A novel framework integrating downhole array data and site response analysis to extract dynamic soil behavior

Chi Chin Tsai, Youssef M.A. Hashash

Research output: Contribution to journalArticle

Abstract

Seismic site response analysis is commonly used to predict ground response due to local soil effects. An increasing number of downhole arrays are deployed to measure motions at the ground surface and within the soil profile and to provide a check on the accuracy of site response analysis models. Site response analysis models, however, cannot be readily calibrated to match field measurements. A novel inverse analysis framework, self-learning simulations (SelfSim), to integrate site response analysis and field measurements is introduced. This framework uses downhole array measurements to extract the underlying soil behavior and develops a neural network-based constitutive model of the soil. The resulting soil model, used in a site response analysis, provides correct ground response. The extracted cyclic soil behavior can be further enhanced using multiple earthquake events. The performance of the algorithm is successfully demonstrated using synthetically generated downhole array recordings.

Original languageEnglish (US)
Pages (from-to)181-197
Number of pages17
JournalSoil Dynamics and Earthquake Engineering
Volume28
Issue number3
DOIs
StatePublished - Mar 1 2008

Keywords

  • Downhole array
  • Inverse analysis
  • Site response analysis
  • Soil behavior

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geotechnical Engineering and Engineering Geology
  • Soil Science

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