Development of hierarchical carbon nanotube-glass fibre composites. Development of hierarchical carbon nanotube-glass fibre composites. This project aims to develop a new generation of hierarchical carbon nanotube-glass fibre reinforced composites, using a novel synthesis method that grafts carbon nanotubes (CNTs) onto glass fibre and glass fabric. These hierarchical nano- and micro-fibre composites will have improved in-plane mechanical properties, enhanced fracture toughness and higher electri ....Development of hierarchical carbon nanotube-glass fibre composites. Development of hierarchical carbon nanotube-glass fibre composites. This project aims to develop a new generation of hierarchical carbon nanotube-glass fibre reinforced composites, using a novel synthesis method that grafts carbon nanotubes (CNTs) onto glass fibre and glass fabric. These hierarchical nano- and micro-fibre composites will have improved in-plane mechanical properties, enhanced fracture toughness and higher electric conductivity. This project will use a comprehensive experimental and theoretical study to develop design tools for producing this new generation of composites. The anticipated outcome is lighter and stronger glass fibre composite structures, such as wind turbines in the renewable wind energy industry and boats in the marine industry.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.
Read moreRead less