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
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