Discovery Early Career Researcher Award - Grant ID: DE210100273
Funder
Australian Research Council
Funding Amount
$407,679.00
Summary
Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expe ....Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expected outcomes include a new supercomputing method for train-track dynamics and derailment research and a science-based technique to assess track buckling safety. This project should provide significant benefits to the rail industry including enhanced rail safety, lower maintenance costs and improved transport efficiency.Read moreRead less
Development of Canonical Mist Filter Models. Over one million tonnes of oil (mist) is wasted every year – and emitted to the atmosphere through inefficient filtration. Over 50 per cent of energy usage in most process industries is for filtration and separation processes, yet mist filters and separators are largely designed by trial and error, resulting in sub-optimal, inefficient designs. Recent advances by the research team have, only now, made it possible to develop accurate models for such sy ....Development of Canonical Mist Filter Models. Over one million tonnes of oil (mist) is wasted every year – and emitted to the atmosphere through inefficient filtration. Over 50 per cent of energy usage in most process industries is for filtration and separation processes, yet mist filters and separators are largely designed by trial and error, resulting in sub-optimal, inefficient designs. Recent advances by the research team have, only now, made it possible to develop accurate models for such systems. This work intends to be the first to develop accurate, broadly applicable models for all processes in mist filters, thereby providing immense process efficiency benefits, together with improved worker and environmental protection, and less wastage of dwindling oil resources.Read moreRead less
Towards autonomous structural safety prognostics: integrating in-situ imaging and predictive modelling. This project aims to advance a scientific basis for autonomous safety prognostics by developing predictive models and in-situ damage imaging principles. Development of this new health prognostic approach will overcome the significant challenge of safety assurance of composite structures in the presence of in-service damage, which is largely hidden.
Optimising gaseous and particulate emissions from diesel engines. About $3.7 billion is spent annually in Australia on respiratory diseases. Diesel vehicle emissions of nano- and ultra-fine urban air particulate pollution are a significant factor in this disease. This project will directly addresses this problem by developing a technology to monitor and reduce diesel particulate emissions.
Nonlinear frequency mixing methods for materials and damage evaluation. This project aims to investigate new approaches for frequency mixing in nonlinear ultrasonics, and to demonstrate their potential for the non-destructive evaluation of material degradation and early damage detection. The anticipated outcomes will be increased detection sensitivity relative to current inspection techniques and an enhanced capability for quantifying the damage. This will provide the basis for more cost efficie ....Nonlinear frequency mixing methods for materials and damage evaluation. This project aims to investigate new approaches for frequency mixing in nonlinear ultrasonics, and to demonstrate their potential for the non-destructive evaluation of material degradation and early damage detection. The anticipated outcomes will be increased detection sensitivity relative to current inspection techniques and an enhanced capability for quantifying the damage. This will provide the basis for more cost efficient safety management of high-value assets and infrastructure, and for enhancing Australia’s competitiveness in advanced manufacturing.Read moreRead less