Towards autonomous structural safety prognostics: integrating in-situ imaging and predictive modelling. This project aims to advance a scientific basis for autonomous safety prognostics by developing predictive models and in-situ damage imaging principles. Development of this new health prognostic approach will overcome the significant challenge of safety assurance of composite structures in the presence of in-service damage, which is largely hidden.
Baseline-free Methods for Early Damage Diagnosis using Nonlinear Ultrasound. To address the significant limitation of existing non-destructive evaluation techniques in detecting and characterising early damage, this project aims to discover the physical nature of self-generated nonlinear waves by structural damage and to explore its potential for an entirely new class of non-destructive evaluation and structural health monitoring techniques. Major applications are expected to include a baseline- ....Baseline-free Methods for Early Damage Diagnosis using Nonlinear Ultrasound. To address the significant limitation of existing non-destructive evaluation techniques in detecting and characterising early damage, this project aims to discover the physical nature of self-generated nonlinear waves by structural damage and to explore its potential for an entirely new class of non-destructive evaluation and structural health monitoring techniques. Major applications are expected to include a baseline-free structural health monitoring technique capable of detecting and quantifying barely-visible impact damage in advanced composite materials, non-destructive evaluation of structures made by additive manufacturing, and detection of hard-to-inspect locations in unitised structures.Read moreRead less
Understanding dissipation, thermal conduction and diffusion in superionic conductors using ab initio nonequilibrium molecular dynamics simulation. Lithium ion batteries are widely used in computers, cars and more recently in aircraft. However they may exhibit thermal runaway leading to fire. Recently these problems have grounded the fleet of Boeing 787 aircraft, worldwide. Understanding superionic conduction is of thus of considerable technological importance. The project will focus on understa ....Understanding dissipation, thermal conduction and diffusion in superionic conductors using ab initio nonequilibrium molecular dynamics simulation. Lithium ion batteries are widely used in computers, cars and more recently in aircraft. However they may exhibit thermal runaway leading to fire. Recently these problems have grounded the fleet of Boeing 787 aircraft, worldwide. Understanding superionic conduction is of thus of considerable technological importance. The project will focus on understanding mass and heat flow in superionic conductors using a new molecular simulation technique that the team has recently developed. This technique combines nonequilibrium statistical mechanics and ab initio molecular dynamics simulation. The project will learn how heat is generated and conducted through these materials and how temperature influences these processes, and how heat and mass flow couple together.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less