Uncertainty in spatial average undrained shear strength with a site-specific transformation model

Journal Article (2018)
Author(s)

Mark Van Der Krogt (TU Delft - Hydraulic Structures and Flood Risk, Deltares)

T. Schweckendiek (Deltares, TU Delft - Hydraulic Structures and Flood Risk)

Matthijs Kok (TU Delft - Hydraulic Structures and Flood Risk)

Research Group
Hydraulic Structures and Flood Risk
Copyright
© 2018 M.G. van der Krogt, T. Schweckendiek, M. Kok
DOI related publication
https://doi.org/10.1080/17499518.2018.1554820
More Info
expand_more
Publication Year
2018
Language
English
Copyright
© 2018 M.G. van der Krogt, T. Schweckendiek, M. Kok
Research Group
Hydraulic Structures and Flood Risk
Issue number
3
Volume number
13 (2019)
Pages (from-to)
226-236
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Transformation models are used to infer geotechnical properties from indirect measurements. A site-specific transformation model can be calibrated with direct and indirect measurements from a site. When such a model is used, then spatial variability, measurement errors and statistical uncertainty propagate into the uncertainty of the spatial average, which is the variable of interest in most geotechnical analyses. This research shows how all components enter the total uncertainty of a transformation model for undrained shear strength from cone resistance. A method is proposed to estimate the uncertainty in the spatial average undrained shear strength, particularly focusing on the role of averaging of all spatially variable error components. The main finding is that if a considerable share of the measurement and transformation errors is random or spatially variable, the uncertainty estimates can be considerably lower compared to methods proposed earlier, and hence, characteristic values can be considerably higher.