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Socio-Economic Objective : Wind Energy
Status : Active
Research Topic : Flight dynamics
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Dynamics, Vibration and Vibration Control (3)
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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

    Linkage Projects - Grant ID: LP230100456

    Funder
    Australian Research Council
    Funding Amount
    $371,499.00
    Summary
    Dynamic model assisted fault diagnostics of wind turbine gearbox. This project aims to develop novel condition monitoring methodologies for the gearbox of large horizontal-axis wind turbines which are widely installed in wind farms for generating renewable energy. This project expects to generate a new diagnostic framework by integrating dynamic model assisted simulations and digital twin-based approaches. Expected outcomes of this project include new vibration-based methods for fault diagnostic .... Dynamic model assisted fault diagnostics of wind turbine gearbox. This project aims to develop novel condition monitoring methodologies for the gearbox of large horizontal-axis wind turbines which are widely installed in wind farms for generating renewable energy. This project expects to generate a new diagnostic framework by integrating dynamic model assisted simulations and digital twin-based approaches. Expected outcomes of this project include new vibration-based methods for fault diagnostics and predictions of the remaining useful life of turbine gearboxes. This should provide significant benefits to the Australian Wind Industry by ensuring reliable operation of wind turbines, reducing turbine downtime and reducing operation and maintenance costs; ultimately lowering the cost of energy from wind.
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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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    Active Funded Activity

    Discovery Projects - Grant ID: DP190103231

    Funder
    Australian Research Council
    Funding Amount
    $309,934.00
    Summary
    Cepstral methods of operational modal analysis to separate multiple sources. This project aims to develop new methods of operational modal analysis in situations with multiple complex sources, such as rotating machines. The project will obtain scaled mode shapes as well as separated scaled sources. One of the main applications will be to improve the prognostics of machines by having separated scaled estimates of the forcing functions to make it easier to find fault parameters which trend monoton .... Cepstral methods of operational modal analysis to separate multiple sources. This project aims to develop new methods of operational modal analysis in situations with multiple complex sources, such as rotating machines. The project will obtain scaled mode shapes as well as separated scaled sources. One of the main applications will be to improve the prognostics of machines by having separated scaled estimates of the forcing functions to make it easier to find fault parameters which trend monotonically towards failure, and thus greatly improve the estimates of remaining useful equipment life. An additional benefit of the application will be the ability to predict overall noise radiation from a machine or object if both the sources and modal models are scaled.
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    Showing 1-4 of 4 Funded Activites

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