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Field of Research : Environmental Engineering Modelling
Australian State/Territory : NSW
Australian State/Territory : SA
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  • Funded Activity

    Linkage Projects - Grant ID: LP100200665

    Funder
    Australian Research Council
    Funding Amount
    $185,000.00
    Summary
    An integrated modelling approach for efficient management of irrigated landscapes. Northern Victoria's irrigators use a substantial portion of water from the Murray-Darling Basin, which is under mounting pressure to satisfy competing economic, social and environmental needs for water in the face of climate change. Up to 20 per cent of this water may be on-farm surface runoff and deep percolation, with poorly known spatial distributions. This project will provide reliable temporally and spatially .... An integrated modelling approach for efficient management of irrigated landscapes. Northern Victoria's irrigators use a substantial portion of water from the Murray-Darling Basin, which is under mounting pressure to satisfy competing economic, social and environmental needs for water in the face of climate change. Up to 20 per cent of this water may be on-farm surface runoff and deep percolation, with poorly known spatial distributions. This project will provide reliable temporally and spatially distributed information on surface runoff and deep percolation for Northern Victoria irrigation regions. This will inform decisions which improve water use efficiency, agricultural productivity and environmental values through optimisation of irrigation infrastructure and by better management of groundwater resources and salinity.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180100890

    Funder
    Australian Research Council
    Funding Amount
    $523,756.00
    Summary
    Multiscale physics for enhanced oil recovery. The project aims to develop a multiscale mathematical and laboratory modelling methodology for combined enhanced oil recovery (EOR) and CO2 storage, and synthesise the technology for Santos’s Mulberry oilfield as a test case. The multidisciplinary team will develop advanced reservoir- and laboratory-scale mathematical models and novel laboratory methods to enhance the reliability of modern EOR and CO2 storage and increase its uptake by companies in A .... Multiscale physics for enhanced oil recovery. The project aims to develop a multiscale mathematical and laboratory modelling methodology for combined enhanced oil recovery (EOR) and CO2 storage, and synthesise the technology for Santos’s Mulberry oilfield as a test case. The multidisciplinary team will develop advanced reservoir- and laboratory-scale mathematical models and novel laboratory methods to enhance the reliability of modern EOR and CO2 storage and increase its uptake by companies in Australia and globally. The expected outcomes are a pioneering methodology with environmental benefits without additional drilling and reduction of greenhouse effect, and economic benefit to the Australian oil industry through increases in productivity.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210300584

    Funder
    Australian Research Council
    Funding Amount
    $875,432.00
    Summary
    Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa .... Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.
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    Funded Activity

    Discovery Projects - Grant ID: DP110105408

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Robust streamflow predictions by improving the identification of hydrological model structure. This project aims to provide Australian environmental agencies, design engineers and policy-makers with robust methods that better utilise observed environmental data and process understanding to produce hydrological models with stronger scientific basis and improved operational predictive ability in gauged and ungauged catchments.
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    Funded Activity

    Linkage Projects - Grant ID: LP160101040

    Funder
    Australian Research Council
    Funding Amount
    $440,000.00
    Summary
    Network-wide sewer odour and corrosion management by model predictive control. Network-wide sewer odour and corrosion management by model predictive control. This project aims to develop and demonstrate, through real-life field studies, a model predictive control approach that achieves cost-effective network-wide mitigation of hydrogen sulphide. The lack of suitable methodologies to support the control designs of chemical dosing units and sewage pumping stations makes network-wide sewer corrosio .... Network-wide sewer odour and corrosion management by model predictive control. Network-wide sewer odour and corrosion management by model predictive control. This project aims to develop and demonstrate, through real-life field studies, a model predictive control approach that achieves cost-effective network-wide mitigation of hydrogen sulphide. The lack of suitable methodologies to support the control designs of chemical dosing units and sewage pumping stations makes network-wide sewer corrosion and odour management a problem. Innovative control methodology will simultaneously manipulate chemical dosing unit(s) and selected sewage pumping station(s), based on real-time prediction of sewage flows and characteristics both at sources and across the network, to ensure optimal delivery of dosed chemicals to mitigate hydrogen sulphide.
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