Elucidating the mechanics of facet dislocation and fracture in the neck. This project aims to address shortcomings in understanding the mechanics of neck trauma. Understanding the mechanical factors leading to cervical facet dislocation and fracture is necessary to improve injury prevention strategies and their assessment. This project expects to generate new knowledge in the area of spinal injury biomechanics, developing and using new experimental techniques. The project expects to provide know ....Elucidating the mechanics of facet dislocation and fracture in the neck. This project aims to address shortcomings in understanding the mechanics of neck trauma. Understanding the mechanical factors leading to cervical facet dislocation and fracture is necessary to improve injury prevention strategies and their assessment. This project expects to generate new knowledge in the area of spinal injury biomechanics, developing and using new experimental techniques. The project expects to provide knowledge necessary to improve crash test dummy design, associated injury criteria, and computational models, which provide the potential for improved injury prevention measures and methods for assessing existing and new technologies. The anticipated benefits of this project will be significant in reducing the personal and economic burden of spinal injuries.Read moreRead less
Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected out ....Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected outcomes of this project enhance the capacity to conduct the operational monitoring and data interpretation to deliver the best life cycle performance of infrastructure. This project should provide significant benefits to Australia in infrastructure asset management by reducing the interruption of infrastructure operations.Read moreRead less
Crashworthiness topology optimisation for light-weight battery compartments. This project uses computational modelling and optimisation methods to the design of battery compartments for electric vehicles. As the use of electric vehicles becomes more extensive, awareness of the consequences of catastrophic failure of high energy battery in a crash has increased. This project will develop novel design methodologies, using multi-disciplinary techniques for battery compartment structure. The methodo ....Crashworthiness topology optimisation for light-weight battery compartments. This project uses computational modelling and optimisation methods to the design of battery compartments for electric vehicles. As the use of electric vehicles becomes more extensive, awareness of the consequences of catastrophic failure of high energy battery in a crash has increased. This project will develop novel design methodologies, using multi-disciplinary techniques for battery compartment structure. The methodology will expand conventional crashworthiness design to the coupled mechanical-electrochemical-thermal problems. The proposed crashworthiness optimisation of battery compartment structure will enhance safety and reliability of electric vehicles, potentially benefiting consumers and manufacturers.Read moreRead less
Robustness, resilience and security of networked dynamic systems. This project will develop advanced digital control techniques to address security, resilience and robustness in complex networks and deliver fundamental advances in the technology for secure and reliable networks. The project will advance the theory on consensus of networked multi-agent systems to facilitate the fast adoption of the internet of things and the continuous growth of cyber-physical systems These systems in many cases ....Robustness, resilience and security of networked dynamic systems. This project will develop advanced digital control techniques to address security, resilience and robustness in complex networks and deliver fundamental advances in the technology for secure and reliable networks. The project will advance the theory on consensus of networked multi-agent systems to facilitate the fast adoption of the internet of things and the continuous growth of cyber-physical systems These systems in many cases work with high efficiency, stability, and low communication overheads. However, there are cases where disturbance amplification and cascading failures can arise from relatively small unforeseen events. The theoretical work will be complemented by detailed nonlinear networked simulations, using intelligent vehicle systems as a case study.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101181
Funder
Australian Research Council
Funding Amount
$403,775.00
Summary
Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multipl ....Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.Read moreRead less