터널과지하공간 (Tunnel and Underground Space)

  • 제34권4호
  • /
  • Pages.301-311
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  • 2024
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  • 1225-1275(pISSN)
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  • 2287-1748(eISSN)
한국암반공학회 (Korean Society for Rock Mechanics and Rock Engineering)
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시추공 관측소 계측 자료에 기반한 암반의 지반운동 모델 개발

Development of Ground Motion Models within Rock Based on Ground Motion Data Measured at Borehole Seismic Stations

  • 강신항 (한남대학교 )
  • Sinhang Kang (Hannam University)
  • 투고 : 2024.07.15
  • 심사 : 2024.08.06
  • 발행 : 2024.08.31
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초록

우리나라는 2016년 경주 지진과 2017년 포항 지진 이후 지진 재해 방지 대책의 필요성이 증가하고 있으며, 지진 피해 정량화를 위해 신뢰성 있는 지진 재해도 해석 기법과 지반운동 모델이 요구된다. 최근 심층 지하 시설에 대한 수요가 증가하고 있다. 이에 따라 지하 암반층에서의 지진 재해 정량화 기법의 정확성 확보가 필요하다. 본 연구에서는 국내 시추공 관측소에서 계측된 지반운동 자료를 활용하여 지하 암반층에서의 지반운동을 예측할 수 있는 모델을 제안하였다. 스펙트럴 가속도의 0.01~10초 주기 중 17개를 대상으로 경험적 기법 중 회귀분석을 적용하여 지반운동 모델을 개발하였다. 지반운동 모델의 예측 성능을 평가 및 개선하기 위해 잔차 분석을 수행하고, 보정 인자를 모델식에 추가하였다. 제안된 모델을 적용하였을 때 잔차의 구간 평균이 0에 근접하였고, 기존 국외 모델들과 유사한 종합 잔차의 표준편차를 확인함으로써 제안된 모델의 신뢰성을 확인하였다.

In South Korea, following the 2016 Gyeongju and 2017 Pohang earthquakes, the need for earthquake disaster prevention has been increasing. Reliable techniques for probabilistic seismic hazard analysis and ground motion models are required for quantifying earthquake damage. Recently, there has been growing demand for deep underground facilities, necessitating accurate quantification techniques for earthquake damage in deep underground. In this study, ground motion models within rock were proposed using ground motion data measured at borehole seismic stations. A regression analysis, a type of empirical technique, was applied to 17 periods selected in a range from 0.01 to 10 s of spectral accelerations to develop the ground motion models. Residual analysis was performed to evaluate and improve the prediction performance of the ground motion model, with correction factors added to the model equation. When applying the proposed model, the group means of residuals approached zero, and the standard deviation of total residuals, similar to existing models proposed in other countries, confirmed the reliability of the proposed model.

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과제정보

이 논문은 2022학년도 한남대학교 학술연구비 지원에 의하여 연구되었습니다.

참고문헌

  1. Abrahamson, N.A. and Youngs, R.R., 1992, A stable algorithm for regression analyses using the random effects model, Bulletin of the Seismological Society of America, 82(1), 505-510.
  2. Ahn, B.S., Kang, T.S., and Jung, J.O., 2024, Station metadata integration of regional seismic networks in the southern Korean Peninsula, Journal of the Geological Society of Korea, 60(1), 111-119.
  3. Boore, D.M. and Atkinson, G.M., 2008, Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 s and 10.0 s, Earthquake Spectra, 24, 99-138.
  4. Boore, D.M., 2003, Prediction of Ground Motion Using the Stochastic Method, Pure and Applied Geophysics, 160, 635-676.
  5. Bozorgnia, Y., Abrahamson, N.A., Atik, L.A., Ancheta, T.D., Atkinson, G.M., Baker, J.W., Baltay, A., Boore, D.M., Campbell, K.W., Chiou, B.S.J., Darragh, R., Day, S., Donahue, J., Graves, R.W., Gregor, N., Hanks, T., Idriss, I.M., Kamai, R., Kishida, T., and Youngs, R., 2014, NGA-West2 research project, Earthquake Spectra, 30(3), 973-987.
  6. Emolo, A., Sharma, N., Festa, G., Zollo, A., Convertito, V., Park, J.H., Chi, H.C., and Lim, I.S., 2015, Ground-motion prediction equations for South Korea Peninsula, Bulletin of the Seismological Society of America, 105(5), 2625-2640.
  7. Graizer, V. and Kalkan, E., 2009, Prediction of Spectral Acceleration Response Ordinates Based on PGA Attenuation, Earthquake Spectra, 25(1), 39-69.
  8. Jee, H.W. and Han, S.W., 2020, Development of the ground motion simulation model for the Korean Peninsula, Journal of the Architectural Institute of Korea, 36(10), 159-166.
  9. Jee, H.W. and Han, S.W., 2023, Korean Region Ground Motion Prediction Equation Considering Site Effects, Journal of the Architectural Institute of Korea, 39(2), 265-272.
  10. Kang, S., Kim, B., Bae, S., Lee, H., and Kim, M., 2019a, Earthquake-Induced Ground Deformations in the Low-Seismicity Region: A Case of the 2017 M5.4 Pohang, South Korea, Earthquake, Earthquake Spectra, 35(3), 1235-1260.
  11. Kang, S., Kim, B., Cho, H., Lee, J., Kim, K., Bae, S., and Sun, C.G., 2019b, Ground-Motion Amplifications in Small-Size Hills: Case Study of Gokgang-ri, South Korea, during the 2017 ML 5.4, Bulletin of the Seismological Society of America, 109(6), 2626-2643.
  12. Kang, S., Mun, E., Phuong, D.T.T., and Kim, B., 2024, Machine learning‑based ground motion models for predicting PSAs of borehole motions in Japan, Journal of Seismology, 28, 491-518.
  13. National Earthquake Comprehensive Information System (NECIS), https://necis.kma.go.kr/
  14. Rodriguez-Marek, A., Montalva, G.A., Cotton, F., and Bonilla, F., 2011, Analysis of single-station standard deviation using the KiK-net data, Bulletin of the Seismological Society of America, 101(3), 1242-1258.
  15. Sandikkaya, M.A., 2019, On linear site amplification behavior of crustal and subduction interface earthquakes in Japan: (1) regional effects, (2) best proxy selection, Bulletin of Earthquake Engineering, 17(1), 119-139.
  16. Shin, D.H., Hong, S.J., and Kim, H.J., 2016, Prediction of spectral acceleration response based on the statistical analyses of earthquake records in Korea, Journal of Earthquake Engineering Society of Korea, 20(1), 45-54.