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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Harnessing the Power of Wind: Revolutionising Wind Farm Optimisation. This project aims to develop a rigorous, efficient and accurate framework for optimisation of control policies for complete wind farms. It expects to generate new knowledge in data-driven physics informed transient aerodynamic and structural modelling of entire wind farms, generation of low order yet sufficiently accurate models using machine learning, and game-theoretic and model predictive control techniques for operation of ....Harnessing the Power of Wind: Revolutionising Wind Farm Optimisation. This project aims to develop a rigorous, efficient and accurate framework for optimisation of control policies for complete wind farms. It expects to generate new knowledge in data-driven physics informed transient aerodynamic and structural modelling of entire wind farms, generation of low order yet sufficiently accurate models using machine learning, and game-theoretic and model predictive control techniques for operation of an entire wind farm. Expected outcomes are engineering tools to tackle wind farm inefficiencies totalling $700m/year in Australia alone, contributing to energy stability, security and lowered emissions aligned to the National Science and Research Priority ‘Energy’.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