Optimization of Soil Parameters for Deep Excavations by Inverse Analysis

The proposed research aims to optimize soil model parameters through inverse analysis of deep excavations. Soil properties and their engineering behavior are the fundamental uncertainties among the many influential factors involved in deep excavations. Even though geotechnical investigations are usually conducted, the risks are still high due to the limited amount of soil samples extracted from the site. In addition, glacial deposits covering the Greater Toronto Area (GTA) make it very difficult to characterize their properties accurately due to its unsorted grain distribution and highly variable properties, which can easily lead to unsafe design. The goal of this research is to conduct an inverse analysis of deep excavations to optimize soil properties and then correlate the optimized model parameters with soil indices for different soils in the GTA. This research will help mitigate geotechnical risks and develop cost-effective infrastructure development in Canada.

Faculty Supervisor:

Jinyuan Liu

Student:

Partner:

InGeo Design Ltd

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Toronto Metropolitan University

Program: