Industrial Transformation Research Hubs - Grant ID: IH130200012
Funder
Australian Research Council
Funding Amount
$2,748,358.00
Summary
ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). This Research Hub aims to undertake simultaneous modelling of deep Earth and surface processes, spanning basin scales to individual sediment grains. The Hub will develop and apply cutting-edge basin simulation approaches to transform the seeding and testing of basin exploration models, extending their viability to complex, ....ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). This Research Hub aims to undertake simultaneous modelling of deep Earth and surface processes, spanning basin scales to individual sediment grains. The Hub will develop and apply cutting-edge basin simulation approaches to transform the seeding and testing of basin exploration models, extending their viability to complex, inaccessible remote and deep exploration targets. The Hub will fuse multidimensional data into five dimensional basin models (space and time, with uncertainty estimates) by coupling the evolution of mantle flow, crustal deformation, erosion and sedimentary processes, achieving a quantum leap in basin modelling and petroleum systems analysis.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC180100030
Funder
Australian Research Council
Funding Amount
$3,925,357.00
Summary
ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching ....ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching objectives are to enable development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100051
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models th ....The ARC Research Hub for Digital Bioprocess Development. The ARC Hub for Digital Bioprocess Development aims to assist the Biopharma industry by increasing digital innovation, productivity and competitiveness. An interdisciplinary team of engineers, scientists and computing specialists will develop digitally integrated advanced manufacturing processes and a platform for industry adoption. The program will address key bioprocessing research challenges and develop new process and digital models that can predict and optimise manufacturing processes, resulting in greater yields, faster and more flexible processes and enhanced product stability. The Hub will transform biopharmaceutical manufacturing and unlock growth opportunities to forge an internationally competitive Australian Biopharma sector.Read moreRead less
Modelling graph-of-graphs for solving document categorisation problems. Documents in the World Wide Web, such as scientific documents, exhibit a referencing structure as well as being structured objects themselves. This project addresses some inherent limitations of existing modelling techniques in order to improve on the quality of results, and to allow the addressing of some unsolved problems involving documents.
Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in mi ....Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in microscale tissue properties are lacking. The tools developed by this project will be used to generate new magnetic resonance image based maps to convey information on tissue microstructure changes in the human brain. Additionally, the mathematical tools developed will be transferable to other applications where diffusion and transport in heterogeneous porous media play a role.Read moreRead less
Using species distribution models to make robust conservation decisions. Species distribution models inform numerous conservation decisions, from planning reserves and managing biological invasions to assessing climate change impacts. While it is often vital to predict where suitable conditions for a species occur, many applications disregard uncertainty, leading to unexpected and potentially unacceptable outcomes. This project aims to provide a definitive guide to using species distribution mod ....Using species distribution models to make robust conservation decisions. Species distribution models inform numerous conservation decisions, from planning reserves and managing biological invasions to assessing climate change impacts. While it is often vital to predict where suitable conditions for a species occur, many applications disregard uncertainty, leading to unexpected and potentially unacceptable outcomes. This project aims to provide a definitive guide to using species distribution models in conservation decision-making by integrating ecological and statistical thinking with decision theory. It seeks to describe how to explore the sources of uncertainty and their impact, develop approaches to reducing uncertainty, and evaluate the effects of uncertainty from the decision viewpoint in order to assist more robust conservation decision making.Read moreRead less
International coalitions for climate change mitigation: the role of carbon market linkages and trade restrictions. This project uses cooperative game theory, implementation theory and agent-based modelling to investigate how coalitions to reduce greenhouse gas emissions could be formed and maintained among countries. Applications include the role of carbon market linkage and trade policy, in countries of the Asia-Pacific region.
Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate t ....Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate this task. This project aims to develop a real-time, whole-of-system operational performance framework that can help operators in finding and evaluating solutions to maximise throughput, reduce wait times and mitigate flow-on effects. Innovative new video analytic and Bayesian Network based tools are integrated to address the challenges of adaptability and uncertainty.Read moreRead less
Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dyn ....Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dynamics over time in the fields of education, health, public discourse and science. It is expected to result in new theories and methods for recurrence analysis validated using real-world data; and to enable new technologies for evaluating professional communication training and communication changes resulting from education or disease progression.Read moreRead less