Motion of objects in soils. This project aims to conduct a fundamental study of a challenging class of geotechnical problems in which an object moves inside a layer of soil, interacts with soil, and disturbs it, by developing advanced numerical and analytical methods. This project expects to determine the fundamental principles governing soil behaviour upon movement of embedded objects. The expected outcomes are robust solutions and computational procedures that will benefit government and engin ....Motion of objects in soils. This project aims to conduct a fundamental study of a challenging class of geotechnical problems in which an object moves inside a layer of soil, interacts with soil, and disturbs it, by developing advanced numerical and analytical methods. This project expects to determine the fundamental principles governing soil behaviour upon movement of embedded objects. The expected outcomes are robust solutions and computational procedures that will benefit government and engineers by providing safer and more cost-effective strategies for designing, constructing, and maintaining Australia's infrastructure. This should bring significant benefits to industries engaged in harvesting energy resources, such as wind farms, as well as oil and gas.Read moreRead less
Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolut ....Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolution algorithms, and cooperative co-evolutionary strategies. The outcome results will be demonstrated by practical evaluations over public datasets and comparisons to related works. The project is beneficial to the nation in both theory of artificial intelligence techniques and applications of real transport systems.Read moreRead less