Abstract
ISO2394:2015 contains a new informative Annex D on “Reliability of Geotechnical Structures”. The emphasis in Annex D is to identify and characterize critical elements of the geotechnical reliability-based design (RBD) process, while respecting the diversity of geotechnical engineering practice arising from the influence of site-specific conditions. Annex D should pave the way for future code revisions to inject greater realism into geotechnical RBD. The most important element is the characterization of geotechnical variability. There are some noteworthy features: (1) the coefficient of variation (COV) of a geotechnical design parameter does not fall within a narrow range of values, (2) the multivariate nature of geotechnical data can be exploited to reduce the COV, (3) spatial variability affects the limit state beyond reduction in COV due to spatial averaging, and (4) statistical uncertainty may be significant, because the volume of soil sampled is a minute fraction of the volume of interest. Another important element is the characterization of model uncertainty. Geotechnical design codes, be it reliability-based or otherwise, must cater to diverse local site conditions and diverse local practices that grew and evolved over the years to suit these conditions. One obvious example is that the COVs of geotechnical parameters can vary over a wide range, because diverse property evaluation methodologies exist to cater to these diverse practice and site conditions. Another example is that deep foundations are typically installed in layered soil profiles that vary from site to site. These diverse site specific design scenarios do not surface in structural engineering. Section D.5.2 notes that reliability calibration for geotechnical RBD is more challenging for this reason.
Original language | English |
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Pages (from-to) | 24-33 |
Number of pages | 10 |
Journal | Structural Safety |
Volume | 62 |
Issue number | September |
DOIs | |
Publication status | Published - 30 May 2016 |
Keywords
- ISO2394:2015
- Geotechnical variability
- Multivariate geotechnical data
- Model factor
- Reliability-based design