Scale of fluctuation for spatially varying soils: estimation methods and values
Spatial variability is one of the major sources of uncertainty in geotechnical applications.
This variability is characterized customarily by the scale of fluctuation. Scale of fluctuation …
This variability is characterized customarily by the scale of fluctuation. Scale of fluctuation …
State-of-the-art review of geotechnical-driven artificial intelligence techniques in underground soil-structure interaction
There has been an increasing demand for underground construction due to urbanization
and limited land in metropolitan cities in the recent years. However, the behavior of …
and limited land in metropolitan cities in the recent years. However, the behavior of …
Assessment of pile drivability using random forest regression and multivariate adaptive regression splines
W Zhang, C Wu, Y Li, L Wang… - Georisk: Assessment and …, 2021 - Taylor & Francis
Driven pile is widely used as an effective and convenient structural component to transfer
superstructure loads to deep stiffer soils. Nevertheless, during the design process of piles …
superstructure loads to deep stiffer soils. Nevertheless, during the design process of piles …
Constructing quasi-site-specific multivariate probability distribution using hierarchical Bayesian model
In geotechnical engineering, it is challenging to construct a site-specific multivariate
probability distribution model for soil/rock properties because the site-specific data are …
probability distribution model for soil/rock properties because the site-specific data are …
Constructing site-specific multivariate probability distribution model using Bayesian machine learning
This study proposes a novel data-driven Bayesian machine learning method for constructing
site-specific multivariate probability distribution models in geotechnical engineering. There …
site-specific multivariate probability distribution models in geotechnical engineering. There …
Hierarchical Bayesian model for predicting small-strain stiffness of sand
This paper develops a hierarchical Bayesian model (HBM) that integrates the physical
knowledge and the test data to predict the small-strain shear modulus G max for a target …
knowledge and the test data to predict the small-strain shear modulus G max for a target …
The story of statistics in geotechnical engineering
KK Phoon - Georisk: Assessment and Management of Risk for …, 2020 - Taylor & Francis
The story of statistics in geotechnical engineering can be traced to Lumb's classical
Canadian Geotechnical Journal paper on “The Variability of Natural Soils” published in …
Canadian Geotechnical Journal paper on “The Variability of Natural Soils” published in …
A hierarchical Bayesian similarity measure for geotechnical site retrieval
Geotechnical site retrieval refers to the quantitative identification and extraction of sites
similar to a given target site from predocumented generic sites in a database. This is known …
similar to a given target site from predocumented generic sites in a database. This is known …
Role of reliability calculations in geotechnical design
KK Phoon - Georisk: Assessment and Management of Risk for …, 2017 - Taylor & Francis
This paper adds to the ongoing discussion on the role of reliability calculations in
geotechnical design. It situates design calculations, be it verified by a global factor of safety …
geotechnical design. It situates design calculations, be it verified by a global factor of safety …
A spectral algorithm for quasi-regional geotechnical site clustering
Geotechnical site clustering refers to identifying (or learning) groups in a site-labelled
soil/rock database based on inter-site similarity. It is common to cluster sites in a “region” in …
soil/rock database based on inter-site similarity. It is common to cluster sites in a “region” in …