Sources of Uncertainty in Site Characterization and Their Impact on Geotechnical Reliability-Based Design
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3, Issue 4
Abstract
Different variabilities and uncertainties (e.g., inherent variability, measurement errors, statistical uncertainty, and transformation uncertainty) in site characterization are usually lumped together as total variability and used subsequently in geotechnical reliability-based design or probabilistic geotechnical analysis. However, only the inherent variability affects the observed performance of geotechnical structures. Knowledge uncertainties (i.e., measurement errors, statistical uncertainty, and transformation uncertainty) have no impact on performance of geotechnical structures, although they may significantly affect the calculated failure probability or risk. In this paper, a comparative study is performed using the total variability approach, which lumps various uncertainties together, and the Bayesian inverse analysis approach, which explicitly characterizes inherent variability, to perform probabilistic characterization of effective friction angle from cone penetration test (CPT) results. The probabilistic characterization results from the two approaches are used in a Eurocode 7 evaluation example of foundation design to explore their impacts on reliability-based design of foundation. It is found that the total variability approach leads to much larger uncertainty in geotechnical properties than the Bayesian inverse analysis approach. Consequently, the total variability approach leads to larger calculated failure probabilities for the foundation and subsequently produces a foundation design that is much more conservative than those from the Bayesian inverse analysis approach.
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Acknowledgments
The work described in this paper was supported by grants from the Research Grants Council of the Hong Kong. Special Administrative Region, China [Project No. 9042331 (CityU 11225216) and Project No. 8779012 (T22-603/15N)]. The financial support is gratefully acknowledged.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3 • Issue 4 • December 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Nov 28, 2016
Accepted: Apr 7, 2017
Published online: Aug 19, 2017
Published in print: Dec 1, 2017
Discussion open until: Jan 19, 2018
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