| description 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. | |
