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Field of Research : Civil Engineering
Research Topic : Commercial security services
Australian State/Territory : ACT
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP170100922

    Funder
    Australian Research Council
    Funding Amount
    $771,000.00
    Summary
    Water availability and demand: better forecasts, better management. This project aims to improve Australia’s capability in the provision and use of water forecasts for managing water resources. The current water forecasts are not fully utilised by water agencies as they are not sufficiently comprehensive and advanced. This project expects to achieve a step change in the uptake and utility of hydro-climate forecasts through an extensive partnership of leading researchers and operational agencies .... Water availability and demand: better forecasts, better management. This project aims to improve Australia’s capability in the provision and use of water forecasts for managing water resources. The current water forecasts are not fully utilised by water agencies as they are not sufficiently comprehensive and advanced. This project expects to achieve a step change in the uptake and utility of hydro-climate forecasts through an extensive partnership of leading researchers and operational agencies of hydro-climate forecasting, with federal, state and regional water agencies.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100217

    Funder
    Australian Research Council
    Funding Amount
    $248,000.00
    Summary
    Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi .... Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210200765

    Funder
    Australian Research Council
    Funding Amount
    $372,893.00
    Summary
    A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural netw .... A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural networks trained on lab-scale and synthetic data to field implementation. The outcome is a machine learning framework to optimise biogas harvesting and renewable energy generation, and to avoid structural failure, that is capable of continuous improvement to take into account improved data and/or modelling capabilities.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100909

    Funder
    Australian Research Council
    Funding Amount
    $710,000.00
    Summary
    Smart management of disinfectant in chloraminated water-supply systems. Smart management of disinfectant in chloraminated water-supply systems. This project aims to develop an adaptive, real-time control system for managing disinfectant residuals in chloraminated water supply systems. While chloramine delivers microbiologically safe drinking water in warmer climates and in long distribution systems, it is largely unpredictable, costs water utilities millions of dollars annually, and has uncertai .... Smart management of disinfectant in chloraminated water-supply systems. Smart management of disinfectant in chloraminated water-supply systems. This project aims to develop an adaptive, real-time control system for managing disinfectant residuals in chloraminated water supply systems. While chloramine delivers microbiologically safe drinking water in warmer climates and in long distribution systems, it is largely unpredictable, costs water utilities millions of dollars annually, and has uncertain benefits. This project’s control system will be guided by quantitative models formulated from multi-pronged, fundamental experiments. The project will quantify microbial chloramine decay and determine mechanisms to increase predictability. The project will develop and demonstrate a real-time control technology which delivered microbiologically safe, cost-efficient drinking water to people in warmer climates, despite warming climate and increasing population.
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