The microbe factory: a novel approach to benign minerals processing. The purpose of this project is to reduce the environmental impact of current mining practices. The anticipated outcome of this project is the replacement of toxic chemicals used in the separation of minerals with the novel use of environmentally benign microbes.
Triboelectric separation - fundamentals and practice. Triboelectric separation is a novel way to refine mineral ores without using scarce water resources, based on the familiar generation of electrostatic charge by friction. This project will provide a practical dry particle separation process, and a better understanding of a common and important problem in electrostatics.
Preventing mining disasters: reducing the risk of tailings dam failure. This project aims to improve safety of tailings storage facilities (TSFs). Mineral processing produces waste called tailings, being mixtures of water and soil-sized particles. Tailings are stored on sites contained by embankments made from soil or a coarse component of tailings. Sections of the TSFs are partially saturated, have high concentrations of fine particles and physically change with age. Their resistance to earthqu ....Preventing mining disasters: reducing the risk of tailings dam failure. This project aims to improve safety of tailings storage facilities (TSFs). Mineral processing produces waste called tailings, being mixtures of water and soil-sized particles. Tailings are stored on sites contained by embankments made from soil or a coarse component of tailings. Sections of the TSFs are partially saturated, have high concentrations of fine particles and physically change with age. Their resistance to earthquake loading and liquefaction, and strength post-earthquake, arising from these properties are poorly understood and can not be quantified reliably so will be addressed here. Anticipated outcomes will be updated industry guidelines for the design and management of TSFs. Mines will benefit and failures will be prevented.Read moreRead less
Strength and resistance along oceanic megathrust faults: implications for subduction initiation. Hjorta Trench, south of Macquarie Island, is a seismically active boundary of the Australian plate and a unique natural laboratory for study of the initiation of the processes which are currently driving Australia north at 7 millimetres per year. Sophisticated computer models will be used to understand the evolution of this oceanic megathrust system.
Tracking water on planetary surfaces using data from the Curiosity rover, the laboratory, meteorites and Australian field sites. A fundamental question in science is why does Earth have so much liquid water, but other planets do not? This project will answer this question using the Curiosity rover on Mars, studying alteration minerals that record the action of water. The project will develop new methods to improve our understanding of alteration minerals in martian meteorites, under controlled ....Tracking water on planetary surfaces using data from the Curiosity rover, the laboratory, meteorites and Australian field sites. A fundamental question in science is why does Earth have so much liquid water, but other planets do not? This project will answer this question using the Curiosity rover on Mars, studying alteration minerals that record the action of water. The project will develop new methods to improve our understanding of alteration minerals in martian meteorites, under controlled environmental conditions and in field samples that are relevant for Mars. It aims to build expertise in the environmental aspects of planetary surfaces and in novel instrumentation. This research will improve methods to examine returned extraterrestrial samples, to evaluate land degradation and to search for energy and ore deposits.Read moreRead less
Modelling and simulation of complex granular flows. Granular flows are of crucial importance in a wide range of problems related to civil infrastructure. These include landslides and similar catastrophic events, often leading to loss of life and property. The project aims to develop new methods for accurate prediction of such events thus allowing for the formulation of efficient mitigation strategies.
How the Earth moves: Developing a novel seismological approach to map the small-scale dynamics of the upper mantle. The concept of small-scale convection currents from about 100-400 km below the Earth’s surface is a model proposed to explain the origins of intraplate volcanoes and mountains. However, direct evidence for the physical reality of small-scale convection cells is generally weak. This project will develop a novel seismological approach combining both ambient noise and earthquake data ....How the Earth moves: Developing a novel seismological approach to map the small-scale dynamics of the upper mantle. The concept of small-scale convection currents from about 100-400 km below the Earth’s surface is a model proposed to explain the origins of intraplate volcanoes and mountains. However, direct evidence for the physical reality of small-scale convection cells is generally weak. This project will develop a novel seismological approach combining both ambient noise and earthquake data that can image such small-scale upper mantle convection. The outcomes of this project will help to fill the gap left in the Plate Tectonic paradigm by its inability to explain intraplate geological activity (volcanoes, earthquakes, mountains), which would be a significant step towards unifying conceptual models about how the Earth works.Read moreRead less
Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi ....Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.Read moreRead less
Variational multiscale modelling of granular materials. Granular materials play an important role in a wide-range of problems related to physical infrastructure. These include landslides and similar catastrophic events often leading to loss of life and property. This project will aim to develop new methods for adequate simulation of granular flows to allow formulation of efficient risk mitigation strategies.
Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected ....Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected outcomes include new-generation theories and methods for the unsupervised learning of complex interactions in real-life big data, which are anticipated to enable the intrinsic processing of big data complexities and substantially enhance Australia’s leadership in frontier data science research and applications. Read moreRead less