Yan-Guo Zhou, Professor, Zhejiang University, P. R. China, qzking@zju.edu.cn
Jie Zhang, Professor, Tongji University, P. R. China, cezhangjie@tongji.edu.cn

Soil liquefaction, either seismically or statically triggered, is one of the most consequential geo-hazards for critical infrastructure and for the urban environment, which may cause severe damages to embankment and dams, ports, roads, highways and buildings and consequently delay the disaster rescue and relief actions. A fast and reliable assessment of liquefaction hazard is of great importance for making disaster prevention plans beforehand and for planning rescue and relief activities right after earthquakes. In the past decades, tremendous data of either field case history study or laboratory testing related soil liquefaction problems are available, many of which have been well documented by the engineering/scientific community. It will definitely provide the most updated database for further analysis of soil liquefaction hazard and risk by data-driven approaches in view of the fascinating developments in the field of machine learning.

In this session, we aim to revisit field case histories from past liquefaction events during the recent strong earthquakes, recompile the laboratory test data of soil element and physical modeling, in an effort to uncover the mechanism related to the phenomena and quantifying the hazard risk by adopting the data-driven approaches. The topics in this session include but are not limited to:
(1)Post-earthquake field case history study and liquefaction database
(21)Soil liquefaction tests in laboratory and database in soil element scale
(3)Physical modeling of soil liquefaction and database in boundary value problems
(4)Machine learning for soil liquefaction behavior and analysis
(5)Data-driven and deterministic approaches for risk assessment of soil liquefaction hazards