Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100109
Funder
Australian Research Council
Funding Amount
$370,000.00
Summary
A facility for non-destructive quantification of coal structures, composition and percolation fluid flows in energy and environmental applications. The facility will advance our scientific understanding of 3D micro- and nanostructures of coal under various mechanical and chemical conditions. It will help develop process innovation and breakthrough technologies for energy and environmental applications. It will also enhance the research capabilities of the collaborating institutions.
Enhanced productivity of coal seam gas wells by continuous gas circulation. This project aims to develop foam assisted continuous gas circulation for dewatering new and existing coal seam gas wells. The potential benefits of this new method include enhanced gas production, better well control, reduced costs and better environmental effectiveness. The proposed solution eliminates the need for mechanical pumps which are currently used for dewatering, and which fail regularly due to gas and solids ....Enhanced productivity of coal seam gas wells by continuous gas circulation. This project aims to develop foam assisted continuous gas circulation for dewatering new and existing coal seam gas wells. The potential benefits of this new method include enhanced gas production, better well control, reduced costs and better environmental effectiveness. The proposed solution eliminates the need for mechanical pumps which are currently used for dewatering, and which fail regularly due to gas and solids accumulation within the production wells. Continuous gas circulation could achieve significant savings in downtime and maintenance costs. In addition, reducing onsite maintenance will minimise access requirements for maintenance rigs which disrupt rural activities where the wells are located, thus easing local traffic and reduce the environmental impacts that are associated with well workovers.Read moreRead less
Particle-scale modelling of particle-fluid flows in gas and oil extraction. Particle-scale modelling of particle-fluid flows in gas and oil extraction. This project aims to develop a particle scale model to study the pipeline transport of petroleum fluids. It will use a combined theoretical and experimental program, involving state-of-the-art discrete element modelling and simulation techniques, to describe the complex particle-fluid flow and erosion of pipeline transport in gas and oil extracti ....Particle-scale modelling of particle-fluid flows in gas and oil extraction. Particle-scale modelling of particle-fluid flows in gas and oil extraction. This project aims to develop a particle scale model to study the pipeline transport of petroleum fluids. It will use a combined theoretical and experimental program, involving state-of-the-art discrete element modelling and simulation techniques, to describe the complex particle-fluid flow and erosion of pipeline transport in gas and oil extraction, quantify the effects of key variables, and formulate strategies for optimum process control under different conditions. The research outcomes are expected to be useful for the process control of pipeline transport in Australia’s important petroleum and energy-related industries.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100211
Funder
Australian Research Council
Funding Amount
$230,000.00
Summary
3D Gamma Ray Tomography for Multiphase Flow Characterisation. We will establish a new tomographic facility which will allow a greater insight on the flows in industrial multiphase equipment which have opaque containers. The facility will provide a platform for Australian researchers to conduct fundamental research on complex flows, particularly those encountered in our mineral processing industry.
Data-driven modelling of complex reactive flows. Complex reactive flow is dominant in many chemicals, physical and biological processes and should be optimised online for operational efficiency and stability, yet it is hindered by the lack of reliable model techniques. The project tackles this challenge by developing a next-generation data-driven modelling approach via integrating continuum/discrete-scale fluid-particle dynamics with system/control theories, supported by lab/plant experiments. D ....Data-driven modelling of complex reactive flows. Complex reactive flow is dominant in many chemicals, physical and biological processes and should be optimised online for operational efficiency and stability, yet it is hindered by the lack of reliable model techniques. The project tackles this challenge by developing a next-generation data-driven modelling approach via integrating continuum/discrete-scale fluid-particle dynamics with system/control theories, supported by lab/plant experiments. Driven by online data, the generic approach can open up a powerful way to reliably describe the inner state of reactors and online predict operation anomalies. The outcomes can help transform a range of industries to smart manufacturing and design, which is vital to Australia's technological future.Read moreRead less
Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achiev ....Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achieve desired dynamic features. This project aims to develop such a data-based approach by controlling latent variable dynamics, using the behavioural systems framework integrated with big data analytics and artificial neural networks. The outcomes are expected to help build a cornerstone for future smart manufacturing.Read moreRead less
Initiation of spontaneous fires. This project aims to determine the origin of the initiation reactions that set off the self-heating of wood chips, coal, milk powder and other economically-important materials, leading to spontaneous fires. This project will provide fundamental understanding of the reactions between electronically excited species of oxygen and carbonaceous fuels, with applications to improved safety in wood, mineral and food industries. The outcomes include identification of the ....Initiation of spontaneous fires. This project aims to determine the origin of the initiation reactions that set off the self-heating of wood chips, coal, milk powder and other economically-important materials, leading to spontaneous fires. This project will provide fundamental understanding of the reactions between electronically excited species of oxygen and carbonaceous fuels, with applications to improved safety in wood, mineral and food industries. The outcomes include identification of the initiation mechanisms and development of mechanistic models that include the initiation step of the self-heating process, and development of new technologies for mitigation of spontaneous fires, based on quenching of the initiation reactions.Read moreRead less