TY - GEN
T1 - Applications of Statistical Design of Experiments to Study the Factor of Safety of Unreinforced Slopes
AU - Trinidad Gonzalez, Yuderka
AU - Schaefer, Vernon
AU - Rollins, Derrick K.
N1 - Funding Information:
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.
Funding Information:
Financial support for this work was provided by the National Science Foundation Grant No. CMMI-1563428. The support of Dr. Joy Pauschke, program director at the National Science Foundation, is greatly appreciated.
Funding Information:
The authors would also like to gratefully acknowledge the financial support from the National Science Foundation under Grant No. CMMI-1804822.
Funding Information:
The study on which this paper is based was supported by National Science Foundation through Grant #1900445 and NASA -MIRO Grant awarded to University of the District of Columbia. The results and opinions expressed in this paper do not necessarily reflect the views and policies of the National Science Foundation and National Aeronautics and Space Administration.
Funding Information:
This material is based upon work supported in part by the National Science Foundation (NSF) under Grant No. CMMI-1634748 and the U.S. Army Engineer Research and Development Center (ERDC) under contract W9I2HZ-17-C-0021. 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.
Funding Information:
The first author would like to show his gratitude to LPDP (Indonesia Endowment Fund for Education), which has provided financial support for his graduate study.
Funding Information:
The research described herein was supported by the Center for Bio-mediated and Bio-inspired Geotechnics (CBBG) under National Science Foundation (NSF) Cooperative Agreement No. EEC-1449501 and as a Payload Project under NSF Grant No. CMMI-1933350. The authors are grateful for the NSF support. Any opinions, findings and conclusions, or recommendations expressed in this material are thosee of the authors and do not necessarily reflect those of the NSF. 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.
Funding Information:
This research was partially supported by the National Science Foundation awards number CMMI-1728612 and CMMI-1000908. This support is gratefully acknowledged.
Funding Information:
This research was partially supported by the National Science Foundation award number CMMI-1728612. This support is gratefully acknowledged.
Publisher Copyright:
© ASCE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85106013422&partnerID=8YFLogxK
U2 - 10.1061/9780784483428.029
DO - 10.1061/9780784483428.029
M3 - Chapter in a published conference proceeding
VL - 2021-May
T3 - Geotechnical Special Publication
SP - 278
EP - 286
BT - Proceedings of the technical sessions of the international foundations congress & equipment expo ASCE, Dallas, Texas, May 10-14, 2021.
ER -