Discovery Early Career Researcher Award - Grant ID: DE130100457
Funder
Australian Research Council
Funding Amount
$360,945.00
Summary
Dynamic fracturing in shale rock through coupled continuum-discontinuum modelling. The research includes modelling the grain level fracturing of shale rock under dynamic loads. The outputs will have a direct impact on the development and optimisation of rock drilling and rock cutting technologies and will improve the operational efficiencies in which rock excavations are conducted.
The effect of climate change on the biogeochemistry of estuarine soft soils. The Australian coastline is dotted with soft clays to a significant depth. These soft clay deposits display excessive settlement characteristics, affecting transport infrastructure. Understanding the couplings between the biogeochemical composition of the pore liquid and the mechanical behaviour of soft soils is essential, but current engineering practice is limited. Sea level rise in Australia will potentially place as ....The effect of climate change on the biogeochemistry of estuarine soft soils. The Australian coastline is dotted with soft clays to a significant depth. These soft clay deposits display excessive settlement characteristics, affecting transport infrastructure. Understanding the couplings between the biogeochemical composition of the pore liquid and the mechanical behaviour of soft soils is essential, but current engineering practice is limited. Sea level rise in Australia will potentially place as much as $67 billion in transport infrastructure at risk; consequently, this project aims to examine the impact of climate change on the biogeochemical processes of estuarine sediments in relation to: geotechnical properties; soft soil stability under sea level change; and soil carbon sequestration.Read moreRead less
Preventing extreme granular wear of geotechnical machinery. This project will investigate the mechanisms controlling the mechanical wear that is incurred while handling geomaterials such as sand, ore, coal and fragmented rock. The overarching aim is to help forecast and mitigate extreme wear conditions by analysing the microscopic forces that granular materials produce when in contact with moving metallic surfaces. The intended outcomes include a thorough understanding of these interfacial inter ....Preventing extreme granular wear of geotechnical machinery. This project will investigate the mechanisms controlling the mechanical wear that is incurred while handling geomaterials such as sand, ore, coal and fragmented rock. The overarching aim is to help forecast and mitigate extreme wear conditions by analysing the microscopic forces that granular materials produce when in contact with moving metallic surfaces. The intended outcomes include a thorough understanding of these interfacial interactions and an experimentally validated theory predicting wear rates for a range of materials and handling processes. The expected benefit of this project is to enhance the productivity and reliability of the mining and construction sectors by reducing wear-related machinery failures.Read moreRead less
Geomechanics of multiple seam mining interactions. This project will address a highly significant and timely problem that has arisen in the coal mining industry. Through the application of scientific principles and advanced methods of engineering analysis, this research will develop practical guidelines that in turn will provide the means for rational planning of multi-seam mining operations.
Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings a ....Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings and outcomes of this research will advance the knowledge and practice of hard-rock mining machines in Australia. The success of this project will significantly increase mining productivity and reduce human injuryRead moreRead less
A multi-scale theory of unsaturated porous media under extreme loading. Extreme loading induced by impacts, explosives or earthquakes generates stress wave propagation through unsaturated media; this can lead to rock fracturing and soil liquefaction and severely damage civil, mining and military infrastructures and operations. The project aims to develop a novel experimentally-validated theory, with associated models, for describing dynamic responses of unsaturated porous media subject to extrem ....A multi-scale theory of unsaturated porous media under extreme loading. Extreme loading induced by impacts, explosives or earthquakes generates stress wave propagation through unsaturated media; this can lead to rock fracturing and soil liquefaction and severely damage civil, mining and military infrastructures and operations. The project aims to develop a novel experimentally-validated theory, with associated models, for describing dynamic responses of unsaturated porous media subject to extreme loading. Our continuum framework will allow building constitutive models directly from saturation-dependent contact laws at the micro-scale. This will remove the need to use the site-dependent empirical models and thus give the derived constitutive models truly predictive capabilities.Read moreRead less
Propagating fragmentation waves in granular materials. This project will conduct the first systematic study to understand and control fragmentation waves in granular systems subject to impact loading. The outcomes will be essential for geoscience including earthquakes and meteoritic impacts, and for many industries, including mining, mineral processes, petroleum production and pharmaceutics.
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH140100035
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Computational Particle Technology. ARC Research Hub for Computational Particle Technology. This research hub aims to develop and apply advanced theories and mathematical models to design and optimise particulate and multiphase processes that are widely used in the minerals and metallurgical industries. This should be achieved through detailed analysis of the fundamentals governing fluid flow, heat and mass transfer at different time and length scales, facilitated by various ....ARC Research Hub for Computational Particle Technology. ARC Research Hub for Computational Particle Technology. This research hub aims to develop and apply advanced theories and mathematical models to design and optimise particulate and multiphase processes that are widely used in the minerals and metallurgical industries. This should be achieved through detailed analysis of the fundamentals governing fluid flow, heat and mass transfer at different time and length scales, facilitated by various novel research techniques. Research outcomes including theories, computer models and simulation techniques, as well as well-trained young researchers, should have a significant impact across a range of industries of vital importance to Australia’s economic and technological future, including the minerals, metallurgical, materials, chemical, energy, pharmaceutical and environment sectors.Read moreRead less
Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the ....Deep reinforcement learning for discovering and visualising biomarkers. This project aims to develop novel methods for discovering and visualising optimal bio-markers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. The extensions proposed in this project will advance medical image analysis by allowing an efficient analysis of large dimensionality inputs in their original high resolution. In addition, this project will be the first approach capable of discovering previously unknown biomarkers associated with important clinical outcomes. The project will validate the approach on a real-world case study data set concerning the prediction of five-year survival of chronic disease.Read moreRead less