Co-design and dynamic mission optimisation of hypersonic flight vehicles. This project aims to deliver fundamental knowledge by integrating the modelling and control with the design of next generation hypersonic platforms. In an era where Australia's national security reliance on geographic isolation and support from allied forces are being challenged, the research outcomes of this project will play an important role in understanding the capabilities of hypersonic systems. The project will also ....Co-design and dynamic mission optimisation of hypersonic flight vehicles. This project aims to deliver fundamental knowledge by integrating the modelling and control with the design of next generation hypersonic platforms. In an era where Australia's national security reliance on geographic isolation and support from allied forces are being challenged, the research outcomes of this project will play an important role in understanding the capabilities of hypersonic systems. The project will also have significant spillover benefits into other complex system domains, where computational tools can be used to aid in design leading to high embedded-IP products for Australian industry. Furthermore, the proposal encompasses a strong research training aspect, with graduates exposed to leading edge industry and academia.Read moreRead less
Special Research Initiatives - Grant ID: SR180100023
Funder
Australian Research Council
Funding Amount
$940,000.00
Summary
Thermal decomposition of PFAS. This project aims to investigate the thermal decomposition of per- and poly-fluroalkyl substances (PFAS). The project will focus on the catalytic destruction of PFAS reactions at elevated temperatures, which is expected to transform PFAS in a controlled and predictable way into benign products. By understanding the fate of these compounds during thermal decomposition, the project will allow the development of a new technology aimed at treating materials which have ....Thermal decomposition of PFAS. This project aims to investigate the thermal decomposition of per- and poly-fluroalkyl substances (PFAS). The project will focus on the catalytic destruction of PFAS reactions at elevated temperatures, which is expected to transform PFAS in a controlled and predictable way into benign products. By understanding the fate of these compounds during thermal decomposition, the project will allow the development of a new technology aimed at treating materials which have been contaminated with or have been used as absorbants for PFAS. The project will provide the technical underpinning of a new technology developed to treat fluorochemical-contaminated material and, in doing so, reduce the environmental impact of these contaminants.Read moreRead less
High Performance Anode for Direct Ammonia Solid Oxide Fuel Cells. Solid oxygen fuel cells are a clean energy generation device with very high energy efficiency and if with hydrogen as fuel, the emission is zero. However, the utilisation of hydrogen is limited by on-board storage. Ammonia is a promising hydrogen carrier and can be directly fed to solid oxide fuel cells without fuel storage problem, and the products are just hydrogen and nitrogen. For direct ammonia solid oxide fuel cells, the key ....High Performance Anode for Direct Ammonia Solid Oxide Fuel Cells. Solid oxygen fuel cells are a clean energy generation device with very high energy efficiency and if with hydrogen as fuel, the emission is zero. However, the utilisation of hydrogen is limited by on-board storage. Ammonia is a promising hydrogen carrier and can be directly fed to solid oxide fuel cells without fuel storage problem, and the products are just hydrogen and nitrogen. For direct ammonia solid oxide fuel cells, the key challenge is the anode. This project aims to develop a high performance anode for direct ammonia solid oxide fuel cells with both high activity and high stability at low temperature (below 600 degree C), thus addressing a key issue to make the direct ammonia solid oxide fuel cells commercially viable.Read moreRead less
Composites for thermal expansion matched oxygen electrodes. This project aims to develop high performance composite oxygen electrodes by using both negative thermal expansion materials and electrolyte materials to tailor the thermal expansion and activities of the perovskite-based electrodes for use in reduced temperature solid oxide cells. Such composite electrodes will show highly matched thermal expansion with electrolyte without sacrificing high activity at reduced temperatures. This project ....Composites for thermal expansion matched oxygen electrodes. This project aims to develop high performance composite oxygen electrodes by using both negative thermal expansion materials and electrolyte materials to tailor the thermal expansion and activities of the perovskite-based electrodes for use in reduced temperature solid oxide cells. Such composite electrodes will show highly matched thermal expansion with electrolyte without sacrificing high activity at reduced temperatures. This project seeks to address an important practical issue in the operation of solid oxide power cells - thermal expansion compatibility, which causes poor efficiency outside a narrow temperature band.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.
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EnzOnomy - an enzyme-based production pipeline for the bioeconomy. The sustainable production of high value chemicals (e.g. fuels, foods) from renewable materials is a cornerstone for the emerging global bioeconomy. We aim to harness the potential of protein engineering to develop a technology (EnzOnomy) to convert renewable raw material (e.g. sugar) into platform chemicals (e.g. isobutanol, a building block for jet fuels, fibers, plastics and antioxidants). Our multi-disciplinary and well estab ....EnzOnomy - an enzyme-based production pipeline for the bioeconomy. The sustainable production of high value chemicals (e.g. fuels, foods) from renewable materials is a cornerstone for the emerging global bioeconomy. We aim to harness the potential of protein engineering to develop a technology (EnzOnomy) to convert renewable raw material (e.g. sugar) into platform chemicals (e.g. isobutanol, a building block for jet fuels, fibers, plastics and antioxidants). Our multi-disciplinary and well established international team will link scientific progress to markets to enhance potential commercial impact in the bioeconomy. The project thus provides great benefit for our nation as it embeds Australia in technologies and global networks that will cement its leading position to safe-guard the future of our planet.
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Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in w ....Enabling wider use of mechanistic models for biodiversity forecasts . Forecasting species distributions is challenging yet necessary. The pattern-based models commonly used are error-prone. Mechanistic models, best equipped for the task, are limited by lack of data. This project aims to enable wider use of mechanistic models by developing new methods for dealing with incomplete trait data and uncertainty. It expects to generate new knowledge about how species’ traits define the environments in which they persist. Anticipated outcomes include enhanced capacity to apply mechanistic models to conservation problems, methods for communicating uncertainties and models for tens of species of immediate conservation interest. This will enable more reliable biodiversity forecasts, supporting better decision-making.
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Augmented Sociality: Enabling a Socialised Experience of Augmented Reality. This project will explore new socialised uses of Augmented Reality (AR) that expand creativity, social relations, and participation. We seek to better understand how AR content can be leveraged by people to create their own new ways of learning, collaborating, and relating with each other. To do so we will study and prototype new tools and platforms to allow non-experts to create their own AR media. We aim to enable peop ....Augmented Sociality: Enabling a Socialised Experience of Augmented Reality. This project will explore new socialised uses of Augmented Reality (AR) that expand creativity, social relations, and participation. We seek to better understand how AR content can be leveraged by people to create their own new ways of learning, collaborating, and relating with each other. To do so we will study and prototype new tools and platforms to allow non-experts to create their own AR media. We aim to enable people of all ages, education, and background, to imagine and create, and not just passively consume, AR contents, services, and applications. We will generate new applications of AR, a new platform to collaboratively create these applications, and a new theory of 'Augmented Sociality' to guide AR design.
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