Doctoral Dissertations
Keywords and Phrases
Coefficient of variation; Reliability-based design (RBD); Second moment statistics
Abstract
"A very carefully planned Missouri-wide field exploration and laboratory investigation program, with a focus on fine-grained soils, was executed with the aim of characterizing the variability of geotechnical parameters statistically with a view to increasing the use of reliability-based design (RBD) among geotechnical engineers. Geotechnical parameters were characterized in terms of both their first and second statistical moments and their coefficient of variation (COV). Their probability distributions and their scale of fluctuation, θ, were also determined. Correlations between difficult-to-obtain parameters and more easily-obtained parameters were developed and the degree of fit of study data to published empirical correlations was investigated. Results of the analyses show that: COV and probability distribution of parameters are dependent upon the soil classification type and in-situ state; Field data, like CPTu data, which provide sufficient data to establish a well-defined parameter profile, are the best for determining θ; The Semivariogram Function (SVF) is better suited than the Autocorrelation Function (ACF) for the determination of θ from widely-spaced, non-continuous, irregular data obtained from laboratory tests; Considering the fewer number of data points from a dataset required (half that of SVF) for analysis with the ACF, the SVF is better for the determination of θ. A framework which incorporates the spatial averaging effect of parameters based on the scale of fluctuation and variance reduction factor that are computed from widely-spaced irregular and non-continuous data was proposed. The application of this framework to RBD was also illustrated with examples"--Abstract, page iii.
Advisor(s)
Ge, Yu-Ning (Louis)
Committee Member(s)
Luna, Ronaldo
Bate, Bate
Rogers, J. David
Stephenson, Richard Wesley
Department(s)
Civil, Architectural and Environmental Engineering
Degree Name
Ph. D. in Civil Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Spring 2012
Pagination
xvi, 174 pages
Note about bibliography
Includes bibliographical references (pages 163-173).
Rights
© 2012 Sitenikechukwu Onyejekwe, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Subject Headings
Reliability (Engineering)
Shear strength of soils
Structural optimization -- Mathematical models
Thesis Number
T 10007
Print OCLC #
817930493
Electronic OCLC #
817925324
Link to Catalog Record
Recommended Citation
Onyejekwe, Sitenikechukwu, "Characterization of soil variability for reliability-based design" (2012). Doctoral Dissertations. 2142.
https://scholarsmine.mst.edu/doctoral_dissertations/2142
APPENDIX B - CPeT-IT.docx (33 kB)
APPENDIX C - SECOND MOMENT STATISTICS - LABORATORY DATA.xlsx (100 kB)
APPENDIX D - SECOND MOMENT STATISTICS - CPTu DATA.xlsx (60 kB)
APPENDIX E - PEARSON'S SPACE.xlsx (1215 kB)
APPENDIX F - DISTRIBUTION TYPE - LABORATORY DATA.xlsx (74 kB)
APPENDIX G - DISTRIBUTION TYPE - CPTu DATA.xlsx (49 kB)
APPENDIX H - CORRELATION MATRIX.xlsx (26 kB)
Comments
Accompanying CD-ROM, available at Missouri S&T Library, contains the eight Appendices (Appendices A to H) referred to in this study. Appendices A and B are Microsoft Word 2007 document files while Appendices C to H are Microsoft Excel 2007 files.