Liquefaction of silty soils: Micromechanics, modelling and prediction. The project aims to develop a numerical approach to understand liquefaction in silty soils. Liquefaction of silty soils in submarine landslides, mine tailings dam failures and cargo liquefaction in vessels carrying iron/nickel ores can cause property loss and be fatal. This project will bridge the behaviours across the scales and deliver constitutive models that possess grain scale mechanisms for better prediction of liquefac ....Liquefaction of silty soils: Micromechanics, modelling and prediction. The project aims to develop a numerical approach to understand liquefaction in silty soils. Liquefaction of silty soils in submarine landslides, mine tailings dam failures and cargo liquefaction in vessels carrying iron/nickel ores can cause property loss and be fatal. This project will bridge the behaviours across the scales and deliver constitutive models that possess grain scale mechanisms for better prediction of liquefaction induced failure at the large scales. The expected outcomes are liquefaction criteria for silty soils with different silt contents and numerical tools to predict the onset of liquefaction and flow of liquefied soils.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101181
Funder
Australian Research Council
Funding Amount
$403,775.00
Summary
Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multipl ....Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.Read moreRead less