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  • Funded Activity

    Australian Laureate Fellowships - Grant ID: FL0992039

    Funder
    Australian Research Council
    Funding Amount
    $2,860,400.00
    Summary
    Failure Analysis of Geotechnical Infrastructure. With a forecast public and private sector investment of around 200 billion dollars in Australia's infrastructure over the next five years, there is an unprecedented need to design and build this infrastructure as cheaply and safely as possible. Given the magnitude of the investment involved, even small percentage savings resulting from advanced research will lead to large returns in absolute dollar terms. This project will provide engineers with .... Failure Analysis of Geotechnical Infrastructure. With a forecast public and private sector investment of around 200 billion dollars in Australia's infrastructure over the next five years, there is an unprecedented need to design and build this infrastructure as cheaply and safely as possible. Given the magnitude of the investment involved, even small percentage savings resulting from advanced research will lead to large returns in absolute dollar terms. This project will provide engineers with new and better tools for predicting the safety of geostructures such as roads, railways, tunnels, dams, and port facilities. Moreover, commercialisation of the corresponding software worldwide will provide knowledge transfer from the university sector to industry and generate technology exports.
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    Funded Activity

    Federation Fellowships - Grant ID: FF0455859

    Funder
    Australian Research Council
    Funding Amount
    $1,519,710.00
    Summary
    Geostructural stability analysis with adaptive mesh refinement. AIMS: To conduct fundamental research on new methods for predicting the stability of geostructures such as tunnels, dams, highways and foundations. To translate this research into innovative computer software and better civil design procedures. SIGNIFICANCE: Billions of dollars are spent annually on the construction of Australian infrastructure. This project will lead to new algorithms and computer software for designing this inf .... Geostructural stability analysis with adaptive mesh refinement. AIMS: To conduct fundamental research on new methods for predicting the stability of geostructures such as tunnels, dams, highways and foundations. To translate this research into innovative computer software and better civil design procedures. SIGNIFICANCE: Billions of dollars are spent annually on the construction of Australian infrastructure. This project will lead to new algorithms and computer software for designing this infrastructure. Particular emphasis will be placed on the development of adaptive methods for three-dimensional problems involving complex ground profiles, where current procedures are inadequate. EXPECTED OUTCOMES: Cutting-edge algorithms and computer software that will lead to cheaper and safer design of civil infrastructure. This will be accompanied by top-level refereed publications and a book.
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    Funded Activity

    Discovery Projects - Grant ID: DP0879979

    Funder
    Australian Research Council
    Funding Amount
    $323,890.00
    Summary
    Design in Context: Augmented Reality Technology to Improve the Quality and Performance of Architecture. This project will develop tools and knowledge to assess and improve the environmental performance and visual impact of design proposals prior to construction. The design simulation technology proposed here will allow stakeholders to concurrently test socio-cultural and functional performance over time, will allow more informed decision making and make a significant contribution to the social, .... Design in Context: Augmented Reality Technology to Improve the Quality and Performance of Architecture. This project will develop tools and knowledge to assess and improve the environmental performance and visual impact of design proposals prior to construction. The design simulation technology proposed here will allow stakeholders to concurrently test socio-cultural and functional performance over time, will allow more informed decision making and make a significant contribution to the social, cultural and economic life of Australia. The augmented reality technology to be developed in this project also has significant potential for applications in other domains and industries such as landscape and parks management.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562455

    Funder
    Australian Research Council
    Funding Amount
    $144,888.00
    Summary
    Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. Current risk assessment paradigms are not suited to the control of catastrophic events such as terrorism. An advanced approach to risk assessment will be developed in this project for rare high impact events such as bomb blasts, where critical infrastructure is threatened. A new software platform based on scripted agent modelling will be constructed that will allow for state .... Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. Current risk assessment paradigms are not suited to the control of catastrophic events such as terrorism. An advanced approach to risk assessment will be developed in this project for rare high impact events such as bomb blasts, where critical infrastructure is threatened. A new software platform based on scripted agent modelling will be constructed that will allow for state of the art models to be used as agents providing a dynamic risk evaluation and necessary information for actions to infrastructure owners and emergency responders as a threat develops. Both the developed scripted agent and the risk assessment technologies can be applied to other technologies and complex risks, such as waste disposal and biotechnology.
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    Funded Activity

    Linkage Projects - Grant ID: LP0882474

    Funder
    Australian Research Council
    Funding Amount
    $153,762.00
    Summary
    Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. The project will develop a distributed risk network capable of real time assessment of multiple threats to critical infrastructure, which will guide decision making on the appropriate response as the nature of the threat changes. This will assist all stakeholders and allow an integrated response across industry and government agencies. The developed technology will find read .... Development of a Multi Threat Risk Assessment Model for Critical Infrastructure Using Scripted Agent Computer Technology. The project will develop a distributed risk network capable of real time assessment of multiple threats to critical infrastructure, which will guide decision making on the appropriate response as the nature of the threat changes. This will assist all stakeholders and allow an integrated response across industry and government agencies. The developed technology will find ready application in other areas where integration of science and technology is required to solve complex problems. For example, risk network technology has application to natural hazards, waste disposal and financial markets while the scripted agent has application to communication technologies and sensor networks.
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    Funded Activity

    Linkage Projects - Grant ID: LP0883807

    Funder
    Australian Research Council
    Funding Amount
    $423,585.00
    Summary
    Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will .... Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will be verified using available bridge datasets of QDMR and GCCC. The methodology is applicable to other bridge authorities throughout Australia and internationally to maintain ageing bridge stock.
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