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Socio-Economic Objective : Wind Energy
Research Topic : nested case control study
Australian State/Territory : VIC
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  • Funded Activity

    Linkage Projects - Grant ID: LP110200364

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Enabling ambient intelligence for manufacturing processes through distributed camera networks. This project will develop methods to optimise and schedule networks of smart and traditional cameras in a manufacturing environment, enabling knowledge capture, manage performance and identify causes of quality degradation. This research will assist Australian manufacturers to stay competitive in the dynamic global market.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210100990

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Machine Learning and Shape Optimisation of Fluid-Structure Interactions. This project aims to address vibrations of solid structures by utilising a combination of advanced experimental and computational methods. This project expects to generate new knowledge in the area of flow-induced vibrations utilising the new techniques of machine learning and evolutionary shape optimisation. Expected outcomes of this project include greatly accelerated discovery of mechanisms leading to structural vibratio .... Machine Learning and Shape Optimisation of Fluid-Structure Interactions. This project aims to address vibrations of solid structures by utilising a combination of advanced experimental and computational methods. This project expects to generate new knowledge in the area of flow-induced vibrations utilising the new techniques of machine learning and evolutionary shape optimisation. Expected outcomes of this project include greatly accelerated discovery of mechanisms leading to structural vibrations and optimising structure geometries to either enhance or suppress the vibrations. This should provide significant benefits, such as the design strategies for improved energy harvesters, such as current oscillators, or more stable structures, such as platforms for offshore wind turbines.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200101650

    Funder
    Australian Research Council
    Funding Amount
    $412,700.00
    Summary
    Intelligent active control of flow-induced vibration. This project aims to develop advanced and effective control methods using an innovative interdisciplinary approach for flow-induced vibration for a wide range of generic elements of engineering structures. This project expects to generate new scientific knowledge of fluid-structure interaction that is essential for the prediction and control of flow-induced vibration. The expected outcomes of this project are artificial intelligence based act .... Intelligent active control of flow-induced vibration. This project aims to develop advanced and effective control methods using an innovative interdisciplinary approach for flow-induced vibration for a wide range of generic elements of engineering structures. This project expects to generate new scientific knowledge of fluid-structure interaction that is essential for the prediction and control of flow-induced vibration. The expected outcomes of this project are artificial intelligence based active control methods for flow-induced vibration. Ultimately, this project should provide significant benefits, such as advances in scientific knowledge and improved technologies for the areas of energy, transport, buildings and infrastructure.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100740

    Funder
    Australian Research Council
    Funding Amount
    $198,000.00
    Summary
    A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced n .... A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced noise and other interference noise are further filtered out by a specific adaptive noise cancellation algorithm based on the spherical and differential microphone array structure. With the proposed system, the measurement configuration size is expected to be reduced from the current few metres to less than 10 centimetres, and with better accuracy.
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    Funded Activity

    Discovery Projects - Grant ID: DP180100898

    Funder
    Australian Research Council
    Funding Amount
    $403,306.00
    Summary
    High-fidelity simulations for new models that reduce noise pollution. This project aims to develop a method for accurate and affordable prediction and mitigation of flow-induced noise. The innovative approach, based on recent developments in simulation and data-driven modelling, expects to reduce environmental noise pollution, improve public health and ease the impact of urbanisation. To date methodological limitations have hampered our ability to predict noise reliably and hence control it. Thi .... High-fidelity simulations for new models that reduce noise pollution. This project aims to develop a method for accurate and affordable prediction and mitigation of flow-induced noise. The innovative approach, based on recent developments in simulation and data-driven modelling, expects to reduce environmental noise pollution, improve public health and ease the impact of urbanisation. To date methodological limitations have hampered our ability to predict noise reliably and hence control it. This project, exploiting proven high-fidelity simulation and machine-learning techniques to overcome limitations to produce the scientific knowledge required for practical noise mitigation. Benefits include quieter aerospace, marine and renewable energy technologies, creating more pleasant communities.
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