Remote sensing to improve structural efficiency of high-speed catamarans. This project aims to develop a monitoring system to remotely measure ship motions, loads and ride control activity under commercial operations. Data will be analysed using advanced statistical methods to inform evidence-based design to improve both structural efficiency and passenger comfort. The research will impact on design rules used worldwide, reducing weight and increasing payload and transport efficiency for this cl ....Remote sensing to improve structural efficiency of high-speed catamarans. This project aims to develop a monitoring system to remotely measure ship motions, loads and ride control activity under commercial operations. Data will be analysed using advanced statistical methods to inform evidence-based design to improve both structural efficiency and passenger comfort. The research will impact on design rules used worldwide, reducing weight and increasing payload and transport efficiency for this class of vessel. A "Smart” semi-autonomous interface will be developed to provide on-board seakeeping guidance to the ship captain. This technology will have significant benefits such as increased ship safety, vessel longevity and improving passenger comfort for all types of vessels worldwide including high-speed catamarans.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101864
Funder
Australian Research Council
Funding Amount
$442,500.00
Summary
Unlocking Urban Airspace for Drone Transport. This project aims to accurately quantify the mid-air collision risk associated with low-altitude unmanned operations in urban airspace through the creation of new data-driven collision risk modelling techniques. Without such techniques, drone operations remain suppressed so their true potential cannot be realised. The collision risk models address this by providing the key missing knowledge that can underpin/enable vital unmanned traffic management ....Unlocking Urban Airspace for Drone Transport. This project aims to accurately quantify the mid-air collision risk associated with low-altitude unmanned operations in urban airspace through the creation of new data-driven collision risk modelling techniques. Without such techniques, drone operations remain suppressed so their true potential cannot be realised. The collision risk models address this by providing the key missing knowledge that can underpin/enable vital unmanned traffic management applications, including airspace design and the development of separation standards. This can ultimately enable greater access to urban airspace without compromising air safety such that we unlock the commercial and societal benefits of drone use and help modernise urban air transportation.
Read moreRead less