The workshop aims to provide a fundamental understanding of the liquefaction process, necessary to the enhancement of liquefaction prediction. The contributions are divided into eight sections, which include: factors affecting liquefaction susceptibility and field studies of liquefaction.

Rainfall-induced landslides are common around the world. With global climate change, their frequency is increasing and the consequences are becoming greater. Previous studies assess them mostly from the perspective of a single discipline—correlating landslides with rainstorms, geomorphology and hydrology in order to establish a threshold prediction value for rainfall-induced landslides; analyzing the slope’s stability using a geomechanical approach; or assessing the risk from field records. Rainfall Induced Soil Slope Failure: Stability Analysis and Probabilistic Assessment integrates probabilistic approaches with the geotechnical modeling of slope failures under rainfall conditions with unsaturated soil. It covers theoretical models of rainfall infiltration and stability analysis, reliability analysis based on coupled hydro-mechanical modelling, stability of slopes with cracks, gravels and spatial heterogenous soils, and probabilistic model calibration based on measurement. It focuses on the uncertainties involved with rainfall-induced landslides and presents state-of-the art techniques and methods which characterize the uncertainties and quantify the probabilities and risk of rainfall-induced landslide hazards. Additionally, the authors cover: The failure mechanisms of rainfall-induced slope failure Commonly used infiltration and stability methods The infiltration and stability of natural soil slopes with cracks and colluvium materials Stability evaluation methods based on probabilistic approaches The effect of spatial variability on unsaturated soil slopes and more

Model Uncertainties in Foundation Design is unique in the compilation of the largest and the most diverse load test databases to date, covering many foundation types (shallow foundations, spudcans, driven piles, drilled shafts, rock sockets and helical piles) and a wide range of ground conditions (soil to soft rock). All databases with names prefixed by NUS are available upon request. This book presents a comprehensive evaluation of the model factor mean (bias) and coefficient of variation (COV) for ultimate and serviceability limit state based on these databases. These statistics can be used directly for AASHTO LRFD calibration. Besides load test databases, performance databases for other geo-structures and their model factor statistics are provided. Based on this extensive literature survey, a practical three-tier scheme for classifying the model uncertainty of geo-structures according to the model factor mean and COV is proposed. This empirically grounded scheme can underpin the calibration of resistance factors as a function of the degree of understanding – a concept already adopted in the Canadian Highway Bridge Design Code and being considered for the new draft for Eurocode 7 Part 1 (EN 1997-1:202x). The helical pile research in Chapter 7 was recognised by the 2020 ASCE Norman Medal.