한국지반공학회논문집 (Journal of the Korean Geotechnical Society)

  • 제38권8호
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  • Pages.53-66
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  • 2022
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  • 1229-2427(pISSN)
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  • 2288-646X(eISSN)
한국지반공학회 (Korean Geotechnical Society)
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표준관입시험 및 시추공 정보를 이용한 국내 전단파속도 예측

VS Prediction Model Using SPT-N Values and Soil Layers in South Korea

  • 허기석 (한양대학교 건설환경시스템공학과) ;
  • 곽동엽 (한양대학교 ERICA 건설환경공학과)
  • Heo, Gi-Seok (Dept. of Civil, Environmental and System Engrg., Hanyang Univ.) ;
  • Kwak, Dong-Youp (Dept. of Civil and Environmental Engrg., Hanyang Univ., ERICA)
  • 투고 : 2022.06.23
  • 심사 : 2022.07.22
  • 발행 : 2022.08.31
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초록

국토지반정보 통합DB센터(GeoInfo)는 전국 건설현장에서 생산되는 많은 수의 지반조사결과 자료를 배포하고 있다. GeoInfo에는 많은 수의 표준관입시험(Standard Penetration Test, SPT) 자료가 존재하지만, 전단파속도(VS) 데이터는 아직 부족한 실정이다. 따라서 풍부한 SPT 데이터로부터 VS를 예측하기위해 본 연구에서는 GeoInfo에서 배포하는 자료를 이용하여 새로운 N-VS 모델을 제안하였다. 본 연구는 지층 또는 토층에 구분없이 하나의 모델을 제안한다. 단, 지층에 따라 VS의 최대값을 설정하여 N치의 과대 예측에 의한 VS의 과대 예측을 방지하였다. 모델 개발에 사용하지 않은 검증용 데이터를 활용하여 선행연구에서 제시한 N-VS모델과 본 연구에서 개발한 모델을 비교해 본 결과, 본 연구에서 제안한 모델이 가장 우수한 성능을 보여주었다. 제안한 N-VS 모델은 GeoInfo의 많은 데이터로부터 유추된 경험식이기에 GeoInfo의 SPT 데이터를 VS로 변환하는데 가장 적합할 것으로 판단된다.

The national ground survey database (GeoInfo) distributes numerous ground survey data nationwide. Many standard penetration test results exist in this database; however, the number of shear wave velocity (VS) data is small. Hence, to use abundant standard penetration test-N values to predict VS, this study proposed a new empirical N-VS relationship model using GeoInfo data. The proposed N-VS model is a single equation regardless of geological layer types; the layer type only specifies the upper limit of VS. To validate the proposed model, residual analysis was performed using a test dataset that was not used for the model development. Therefore, this study's proposed model performed better than N-VS models from previous studies. Since the N-VS model in this study was developed using sufficient data from GeoInfo, we expect that it is the most applicable to GeoInfo dataset for VS prediction.

키워드

과제정보

본 연구는 국토교통부 광역단위 노후건축물 디지털 안전워치 기술개발사업의 연구비지원(과제번호 RS-2022-00143584) 및 한국기상산업기술원 「지진·지진해일·화산감시 및 예측기술 개발」사업의 연구비지원(과제번호 KMI2021-01911)에 의해 수행되었습니다. 이에 깊은 감사를 드립니다. 또한, 이 논문은 2022 지반공학회 봄학술발표회 논문을 수정·보완하여 작성되었습니다.

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