Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization.Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability “de...

This book aims to introduce the principle and design of various foundations, covering shallow foundations, mat foundations, earth retaining structures, excavations, pile foundations, and slope stability. Since the analysis and design of a foundation are based on the soil properties under short-term (undrained) or long-term (drained) conditions, the assessment of soil properties from the geotechnical site investigation and the concept of drained or undrained soil properties are discussed in...

Uncertainty, Modeling, and Decision Making in Geotechnics shows how uncertainty quantification and numerical modeling can complement each other to enhance decision-making in geotechnical practice, filling a critical gap in guiding practitioners to address uncertainties directly.The book helps practitioners acquire a working knowledge of geotechnical risk and reliability methods and guides them to use these methods wisely in conjunction with data and numerical modeling. In ...