waveforms; the overall standard deviations of the orientation corrections are less than 5°. Therefore, orientation corrections for the accelerograph station network can be tracked periodically by the ambient-noise method and the result can be used in various studies using the horizontal-component of acceleration data.

Crossplot Interpretation of Electrical Resistivity and Seismic Velocity Values for Mapping Weak Zones in Levees (제방의 취약구간 파악을 위한 전기비저항과 탄성파속도의 교차출력 해석)

  • Cho, Kyoung-Seo;Kim, Jeong-In;Kim, Jong-Woo;Kim, Ji-Soo
    • The Journal of Engineering Geology
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    • v.31 no.4
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    • pp.507-522
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    • 2021
  • Specific survey objectives often cannot be met using only one geophysical method, as each method's results are influenced by the specific physical properties of subsurface materials. In particular, areas susceptible to geological hazards require investigation using more than one method in order to reduce risks to life and property. Instead of analyzing the results from each method separately, this work develops a four-quadrant criterion for classifying areas of levees as safe or weak. The assessment is based on statistically determined thresholds of seismic velocity (P-wave velocity from seismic refraction and S-wave velocity from multichannel analysis of surface waves) and electrical resistivity. Thresholds are determined by subtracting the standard deviation from the mean during performance testing of this correlation technique applied to model data of four horizontal and inclined fracture zones. Compared with results from the crossplot of resistivity and P-wave velocity, crossplot analysis using resistivity and S-wave velocity data provides more reliable information on the soil type, ground stiffness, and lithological characteristics of the levee system. A loose and sandy zone (represented by low S-wave velocity and high resistivity) falling within the second quadrant is interpreted to be a weak zone. This interpretation is well supported by the N values from standard penetrating test for the central core.

Deep Learning based Estimation of Depth to Bearing Layer from In-situ Data (딥러닝 기반 국내 지반의 지지층 깊이 예측)

  • Jang, Young-Eun;Jung, Jaeho;Han, Jin-Tae;Yu, Yonggyun
    • Journal of the Korean Geotechnical Society
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    • v.38 no.3
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    • pp.35-42
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    • 2022
  • The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

Traffic Forecasting Model Selection of Artificial Neural Network Using Akaike's Information Criterion (AIC(AKaike's Information Criterion)을 이용한 교통량 예측 모형)

  • Kang, Weon-Eui;Baik, Nam-Cheol;Yoon, Hye-Kyung
    • Journal of Korean Society of Transportation
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    • v.22 no.7 s.78
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    • pp.155-159
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    • 2004
  • Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

Performance Analysis of a Deep Vertical Closed-Loop Heat Exchanger through Thermal Response Test and Thermal Resistance Analysis (열응답 실험 및 열저항 해석을 통한 장심도 수직밀폐형 지중열교환기의 성능 분석)

  • Shim, Byoung Ohan;Park, Chan-Hee;Cho, Heuy-Nam;Lee, Byeong-Dae;Nam, Yujin
    • Economic and Environmental Geology
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    • v.49 no.6
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    • pp.459-467
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    • 2016
  • Due to the limited areal space for installation, borehole heat exchangers (BHEs) at depths deeper than 300 m are considered for geothermal heating and cooling in the urban area. The deep vertical closed-loop BHEs are unconventional due to the depth and the range of the typical installation depth is between 100 and 200 m in Korea. The BHE in the study consists of 50A (outer diameter 50 mm, SDR 11) PE U-tube pipe in a 150 mm diameter borehole with the depth of 300 m. In order to compensate the buoyancy caused by the low density of PE pipe ($0.94{\sim}0.96g/cm^3$) in the borehole filled with ground water, 10 weight band sets (4.6 kg/set) were attached to the bottom of U-tube. A thermal response test (TRT) and fundamental basic surveys on the thermophysical characteristics of the ground were conducted. Ground temperature measures around $15^{\circ}C$ from the surface to 100 m, and the geothermal gradient represents $1.9^{\circ}C/100m$ below 100 m. The TRT was conducted for 48 hours with 17.5 kW heat injection, 28.65 l/min at a circulation fluid flow rate indicates an average temperature difference $8.9^{\circ}C$ between inlet and outlet circulation fluid. The estimated thermophysical parameters are 3.0 W/mk of ground thermal conductivity and 0.104 mk/W of borehole thermal resistance. In the stepwise evaluation of TRT, the ground thermal conductivity was calculated at the standard deviation of 0.16 after the initial 13 hours. The sensitivity analysis on the borehole thermal resistance was also conducted with respect to the PE pipe diameter and the thermal conductivity of backfill material. The borehole thermal resistivity slightly decreased with the increase of the two parameters.

Numerical Analysis of Groundwater Flow through Fractured Rock Mass by Tunneling in a Mountainous Area (산악 지역 내 터널 굴착 시 단열 암반 내 지하수 유동 분석)

  • Kim, Hyoung-Soo;Lee, Ju-Hyun;Ahn, Ju-Hee;Ahn, Gyu-Cheon;Yoon, Woon-Sang
    • Tunnel and Underground Space
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    • v.16 no.4 s.63
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    • pp.281-287
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    • 2006
  • Intake of groundwater by tunneling in a mountainous area mostly results from groundwater flow through fractured parts of total rock mass. For reasonable analysis of this phenomenon the representative joint groups 1, 2, and 3 have been selected by previous investigations, geological/geophysical field tests and boring works. Three dimensional fractures were generated by the FracMan and MAFIC which is a three dimensional finite element model has been used to analyse a groundwater flow through fractured media. Monte Carlo simulation was applied to reduce the uncertainty of this study. The numerical results showed that the average and deviation of amounts of groundwater intaked into tunnel per unit length were $5.40{\times}10^{-1}$ and $3.04{\times}10^{-1}m^3/min/km$. It is concluded that tunnel would be stable on impact of groundwater environment by tunneling because of the lower value than $2.00{\sim}3.00m^3/min/km$ as previous and present standard on the application of tunnel construction.