Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to bu ....Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to build practical mathematical models for droplet impaction, spreading and evaporation on leaf surfaces, and experimentally calibrate and validate the models. The software is expected to drive the development of agrichemical products that increase retention, minimise environmental impacts, and reduce costs for end-users.Read moreRead less
Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptiv ....Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptive trust and integrity preserving methods, and reliable distributed data processing mechanisms to mitigate vulnerabilities in real-time IoT-enabled critical surveillance. This should provide significant benefits to Australia's economy, one of which is the enhanced consumer-centric adoption of IoT for sensitive operations.Read moreRead less
Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutt ....Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutting-edge Blockchain based secure IoT data management and privacy-preserving smart contracts for smart farming supply-chain management. This data infrastructure will be the first of its kind which will lay a solid foundation for smart farming technology.Read moreRead less
Foundations for offshore wind turbines in Australian carbonate seabed soils. This projects aims to enable performance prediction of foundations for offshore wind turbines in the challenging carbonate sandy sediments which are prevalent offshore Australia. This is significant for an emerging industry with each project costing tens of billions of dollars and foundations accounting for a quarter of the development cost. This project expects to provide guidance for these complex different soil condi ....Foundations for offshore wind turbines in Australian carbonate seabed soils. This projects aims to enable performance prediction of foundations for offshore wind turbines in the challenging carbonate sandy sediments which are prevalent offshore Australia. This is significant for an emerging industry with each project costing tens of billions of dollars and foundations accounting for a quarter of the development cost. This project expects to provide guidance for these complex different soil conditions that is based on advanced understanding obtained from innovative experimental and numerical techniques. Expected outcomes include de-risking through significantly reduced uncertainties. This research should therefore lead to significant economic and societal benefits of affordable clean energy and generation of jobs.Read moreRead less
Design guideline for suction caissons supporting offshore wind turbines. This project aims to develop an industry guideline for suction caisson foundations, that are a new form of fixed platform anchor, for offshore wind turbines. The project expects to generate new knowledge of caisson response during installation and over millions of wind/wave load cycles, by integrating field experience with measurements from innovative experiments. The expected outcomes of this project include new methods to ....Design guideline for suction caissons supporting offshore wind turbines. This project aims to develop an industry guideline for suction caisson foundations, that are a new form of fixed platform anchor, for offshore wind turbines. The project expects to generate new knowledge of caisson response during installation and over millions of wind/wave load cycles, by integrating field experience with measurements from innovative experiments. The expected outcomes of this project include new methods to guide suction installation in difficult soil layering and predicting rotation and stiffness over a turbine’s operational life. The benefits of these scientific advances will contribute to the economic and reliable design of suction caisson foundations and a more rapid take-up of offshore wind energy.Read moreRead less
Securing Australian floating wind developments with helical anchors. This project will reduce the cost of offshore floating wind energy by uniting leading academic expertise and innovative industry partners to develop the knowledge and practical tools that will enable the deployment of helical anchors as a cheap and reliable anchoring system for floating wind. Helical anchors are seen as the most promising solution to anchor wind turbines, but their deployment has been limited by uncertainties a ....Securing Australian floating wind developments with helical anchors. This project will reduce the cost of offshore floating wind energy by uniting leading academic expertise and innovative industry partners to develop the knowledge and practical tools that will enable the deployment of helical anchors as a cheap and reliable anchoring system for floating wind. Helical anchors are seen as the most promising solution to anchor wind turbines, but their deployment has been limited by uncertainties associated with the torque and vertical force required for installation in complex seabeds, and their performance under environmental loading. The project will address these specific points through a combination of physical, numerical and analytical modelling, using data and design scenarios provided by industry.
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Improving road network operations under non-recurrent events. This project aims to develop an innovative approach for improving Road Network Operations (RNO) under non-recurrent events through analysis of big data and images. The outcomes of this project can not only improve the mobility of people, but also provide improved safety outcomes for all users of the transport network. It will help optimise traffic control strategies and traffic designs, reduce the maintenance cost for road infrastruc ....Improving road network operations under non-recurrent events. This project aims to develop an innovative approach for improving Road Network Operations (RNO) under non-recurrent events through analysis of big data and images. The outcomes of this project can not only improve the mobility of people, but also provide improved safety outcomes for all users of the transport network. It will help optimise traffic control strategies and traffic designs, reduce the maintenance cost for road infrastructure and improve quality of life.Read moreRead less
Assessment of structural integrity and deterioration of masonry walls. Brickwork for housing and medium-rise buildings is a traditional material, also much used for modern construction, with aesthetic appeal and modest cost. However, building regulators and others are increasingly concerned about evidence of slow building deterioration, particularly of older buildings. This increases public safety risks, even under normal conditions and more so under high winds or earthquake-induced ground-shaki ....Assessment of structural integrity and deterioration of masonry walls. Brickwork for housing and medium-rise buildings is a traditional material, also much used for modern construction, with aesthetic appeal and modest cost. However, building regulators and others are increasingly concerned about evidence of slow building deterioration, particularly of older buildings. This increases public safety risks, even under normal conditions and more so under high winds or earthquake-induced ground-shaking. This project will help address this issue. It will obtain unbiased evidence of typical masonry building deterioration. It will couple this with mathematical modelling and state-of-the-art non-destructive visual and dynamic techniques to develop tools for making fast, low-cost practical building risk assessments.Read moreRead less
In-situ Characterisation of Coal from Coal Seam Gas Developments. We aim to develop advanced methods for determination of coal properties required for optimising gas recovery, scheduling future developments and water management by Queensland Gas Company. We will characterise multiphase flow of gas and water in coal cores by Positron Emission Tomography and flooding experiments. Advancement in knowledge is achieved by using massive data from 4D-imaging to predict evolution of petrophysical proper ....In-situ Characterisation of Coal from Coal Seam Gas Developments. We aim to develop advanced methods for determination of coal properties required for optimising gas recovery, scheduling future developments and water management by Queensland Gas Company. We will characterise multiphase flow of gas and water in coal cores by Positron Emission Tomography and flooding experiments. Advancement in knowledge is achieved by using massive data from 4D-imaging to predict evolution of petrophysical properties at in situ condition in different types of coal. This will future proof Australia as the world’s largest exporter of natural gas and will provide significant benefit for the industry in satisfying domestic gas security, maintaining international commitment and addressing environmental concerns. Read moreRead less
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