Geotechnical parameter estimation in tunnelling using relative convergence measurement

Kook Hwan Cho, Min Kwang Choi, Seok Woo Nam, In Mo Lee

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Accurate estimation of geotechnical parameters is an important and difficult task in tunnel design and construction. Optimum evaluation of the geotechnical parameters have been carried out by the back-analysis method based on estimated absolute convergence data. In this study, a back-analysis technique using measured relative convergence in tunnelling is proposed. The extended Bayesian method (EBM), which combines the prior information with the field measurement data, is adopted and combined with the 3-dimensional finite element analysis to predict ground motion. By directly using the relative convergence as observation data in the EBM, we can exclude errors that arise in the estimation of absolute displacement from measured convergence, and can evaluate the geotechnical parameters with sufficient reliability. The proposed back-analysis technique is applied and validated by using the measured data from two tunnel sites in Korea.

Original languageEnglish
Pages (from-to)137-155
Number of pages19
JournalInternational Journal for Numerical and Analytical Methods in Geomechanics
Volume30
Issue number2
DOIs
Publication statusPublished - 2006 Feb

Keywords

  • 3-dimensional analysis
  • Back-analysis
  • Extended Bayesian method
  • Relative convergence

ASJC Scopus subject areas

  • Computational Mechanics
  • Materials Science(all)
  • Geotechnical Engineering and Engineering Geology
  • Mechanics of Materials

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