Response of Vertical Drains in Soft Subgrade under Cyclic Rail Loading. Soft formations (subgrade) can become unstable when subjected to heavy and repeated (cyclic) train loading. This project aims to investigate the cause and mechanisms of undrained instability of soft subgrade soil beneath rail embankments, and to assess the effectiveness of prefabricated vertical drains (PVDs) in stabilising such soils. The role of PVDs to enhance track performance will be quantified via rigorous mathematical ....Response of Vertical Drains in Soft Subgrade under Cyclic Rail Loading. Soft formations (subgrade) can become unstable when subjected to heavy and repeated (cyclic) train loading. This project aims to investigate the cause and mechanisms of undrained instability of soft subgrade soil beneath rail embankments, and to assess the effectiveness of prefabricated vertical drains (PVDs) in stabilising such soils. The role of PVDs to enhance track performance will be quantified via rigorous mathematical techniques complementing a computer-based numerical model, which can be validated by laboratory and field data. It will deliver tangible outcomes for accurately predicting the long-term settlements in soft foundations over prolonged train loading while extending the life span of modern railroad infrastructure.Read moreRead less
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
Understanding and improving sustained attention under vigilance conditions. This project aims to address a major global challenge caused by technological advances: human operators have to monitor computer-control (e.g., in autonomous vehicles, rail and airtraffic control) but sustaining attention is very difficult under these conditions. Developing innovative behavioural and neural methods, this internationally collaborative project bridges basic and applied science to understand lapses of atten ....Understanding and improving sustained attention under vigilance conditions. This project aims to address a major global challenge caused by technological advances: human operators have to monitor computer-control (e.g., in autonomous vehicles, rail and airtraffic control) but sustaining attention is very difficult under these conditions. Developing innovative behavioural and neural methods, this internationally collaborative project bridges basic and applied science to understand lapses of attention under monitoring conditions. It creates a novel intervention, based on brain activity patterns, to improve performance. Outcomes will increase our neural understanding of attention and lay a foundation for a novel system to detect lapses of attention in high-risk environments, preventing errors before they occur.Read moreRead less