Keynote Speech 6
Slope reliability analysis and risk assessment: a modern computational perspective
Professor, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University
Abstract
Slope failure is one of the most commonly-encountered geo-hazards. It is indispensable to properly evaluate slope failure probability and consequences for quantitative slope risk management and reduction. This task relies on the understanding of site conditions, slope stability modeling and analysis, uncertainty quantification and propagation, etc. Slope reliability analysis and risk assessment can be accomplished under a probabilistic framework in a rational and rigorous way. With the advance of computing technologies, slope reliability analysis and risk assessment allow for incorporating more geological and geotechnical details into the analysis, such as soil stratification uncertainty, inherent spatial variability, model uncertainty, multiple failure modes, etc. This study presents recent developments of computer-based simulation methods for slope reliability analysis and risk assessment, which take full advantage of modern computational technologies and powers. Major topics include efficient slope reliability analysis methods based on surrogate models and/or variance reduction techniques, slope system risk assessment method, and effects of various uncertainties on slope failure modes and risk. The roles of advanced computer-based simulation techniques in slope reliability analysis and risk assessment will be emphasized.
Biography
Dianqing Li is a Professor in the State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University. His main research interests include risk and reliability in geotechnical engineering, risk and uncertainty in dams, embankments, and slopes. He published more than 130 research papers in reputable SCI journals. He served as an executive board member of Geotechnical Safety Network (GEOSNet), a member of TC304 (risk) in the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE), and a member of ASCE Technical Committee on Risk Assessment and Management. He is currently editorial board members (EBM) of several international journals, including Computers and Geotechnics, Soils and Foundations, Georisk, and ASCE-ASME Journal of Risk and Uncertainty in Engineering System. He is the recipient of the GEOSNet Award in 2019, Sloan Outstanding Paper Award for 2019 (Computers and Geotechnics), First-class award for natural science, Hubei Provincial Government, 2017, First-class award for natural science, Ministry of Education, 2011 and 2020, National Science Fund for Distinguished Young Scholars, China, in 2012, and the Young and Middle-Aged Leading Scientists, Engineers and Innovators, Ministry of Science and Technology, China, in 2013.
Professor, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University
Abstract
Slope failure is one of the most commonly-encountered geo-hazards. It is indispensable to properly evaluate slope failure probability and consequences for quantitative slope risk management and reduction. This task relies on the understanding of site conditions, slope stability modeling and analysis, uncertainty quantification and propagation, etc. Slope reliability analysis and risk assessment can be accomplished under a probabilistic framework in a rational and rigorous way. With the advance of computing technologies, slope reliability analysis and risk assessment allow for incorporating more geological and geotechnical details into the analysis, such as soil stratification uncertainty, inherent spatial variability, model uncertainty, multiple failure modes, etc. This study presents recent developments of computer-based simulation methods for slope reliability analysis and risk assessment, which take full advantage of modern computational technologies and powers. Major topics include efficient slope reliability analysis methods based on surrogate models and/or variance reduction techniques, slope system risk assessment method, and effects of various uncertainties on slope failure modes and risk. The roles of advanced computer-based simulation techniques in slope reliability analysis and risk assessment will be emphasized.
Biography
Dianqing Li is a Professor in the State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University. His main research interests include risk and reliability in geotechnical engineering, risk and uncertainty in dams, embankments, and slopes. He published more than 130 research papers in reputable SCI journals. He served as an executive board member of Geotechnical Safety Network (GEOSNet), a member of TC304 (risk) in the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE), and a member of ASCE Technical Committee on Risk Assessment and Management. He is currently editorial board members (EBM) of several international journals, including Computers and Geotechnics, Soils and Foundations, Georisk, and ASCE-ASME Journal of Risk and Uncertainty in Engineering System. He is the recipient of the GEOSNet Award in 2019, Sloan Outstanding Paper Award for 2019 (Computers and Geotechnics), First-class award for natural science, Hubei Provincial Government, 2017, First-class award for natural science, Ministry of Education, 2011 and 2020, National Science Fund for Distinguished Young Scholars, China, in 2012, and the Young and Middle-Aged Leading Scientists, Engineers and Innovators, Ministry of Science and Technology, China, in 2013.
