Probabilistic Evaluation of Seismic Soil Liquefaction in Sands Using Cone Penetration Test (CPT)Data

Razavi Nasab, Mohammad | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53339 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Ahmadi, Mohammad Mehdi
  7. Abstract:
  8. More than half a century has passed since the start of research on seismic liquefaction phenomenon in cohesionless soils, and various researchers has proposed different correlations for liquefaction prediction based on in situ tests. However, there still exists a great uncertainty in liquefaction prediction correlations, and liquefaction still occurs in different parts of the world. Hence, the main objective of this research is to reduce uncertainty in seismic liquefaction initiation correlations. While the technical literature indicates that soil resistance can alter due to liquefaction and shaking events and soil resistance after the liquefaction is not necessarily indicative of it prior to the liquefaction, most correlations employ test logs that were performed after the liquefaction event to predict liquefaction, and this is a main source of uncertainty in liquefaction prediction correlations. Soil resistance alteration due to liquefaction and shaking events is characterized and shown in this study using cone penetration test (CPT) logs from the 2010-2011 Canterbury earthquake sequence (CES). Knowing that soil resistance can be altered by occurrence of liquefaction, 83 CPT logs are collated in this study from the 2010-2011 CES all of which were performed prior to a certain liquefaction event. These case histories can reduce uncertainty in liquefaction prediction correlation for they are a better index of soil resistance prior to a liquefaction. Regression modeling is employed to reach at a model for soil cyclic resistance ratio (CRR) and deterministic evaluation of liquefaction potential. Moreover, reliability methods are employed in a Bayesian framework for probabilistic evaluation of liquefaction potential
  9. Keywords:
  10. Reliability Analysis ; Cone Penetration Test ; Liquefaction ; Bayesian Regression Modeling ; Probabilistic Assessment ; Granular Soil

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