Record Details
Multilinear Regression Equations for Predicting Lateral Spread Displacement from Soil Type and CPT Data
ScholarsArchive at Oregon State University
| Field | Value |
|---|---|
| Title | Multilinear Regression Equations for Predicting Lateral Spread Displacement from Soil Type and CPT Data |
| Names |
Gillins, Daniel T.
(creator) Bartlett, Steven F. (creator) |
| Date Issued | 2014-04 (iso8601) |
| Note | This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the American Society of Civil Engineers and can be found at: http://cedb.asce.org. |
| Abstract | In the 1990s, Bartlett and Youd introduced empirical equations for predicting horizontal displacement from liquefaction-induced lateral spreading; these equations have become popular in engineering practice. The equations were developed by multilinear regression (MLR) of lateral spreading case history data compiled by these researchers. In 2002, these equations were revised and updated to include additional case history data. The regressions indicated that the amount of horizontal displacement is statistically related to the topography, earthquake magnitude, and distance from the seismic energy source; and, the thickness, fines content, and mean grain size of the saturated, granular sediments with corrected Standard Penetration Test blow count values less than 15. This paper proposes to modify the MLR empirical equations by replacing the fines content and mean grain size factors with soil description factors. Such modification allows investigators performing preliminary evaluations to make lateral spread displacement estimates using existing geotechnical data with sparse laboratory measurements. The paper also proposes a methodology to estimate the required geotechnical inputs in the proposed modified MLR equations using cone penetration test data. |
| Genre | Article |
| Topic | Soil liquefaction |
| Identifier | Gillins, D. T., & Bartlett, S. F. (2014). Multilinear Regression Equations for Predicting Lateral Spread Displacement from Soil Type and Cone Penetration Test Data. Journal of Geotechnical and Geoenvironmental Engineering, 140(4). doi:10.1061/(ASCE)GT.1943-5606.0001051 |
