Characterising three-dimensional anisotropic spatial correlation of soil properties through in situ test results

Abstract

Proper characterisations of soil properties and their variations are pivotal to the geotechnical design process. Although multiple in situ soil tests are routinely specified and performed in geotechnical investigation programmes, the information they provide regarding the spatial correlations of soil properties are often not fully utilised. This paper presents a holistic framework to characterise the three-dimensional, anisotropic, spatial variability of soil properties, using results of in situ tests such as standard penetration tests or vane shear tests. The restricted maximum likelihood method is implemented with an anisotropic covariance model, leading to improved predictive capabilities compared to conventional approaches, and allows quantification of the uncertainties on soil properties at unsampled locations, represented as distributions of prediction variance across the entire subsurface three-dimensional domain. The magnitudes of prediction variance at different locations can be used to provide guidance on the necessities and locations of additional soil sampling. They can also provide key input parameters for random field models in site-specific probabilistic analyses of geotechnical projects. The proposed approach is applied to the study of two project sites in Hong Kong, where it is shown that the three-dimensional spatial correlation features may be interpreted together with the geological settings at the site.

Probabilistic assessment of pile group response considering superstructure stiffness and three-dimensional soil spatial variability

“…θ ln x and θ ln y are assumed to be 26 m, which is equal to the foundation width; θ ln z is assumed to be half of the pile length. These are also comparable to typical values reported in various studies [27,28]. In the numerical analyses, each pile is discretized into ten 2.5-m long elements.…”

Probabilistic assessment of geogenic arsenic distributions for risk management in the Kwu Tung North New Development Area

“…The geostatistical approach adopted in this study was developed and discussed in detail by Liu and Leung (2018) and Leung et al (2018). Essentially, the main objective of geostatistical analyses is to characterise the spatial variability/correlation patterns of arsenic, based on the existing measured data.…”

Spatial variability of saprolitic soil properties and relationship with joint set orientation of parent rock: Insights from cases in Hong Kong

“…The white noise effects may arise from measurement errors associated with the in situ tests, which are assumed not to correlate with distance. The covariance matrix of ε is denoted as V, and is given by (Liu and Leung, 2018):…”

“…At each study location, hundreds to thousands of borehole measurements are available regarding in situ soil properties and rock joint information. Using a numerical framework recently developed (Liu and Leung, 2018) for characterization of three-dimensional anisotropic spatial correlations, systematic analyses are performed on soil heterogeneity features to reveal the potential links with site geology.…”