A multi-scale theory for solid-granular transition due to fragmentation. The prediction of rock fragmentation and fragment sizes during its phase transition from solid (rock mass) to granular (ore fragments) is the most crucial problem in a cave mining operation. Current practice relies on empirical tools without fundamentals of fracture, and hence cannot reliably predict the fragmentation process and fragment sizes. This can lead to huge economic loss due to damage to extraction points, hold-up ....A multi-scale theory for solid-granular transition due to fragmentation. The prediction of rock fragmentation and fragment sizes during its phase transition from solid (rock mass) to granular (ore fragments) is the most crucial problem in a cave mining operation. Current practice relies on empirical tools without fundamentals of fracture, and hence cannot reliably predict the fragmentation process and fragment sizes. This can lead to huge economic loss due to damage to extraction points, hold-ups for safety precautions, and mine closures. The project will develop a new theory and models to describe this solid-granular transition, and computational tools for simulations of cave mining operations. The expected benefits and outcomes include safer operations, and better control of production schedule and budgeting.Read moreRead less
Carbon conundrum: Functional characterisation of organic matter-clay mineral interactions in relation to carbon sequestration. Carbon sequestration in soil has been recognised as one of the possible measures through which greenhouse gas emissions can be mitigated. The major processes involved in carbon sequestration in soil include chemical immobilisation of carbon with soil particles and physical protection in the pores of soil microaggregates. These two processes are mediated through the funct ....Carbon conundrum: Functional characterisation of organic matter-clay mineral interactions in relation to carbon sequestration. Carbon sequestration in soil has been recognised as one of the possible measures through which greenhouse gas emissions can be mitigated. The major processes involved in carbon sequestration in soil include chemical immobilisation of carbon with soil particles and physical protection in the pores of soil microaggregates. These two processes are mediated through the functional relationships of soil organic matter and clay mineral interactions in soils. This project investigates nanoscale organomineral association underlying microaggregate formation and stability, as well as the distribution and microbial decomposition of carbon within microaggregates using a suite of advanced spectroscopic, molecular and isotopic techniques.Read moreRead less
Nature's mechanisms for leaching and remobilising metals. This project aims to understand the chemical and physical processes that govern reactive transport and metal scavenging in rocky environments. Much of Australia's mineral wealth is the result of the interaction of warm fluids with rocks deep in the Earth over geological timescales. The formation of ore deposits is governed by the physical chemistry of mineral dissolution and crystallisation, and by fluid flow through porous rocks and frac ....Nature's mechanisms for leaching and remobilising metals. This project aims to understand the chemical and physical processes that govern reactive transport and metal scavenging in rocky environments. Much of Australia's mineral wealth is the result of the interaction of warm fluids with rocks deep in the Earth over geological timescales. The formation of ore deposits is governed by the physical chemistry of mineral dissolution and crystallisation, and by fluid flow through porous rocks and fractures. This project integrates innovation in geology, chemistry, and mineral engineering, and will deliver mineral-scale reaction models that will increase efficiency of in-situ mining and leaching technologies. Knowledge generated can be applied to improve mineral exploration, mining, and processing, contributing to unlocking billions of dollars’ worth of resources tied up in low grade, mineralogically complex ores.Read moreRead less
Molecular Structure and Transport Properties of Hydrothermal Fluids under Extreme Conditions: Near-Critical, High Salinity, High Pressure and High Volatile Contents. The experimental capabilities, theoretical understanding, and numerical modeling methods developed in this project have broad implication for supporting both well-established (mineral exploration and ore processing) and emerging (geothermal energy; geosequestration) industries of core significance for the future of Australia's econo ....Molecular Structure and Transport Properties of Hydrothermal Fluids under Extreme Conditions: Near-Critical, High Salinity, High Pressure and High Volatile Contents. The experimental capabilities, theoretical understanding, and numerical modeling methods developed in this project have broad implication for supporting both well-established (mineral exploration and ore processing) and emerging (geothermal energy; geosequestration) industries of core significance for the future of Australia's economy. This project also provides access to unique technology developed overseas; this technology will be adapted for the unique challenges faced by Australia, and made available to the broader scientific community via the Australian Synchrotron.Read moreRead less
Climate and environmental history of SE Queensland dunefields. This project aims to generate fundamental information about the timing and mode of formation of sand dunes in the world's largest downdrift sand system, Cooloola and Fraser Island, Queensland. The project aims to provide a world class record of climate variability, sea-level change and long term climate change from the sub-tropics of Australia, an area critical to understanding global climate links and sea-level change but where high ....Climate and environmental history of SE Queensland dunefields. This project aims to generate fundamental information about the timing and mode of formation of sand dunes in the world's largest downdrift sand system, Cooloola and Fraser Island, Queensland. The project aims to provide a world class record of climate variability, sea-level change and long term climate change from the sub-tropics of Australia, an area critical to understanding global climate links and sea-level change but where high quality long-term records are sparse and little investigated. This project will also underpin the outstanding universal value of the Fraser Island World Heritage Area which is based on the area being the world's largest sand island, but for which scientific understanding of the sand dunes is remarkably poor.Read moreRead less
Efficient causal discovery from observational data. Discovering cause-effect relationships is the ultimate goal for many applications. Randomised control trial is the gold standard for discovering causal relationships. However, conducting such trials is impossible in many cases due to cost and/or ethical concerns. In contrast, a large amount of data has been accumulated in all areas. It is desirable to infer causal relationships from data directly and automatically. This project aims to develop ....Efficient causal discovery from observational data. Discovering cause-effect relationships is the ultimate goal for many applications. Randomised control trial is the gold standard for discovering causal relationships. However, conducting such trials is impossible in many cases due to cost and/or ethical concerns. In contrast, a large amount of data has been accumulated in all areas. It is desirable to infer causal relationships from data directly and automatically. This project aims to develop fast and scalable data mining methods for identifying causal relationships from large and/or high dimensional data sets. The developed methods will mainly be evaluated in real world biological applications. The research outcomes will be useful in many areas for causal reasoning and decision making.Read moreRead less
Fairness aware data mining for discrimination free decision-making. This project aims to develop data mining methods to detect algorithmic discriminations and to build fair decision models. It expects to provide techniques for regulatory organisations to detect discriminations in algorithmic decisions, and for various companies and organisations to build fair decision systems. Expected outcomes are novel and accurate methods for discrimination detection, practical and versatile techniques for fa ....Fairness aware data mining for discrimination free decision-making. This project aims to develop data mining methods to detect algorithmic discriminations and to build fair decision models. It expects to provide techniques for regulatory organisations to detect discriminations in algorithmic decisions, and for various companies and organisations to build fair decision systems. Expected outcomes are novel and accurate methods for discrimination detection, practical and versatile techniques for fair decision model building, and improved understanding of the relationships between privacy preservation and discrimination prevention to enable new techniques to achieve both goals. The developed techniques enable society to tackle ethical challenges in the big data era where many decisions are analytics based. Read moreRead less
Developing novel data mining methods to reveal complex group relationships from heterogeneous data. This project aims to develop novel and effective data mining methods that will enable us to unravel the relationships between multiple, rather than individual, components of complex systems (such as genes, gene regulators and cancer), which is crucial to understanding how such systems work. Potential applications for such methods are extensive.
Online Learning for Large Scale Structured Data in Complex Situations. Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. However, OL has three weaknesses: it does not scale for structured data; it often assumes that all of the data are equally important; it often considers that all of the data are compl ....Online Learning for Large Scale Structured Data in Complex Situations. Online Learning (OL) is the process of predicting answers for a sequence of questions. OL has enjoyed much attention in recent years due to its natural ability of processing large scale non-structured data and adapting to a changing environment. However, OL has three weaknesses: it does not scale for structured data; it often assumes that all of the data are equally important; it often considers that all of the data are complete and noise-free. These weaknesses limit its utility, because real data such as those that must be analysed in processing social networks, fraud detection do not satisfy the restrictions. The aim of this project is to develop theoretical and practical advances in OL that overcome the existing weaknesses.Read moreRead less
Probabilistic Graphical Models For Interventional Queries. The project intends to develop methods to suggest how to optimally intervene so that the future state of the system will best suit our interests. The power of probabilistic graphical models to model complex relationships and interactions among a large number of variables facilitates many applications. However, such models only aim to understand the underlying environment. What is ultimately needed in many real-world applications is to su ....Probabilistic Graphical Models For Interventional Queries. The project intends to develop methods to suggest how to optimally intervene so that the future state of the system will best suit our interests. The power of probabilistic graphical models to model complex relationships and interactions among a large number of variables facilitates many applications. However, such models only aim to understand the underlying environment. What is ultimately needed in many real-world applications is to suggest how we ought to intervene or act, so as to alter the environment to best suit our interests. The proposed project aims to achieve this using probabilistic graphical models on massive real-world data sets, thus facilitating a variety of applications from health care to commerce and the environment.Read moreRead less