Probabilistic Geotechnical Site Characterization from Geophysical Measurements Using Model-Data Fusion

Siddharth S. Parida, Kallol Sett, Puneet Singla

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper exemplifies and validates a recently developed model-data fusion algorithm in spatial and statistical characterization of the elastic soil parameters at any geotechnical sites from geophysical measurements. Advanced geophysical test measurements available for the NEES@UCSB site in Garner Valley, CA, are analyzed to probabilistically estimate the Young's modulus and Poisson's ratio of soil at a 60 m×60 m parcel of the site up to a depth 40 m. The probabilistic estimates of the soil parameters are presented in terms of the mean and standard deviation profiles as well as correlation structures in the x-, y-, and z-direction.

Original languageEnglish (US)
Pages (from-to)489-498
Number of pages10
JournalGeotechnical Special Publication
Volume2018-June
Issue numberGSP 293
DOIs
StatePublished - 2018
Event5th Geotechnical Earthquake Engineering and Soil Dynamics Conference: Slope Stability and Landslides, Laboratory Testing, and In Situ Testing, GEESDV 2018 - Austin, United States
Duration: Jun 10 2018Jun 13 2018

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Architecture
  • Building and Construction
  • Geotechnical Engineering and Engineering Geology

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