Data-driven monitoring of raceway dynamics in ironmaking blast furnaces. Raceway dynamics in ironmaking blast furnaces affect operational stability and cost considerably, yet their dynamic behaviour has not been well monitored online. The project aims to develop a data-driven model for monitoring the internal state of gas-solid-powder reacting flow in the raceway and predicting raceway anomalies online. It will be achieved by combining particle-fluid numerical simulations with data processing an ....Data-driven monitoring of raceway dynamics in ironmaking blast furnaces. Raceway dynamics in ironmaking blast furnaces affect operational stability and cost considerably, yet their dynamic behaviour has not been well monitored online. The project aims to develop a data-driven model for monitoring the internal state of gas-solid-powder reacting flow in the raceway and predicting raceway anomalies online. It will be achieved by combining particle-fluid numerical simulations with data processing and reduced-order state observer, supported by lab/plant experiments, and collaborating with two industry partners from coal and steel industries. The project outcomes including codes, models and raceway control strategies can help promote Australian metallurgical coal's global markets and ultimately the Australian economy.Read moreRead less
Modelling of polydisperse particle-fluid reacting flows. Complex polydisperse particle-fluid reacting flows are widely practised in many industries where particle size distribution is wide and particle number is huge, yet the process design and optimisation are hindered by the lack of fundamental understanding of the complex reacting flows, particularly polydispersity and interactions. The project will tackle this specific challenge by developing a novel particle-scale mathematical model by inco ....Modelling of polydisperse particle-fluid reacting flows. Complex polydisperse particle-fluid reacting flows are widely practised in many industries where particle size distribution is wide and particle number is huge, yet the process design and optimisation are hindered by the lack of fundamental understanding of the complex reacting flows, particularly polydispersity and interactions. The project will tackle this specific challenge by developing a novel particle-scale mathematical model by incorporating new numerical techniques of interphase heat/mass transfers, polydispersity and computation speed-up; and applying it to two typical industry processes for demonstration. The outcomes will be applied across a range of industries of vital importance to Australian economic and technological future.Read moreRead less
Preparation and use of lignite-iron ore composite briquettes for ironmaking. Preparation and use of lignite-iron ore composite briquettes for ironmaking. This project aims to study the briquetting processes of fine powders, and the preparation and utilization of new brown coal (lignite)–iron ore composite briquettes in a blast furnace. Lignite is a low-cost and abundant resource, and could be used in an emerging carbon-iron ore composite briquette for low-cost ironmaking. This project will perfo ....Preparation and use of lignite-iron ore composite briquettes for ironmaking. Preparation and use of lignite-iron ore composite briquettes for ironmaking. This project aims to study the briquetting processes of fine powders, and the preparation and utilization of new brown coal (lignite)–iron ore composite briquettes in a blast furnace. Lignite is a low-cost and abundant resource, and could be used in an emerging carbon-iron ore composite briquette for low-cost ironmaking. This project will perform multi-scale numerical studies, supported by lab/industry-scale experiments, to produce models and control strategies. Anticipated outcomes include better design and control of briquette's preparation and utilization in ironmaking for further cost-cutting; a new market for brown coal; and a more competitive Australian economy.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH230100010
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Smart Process Design and Control . ARC Research Hub for Smart Process Design and Control aims to develop and apply advanced computational technologies to model and optimise complex multiphase processes by integrating the novel multiscale and AI modelling approaches. The outcomes include theories, computer models and simulation techniques, advanced knowledge about process modelling and optimisation, innovative technologies and processes for low carbon operations, and tens of ....ARC Research Hub for Smart Process Design and Control . ARC Research Hub for Smart Process Design and Control aims to develop and apply advanced computational technologies to model and optimise complex multiphase processes by integrating the novel multiscale and AI modelling approaches. The outcomes include theories, computer models and simulation techniques, advanced knowledge about process modelling and optimisation, innovative technologies and processes for low carbon operations, and tens of postdoc and PhD students through academic, industrial and international collaboration. Their application will significantly improve energy/process efficiency and reduce CO2 emission. The Hub will generate a significant impact on the mineral and metallurgical industries which are important to Australia.Read moreRead less
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