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
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Efficient Pipeline Transport of Highly Concentrated Wastewater Sludge . This project aims to investigate the rheology and fluid mechanics of highly concentrated wastewater sludges and develop tools to support effective pipeline designs for wastewater treatment plants. The project expects to generate new knowledge about the complex flow of concentrated wastewater which will enable predictive models to support the design and optimization of pipeline transport systems. Expected outcomes of the proj ....Efficient Pipeline Transport of Highly Concentrated Wastewater Sludge . This project aims to investigate the rheology and fluid mechanics of highly concentrated wastewater sludges and develop tools to support effective pipeline designs for wastewater treatment plants. The project expects to generate new knowledge about the complex flow of concentrated wastewater which will enable predictive models to support the design and optimization of pipeline transport systems. Expected outcomes of the project include a new toolkit that will enable wastewater treatment plants to design and optimize both existing and future pipeline systems. This will support the Australian wastewater industry to plan for future growth, increase throughput and efficiency, reduce environmental pollutants, and capital and operating costs.Read moreRead less
Structural Reliability of Engineering Structures in Cyclonic Winds. This project aims to address the challenge of predicting the impact of extreme cyclonic winds on complex engineering structures. By applying advanced computational and experimental techniques the project expects to develop new insight into turbulent flows at a sub-cyclone scale and how these produce aerodynamic loads on closely spaced cylindrical structures and elements. The expected outcomes of this project include enhanced sim ....Structural Reliability of Engineering Structures in Cyclonic Winds. This project aims to address the challenge of predicting the impact of extreme cyclonic winds on complex engineering structures. By applying advanced computational and experimental techniques the project expects to develop new insight into turbulent flows at a sub-cyclone scale and how these produce aerodynamic loads on closely spaced cylindrical structures and elements. The expected outcomes of this project include enhanced simulation techniques leading to better understanding of structural vulnerability to cyclones. This should provide significant benefits, such as improved structural design and cyclone mitigation strategies applicable to both high-value engineering structures and vulnerable communities in cyclone regions.Read moreRead less
Quantitative structural health assessment of large membrane-like structures. This project aims to develop a new approach, based on remote sensing and computational modelling, to assess and manage the structural health of large floating covers used for odour control and biogas harvesting to prevent unexpected failures. The project has potential benefits for high-value-added manufacturing and maintenance of these floating covers by Australian industry.
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
Optimal maintenance planning for critical mining and energy infrastructure. This project aims to develop cutting-edge mathematical algorithms for optimising maintenance activities in the mining and energy sectors. Such maintenance activities are prone to budget and time overruns due to poor planning - the result of outdated, inefficient manual processes. The project is expected to result in new maintenance planning methods, underpinned by rigorous mathematical theory, for reducing manual interve ....Optimal maintenance planning for critical mining and energy infrastructure. This project aims to develop cutting-edge mathematical algorithms for optimising maintenance activities in the mining and energy sectors. Such maintenance activities are prone to budget and time overruns due to poor planning - the result of outdated, inefficient manual processes. The project is expected to result in new maintenance planning methods, underpinned by rigorous mathematical theory, for reducing manual intervention and optimising both short- and long-term maintenance based on real-time sensor data. These new methods will be powerful tools for tackling the complexity of large-scale, time-critical maintenance projects, driving productivity in the resources industry and fostering collaboration between mathematicians and engineers.Read moreRead less
Low emission iron and steelmaking using hydrogen to pre-reduce lump ore. This project aims to develop and apply a new route of lump iron ore pre-reduction with hydrogen or H2-enriched gases for ironmaking to minimise CO2 emission from steel production. The route will be built up on the base of H2 reduction kinetics of iron ore and with novel technologies such as CO2 recycle and H2-heating using hot blast, underpinning the hydrogen economy by addressing the environmental concerns in mineral and s ....Low emission iron and steelmaking using hydrogen to pre-reduce lump ore. This project aims to develop and apply a new route of lump iron ore pre-reduction with hydrogen or H2-enriched gases for ironmaking to minimise CO2 emission from steel production. The route will be built up on the base of H2 reduction kinetics of iron ore and with novel technologies such as CO2 recycle and H2-heating using hot blast, underpinning the hydrogen economy by addressing the environmental concerns in mineral and steel industries. It is not only significant for low-carbon steel production, but also for better fundamental understanding to develop the future zero-emission iron and steelmaking with hydrogen. The project will be very beneficent because it increases the use of lump iron ore and expends Australian export of iron ores.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less
Smart utilisation of cobaltite based electrodes on solid oxide fuel cells. This project aims to develop solid oxide fuel cell technologies with significantly simplified fabrication steps and at low cost. It aims to generate fundamental knowledge on the polarisation induced electrode/electrolyte interfaces under fuel cell operation conditions. The advanced fuel cell technologies will in turn substantially increase the energy conversion efficiency and provide significant benefit in the reduction o ....Smart utilisation of cobaltite based electrodes on solid oxide fuel cells. This project aims to develop solid oxide fuel cell technologies with significantly simplified fabrication steps and at low cost. It aims to generate fundamental knowledge on the polarisation induced electrode/electrolyte interfaces under fuel cell operation conditions. The advanced fuel cell technologies will in turn substantially increase the energy conversion efficiency and provide significant benefit in the reduction of greenhouse emission.Read moreRead less