Next-Generation Solvers for Complex Microwave Engineering Problems. This project aims to design a complementary physics-guided, data-driven method that can accurately solve complex microwave engineering problems in a timely manner. The primary bottleneck so far preventing that approach, which is the disparity between the trained theoretical model and reality, will be overcome using a multi-frequency complex-valued domain adaptation technique. The method will use deep neural networks to reliably ....Next-Generation Solvers for Complex Microwave Engineering Problems. This project aims to design a complementary physics-guided, data-driven method that can accurately solve complex microwave engineering problems in a timely manner. The primary bottleneck so far preventing that approach, which is the disparity between the trained theoretical model and reality, will be overcome using a multi-frequency complex-valued domain adaptation technique. The method will use deep neural networks to reliably learn the physical concepts of microwave engineering problems. This project will have significant economic and societal benefits, such as supporting the efficient design, installation and operation of communication systems, mining, infrastructure inspection, security, remote sensing, and microwave imaging. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101396
Funder
Australian Research Council
Funding Amount
$360,218.00
Summary
Designing Single-atom catalysts for Renewable Waste Conversion to Urea. This DECRA aims to realise the direct electrochemical conversion of waste resources using renewable energy to generate urea at ambient conditions. By designing impurity-tolerant single atom catalysts and unearthing their structure-activity relationships, the utilisation of flue gas and wastewater will be materialised. This will advance our understanding in the field as current energy conversion reactions require pure feedsto ....Designing Single-atom catalysts for Renewable Waste Conversion to Urea. This DECRA aims to realise the direct electrochemical conversion of waste resources using renewable energy to generate urea at ambient conditions. By designing impurity-tolerant single atom catalysts and unearthing their structure-activity relationships, the utilisation of flue gas and wastewater will be materialised. This will advance our understanding in the field as current energy conversion reactions require pure feedstocks. Expected outcomes from the program is envisioned to lead to deployment of scalable decentralised modes of green urea production (substituting imports), and the knowledge transferrable to other areas of Australia’s emerging hydrogen economy, extending the scope of renewable Power-to-X to realise a circular economy.Read moreRead less
Towards highly-efficient hydrogen gas turbines. The increasing interest in green hydrogen has led to a need for research and development in combustion systems that can accommodate hydrogen. One promising technology is low-emission gas turbines, which is a key player in the electricity market. However, hydrogen gas turbines are susceptible to a phenomenon called thermoacoustic instability, causing loud noise and can damage equipment. This project represents the first comprehensive study of the ef ....Towards highly-efficient hydrogen gas turbines. The increasing interest in green hydrogen has led to a need for research and development in combustion systems that can accommodate hydrogen. One promising technology is low-emission gas turbines, which is a key player in the electricity market. However, hydrogen gas turbines are susceptible to a phenomenon called thermoacoustic instability, causing loud noise and can damage equipment. This project represents the first comprehensive study of the effects of hydrogen fuel on thermoacoustic instability under conditions relevant to gas turbines. By examining low-order models, commonly used for designing gas turbines, this project can significantly advance the field and facilitate the adoption of green hydrogen as a fuel source.Read moreRead less