Applications of Statistical Design of Experiments to Study the Factor of Safety of Unreinforced Slopes

Yuderka Trinidad Gonzalez, Vernon Schaefer, Derrick K. Rollins

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

A technique of statistical design of experiments (DoE) is combined with finite element (FE) analysis to evaluate the strength reduction factor (SRF) sensitivity to slope geometry and soil properties such as slope height (H), the slope angle of inclination (β), friction angle (φ'), cohesion (c' or c), elastic modulus (E), Poisson's ratio (v), pore water coefficient (ru), and unit weight (γ). The analysis is conducted by performing two-dimensional FE analysis in a central composite design fashion classifying the soil into three groups: purely cohesive (c, undrained analysis), purely frictional (φ'), and mixed soils (c' and φ'). The findings indicate that for the mixed soils, six main coefficients (c', β, ru, φ', γ, H) and their interactions have significant effects on the response. For the purely cohesive soils, c, H, β, and their interactions have larger effects on SRF. For purely frictional soils, the larger positive effect comes from φ', and the large negative effects come from β, ru, and their interactions. Based on the results, recommendations for achieving optimum stabilization techniques for each soil group are given.

Original languageEnglish
Title of host publicationProceedings of the technical sessions of the international foundations congress & equipment expo ASCE, Dallas, Texas, May 10-14, 2021.
Pages278-286
Number of pages9
Volume2021-May
EditionGSP 325
DOIs
Publication statusPublished - 6 May 2021

Publication series

NameGeotechnical Special Publication
PublisherAmerican Society of Civil Engineers
ISSN (Print)0895-0563

Bibliographical note

The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of NSF, ERDC or the U.S. Government. Distribution Statement A: Approved for public release: distribution unlimited.

Acknowledgements

This material is based upon work supported by the U. S. Army Research Laboratory and the U. S. Army Research Office under contract numbers W911NF-16-1-0336, W911NF-17-1-0262, W911NF-18-1-0068 and W911NF-20-1-0238. The discussions and conclusions presented in this work reflect the opinions of the authors only.

The support of Dr. Joy Pauschke, program director at the National Science Foundation, is greatly appreciated.

The authors would like to thank the principal investigators of the CMMI grant, Dr. Brina Montoya of North Carolina State University and Dr. T. Matthew Evans of Oregon State University and their students for their guidance and assistance in the testing described herein. The authors would also like to thank the staff at O.H. Hinsdale Wave Research Laboratory, Drs. Dan Cox, Meagan Wengrove, and Tim Maddux, for their technical assistance.

ASJC Scopus subject areas

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

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