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Australian State/Territory : QLD
Scheme : Linkage Projects
Field of Research : Civil Engineering
Australian State/Territory : SA
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  • Funded Activity

    Linkage Projects - Grant ID: LP160100298

    Funder
    Australian Research Council
    Funding Amount
    $350,000.00
    Summary
    Reinforced crumbed rubber concrete for residential construction. Reinforced crumbed rubber concrete for residential construction. This project aims to use crumb rubber from used tyres to replace natural sand aggregate in concrete used in housing construction. Globally, very few of the millions of tyres discarded annually are recycled, while natural sand used in concrete is being depleted. This project intends to provide the tyre industry with a viable market for end of life tyres, and the premix .... Reinforced crumbed rubber concrete for residential construction. Reinforced crumbed rubber concrete for residential construction. This project aims to use crumb rubber from used tyres to replace natural sand aggregate in concrete used in housing construction. Globally, very few of the millions of tyres discarded annually are recycled, while natural sand used in concrete is being depleted. This project intends to provide the tyre industry with a viable market for end of life tyres, and the premix concrete industry with a “green” product for the residential construction market. Expected benefits include the increased use of a waste resource (used tyres), reduced use of a scarce natural resource (sand), and the development of an economic but green alternative concrete option for residential builders and owners.
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    Funded Activity

    Linkage Projects - Grant ID: LP130100033

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    On-line monitoring of cyanobacteria to predict coagulant doses and powdered activated carbon application in water treatment. Cyanobacteria, more commonly known as blue-green algae, can impact water quality by releasing toxins that can be harmful to human health and imparting unpleasant taste and odours to the water. This project will support the water industry in managing these risks by providing a rapid, on-line tool to assist in their removal during water treatment.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180101178

    Funder
    Australian Research Council
    Funding Amount
    $422,000.00
    Summary
    Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental .... Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental protection against PFASs and establishment of new approaches for predicting functional containment lifetimes of liner systems. These outcomes are expected to benefit the waste and remediation industries by influencing next-generation design regulations to ensure long-term environmental protection from PFAS.
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    Funded Activity

    Linkage Projects - Grant ID: LP150101206

    Funder
    Australian Research Council
    Funding Amount
    $185,000.00
    Summary
    Optimization of internal pressure for designing industrial buildings. The project seeks to understand the internal pressure in a building during windstorms, to improve safety and performance. The internal pressure in a building is dependent on its volume and flexibility and the sizes of openings in the building envelope, and is a critical loading parameter in building design. Windstorm damage investigations have shown that incorrect internal pressures are frequently used in building design, lead .... Optimization of internal pressure for designing industrial buildings. The project seeks to understand the internal pressure in a building during windstorms, to improve safety and performance. The internal pressure in a building is dependent on its volume and flexibility and the sizes of openings in the building envelope, and is a critical loading parameter in building design. Windstorm damage investigations have shown that incorrect internal pressures are frequently used in building design, leading to damage. This project aims to study the internal pressures generated in buildings with a range of volumes and openings in the envelope. A combination of model-scale and full-scale tests and theoretical analysis are planned to determine critical parameters for highly turbulent air-flow though openings. Results will inform the revision of design data in codes and of guidelines for consistent, optimal design of buildings.
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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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