Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive ....Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive tools will be developed that will assist in assessing the viability in Australia of hydrogen exploration and engineered retrieval.
Benefits
Ready access to naturally produced hydrogen could enable Australia to replace hydrogen that is currently generated via the use of unabated hydrocarbons.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