Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor ....Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.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
Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This ....Robust learning of dynamic systems. Robots and other autonomous machines use models of the real world to predict the result of their actions and make decisions, but existing methods used for machine-learning are unreliable in many cases and can be easily fooled. This project aims to make machine-learning of dynamic system models reliable, accurate, and secure. The outcomes of this project will be new models and algorithms that ensure safety and increase accuracy of models learned from data. This project will benefit robotics, control engineering, infrastructure automation, and other fields that demand the capability to model physical systems from limited data. It will also improve cybersecurity by making learning algorithms resilient to deliberate attacks with false data.Read moreRead less
Readying Wireless Networks for Future Communications Systems: From Ubiquitous Computing to the Internet of Things. This project aims to prepare wireless networks for future communications systems, by improving the data transmission rates of wireless networks, through developing new coding schemes based on the synergy of noisy-channel coding and index coding. This will allow wireless networks, used in conjunction with the fibre-optic National Broadband Network, to support future high-data-rate an ....Readying Wireless Networks for Future Communications Systems: From Ubiquitous Computing to the Internet of Things. This project aims to prepare wireless networks for future communications systems, by improving the data transmission rates of wireless networks, through developing new coding schemes based on the synergy of noisy-channel coding and index coding. This will allow wireless networks, used in conjunction with the fibre-optic National Broadband Network, to support future high-data-rate and ubiquitous communication services. This project aims to produce new theoretical results in the field of communication theory, and efficient practical coding schemes for wireless communications.Read moreRead less
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
Industrial Transformation Training Centres - Grant ID: IC180100030
Funder
Australian Research Council
Funding Amount
$3,925,357.00
Summary
ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching ....ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching objectives are to enable development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets.Read moreRead less
Millimetre wave communications for mobile broadband systems. This project aims to develop innovative millimetre wave (mmWave) communication theories and techniques, in order to significantly improve the data rate and network capacity for mobile broadband. Pragmatic transceiver designs, channel estimation algorithms, and network optimisation tools will be developed to quantify the potential of this promising wireless infrastructure. The technologies are designed to exploit the abundant mmWave spe ....Millimetre wave communications for mobile broadband systems. This project aims to develop innovative millimetre wave (mmWave) communication theories and techniques, in order to significantly improve the data rate and network capacity for mobile broadband. Pragmatic transceiver designs, channel estimation algorithms, and network optimisation tools will be developed to quantify the potential of this promising wireless infrastructure. The technologies are designed to exploit the abundant mmWave spectrum and complement the state-of-the-art cellular systems to fulfil the formidable demand for ultra-fast data services. The project outcomes are expected to increase mobile broadband speed by an order of magnitude which can benefit end-user experience and open up new opportunities for network providers.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101293
Funder
Australian Research Council
Funding Amount
$426,717.00
Summary
Dynamic Fracturing and Energy Release Mechanisms in Heterogeneous Materials. The prediction of fracturing behaviour in geomaterials (i.e. rock, soil and concrete) under dynamic/impact loads is essential in dealing with a wide range of engineering problems including excavation and mining, blasting and fragmentation, earthquake engineering, impact cratering, and protective structure design However, current knowledge and modelling capabilities of these applications remains empirically based. This p ....Dynamic Fracturing and Energy Release Mechanisms in Heterogeneous Materials. The prediction of fracturing behaviour in geomaterials (i.e. rock, soil and concrete) under dynamic/impact loads is essential in dealing with a wide range of engineering problems including excavation and mining, blasting and fragmentation, earthquake engineering, impact cratering, and protective structure design However, current knowledge and modelling capabilities of these applications remains empirically based. This project aims to investigate fundamental issues governing the dynamic fracturing of geomaterials and apply this knowledge to advance the understanding and modelling capacity of dynamic fractures in geomaterials.Read moreRead less
Optical wireless communications: solving the spectrum crunch. This project aims to make optical wireless communication to handheld mobile receivers a reality by developing systems which combine holographic filters and microsystems to realise a new form of receiver. This will be based on analysis of all of the complex interactions of transmitter, receiver and channel properties. The new receivers will exploit the narrow field of view of holographic optical filters. This project will generate know ....Optical wireless communications: solving the spectrum crunch. This project aims to make optical wireless communication to handheld mobile receivers a reality by developing systems which combine holographic filters and microsystems to realise a new form of receiver. This will be based on analysis of all of the complex interactions of transmitter, receiver and channel properties. The new receivers will exploit the narrow field of view of holographic optical filters. This project will generate knowledge in the fields of communications theory and on the use of holographic filters and microsystems. This solution to the lack of available radio frequency spectrum which conventional wireless face will provide significant practical and commercial benefits.Read moreRead less