Impact of roughness on adverse pressure gradient turbulent boundary layers. This project aims to develop a novel technique for measuring time-resolved fluid velocity vector fields in high-speed flows to investigate rough wall turbulence in adverse pressure gradient environments in unprecedented detail. By using this innovative instrument to study these widespread but poorly understood turbulent flows in power generation and transport, the project seeks to generate new knowledge. Expected outcome ....Impact of roughness on adverse pressure gradient turbulent boundary layers. This project aims to develop a novel technique for measuring time-resolved fluid velocity vector fields in high-speed flows to investigate rough wall turbulence in adverse pressure gradient environments in unprecedented detail. By using this innovative instrument to study these widespread but poorly understood turbulent flows in power generation and transport, the project seeks to generate new knowledge. Expected outcomes include the development of a new instrument and fundamental knowledge leading to improved designs with higher efficiencies in power generation and transport, resulting in significant benefits such as increased energy security, reduced greenhouse gas emissions, and improved quality of life for individuals and society.Read moreRead less
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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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.Read moreRead less
Turbulent wall-bounded flow in adverse pressure gradient environments. This research will create additional research capacity in turbulence control and drag reduction. It will have direct benefits to the Australian economy via the transport industry by reducing the adverse impact of the carbon tax and rising fuel prices on long-haul air, water and road transport, on which Australia is disproportionately reliant.
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.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100067
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Wind profiler network for planetary boundary layer research. Understanding winds in the lower atmosphere is of great fundamental and practical importance. This new wind monitoring network will help Australian scientists to better predict propagation of tropical cyclones, to improve the efficiency of wind energy production, and to better understand atmosphere-ocean interactions affecting weather and climate.