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

Siddharth S. Parida; Kallol Sett; Puneet Singla

doi:10.1061/9780784481486.050

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

Siddharth S. Parida, Kallol Sett, Puneet Singla

Aerospace Engineering

Research output: Contribution to journal › Conference article › peer-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 language	English (US)
Pages (from-to)	489-498
Number of pages	10
Journal	Geotechnical Special Publication
Volume	2018-June
Issue number	GSP 293
DOIs	https://doi.org/10.1061/9780784481486.050
State	Published - 2018
Event	5th 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 2018 → Jun 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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10.1061/9780784481486.050

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@article{b1dab5186d39425abd60776d6864c609,

title = "Probabilistic Geotechnical Site Characterization from Geophysical Measurements Using Model-Data Fusion",

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.",

author = "Parida, {Siddharth S.} and Kallol Sett and Puneet Singla",

note = "Publisher Copyright: {\textcopyright} 2018 American Society of Civil Engineers.; 5th Geotechnical Earthquake Engineering and Soil Dynamics Conference: Slope Stability and Landslides, Laboratory Testing, and In Situ Testing, GEESDV 2018 ; Conference date: 10-06-2018 Through 13-06-2018",

year = "2018",

doi = "10.1061/9780784481486.050",

language = "English (US)",

volume = "2018-June",

pages = "489--498",

journal = "Geotechnical Special Publication",

issn = "0895-0563",

publisher = "American Society of Civil Engineers (ASCE)",

number = "GSP 293",

}

TY - JOUR

T1 - Probabilistic Geotechnical Site Characterization from Geophysical Measurements Using Model-Data Fusion

AU - Parida, Siddharth S.

AU - Sett, Kallol

AU - Singla, Puneet

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

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U2 - 10.1061/9780784481486.050

DO - 10.1061/9780784481486.050

M3 - Conference article

AN - SCOPUS:85048853288

SN - 0895-0563

VL - 2018-June

SP - 489

EP - 498

JO - Geotechnical Special Publication

JF - Geotechnical Special Publication

IS - GSP 293

T2 - 5th Geotechnical Earthquake Engineering and Soil Dynamics Conference: Slope Stability and Landslides, Laboratory Testing, and In Situ Testing, GEESDV 2018

Y2 - 10 June 2018 through 13 June 2018

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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