主讲人：Wang Yu （王 宇）教授
Dr. Yu Wang (王宇) is an Associate Professor of geotechnical engineering at City University of Hong Kong. He obtained his PhD degree from Cornell University, USA. He is a Registered Professional Civil Engineer in Hong Kong and an elected Fellow of American Society of Civil Engineers (ASCE). He served as president of ASCE Hong Kong Section in 2012-2013. His recent research efforts have focused on analytics and simulation of spatially varying but sparsely measured geo-data, machine learning in geotechnical engineering, geotechnical uncertainty, reliability and risk, soil-structure interaction, and seismic risk assessment of critical civil infrastructure systems. His research has earned several international recognitions, including the Highly Cited Research Award by the international journal of Engineering Geology in 2017, the First Class Award of the Natural Science Award in 2017, Hubei Provincial Government, China (湖北省自然科学奖一等奖), the GEOSNet Young Researcher Award by the Geotechnical Safety Network (GEOSNet) in 2015 in the Netherlands, and the Wilson Tang Best Paper Award in 2012 in Singapore. Dr Wang has authored/co-authored more than 140 technical publications in English, including 2 books and about 90 journal papers.
This seminar investigates the occurrence and evolution of various slope failure modes during large deformation in spatially variable soils using Monte Carlo simulation combined with Limit Equilibrium Method (LEM) and Material Point Method (MPM). The proposed method takes advantage of both methods, i.e., the computational efficiency of LEM and the MPM’s capability of modeling the whole process of a landslide, particularly large deformation of soils after the landslide is initiated. The proposed method is illustrated through a two-layer cohesive soil slope. Four slope failure modes (i.e., shallow, intermediate, deep and progressive failure modes) are identified and characterized quantitatively. It is found that the evolution and consequences of these failure modes depend on spatial distribution of soil shear strength. This highlights the value of the site-specific spatial variability information obtained from site investigation.