Solar particle receivers, in which solid particles suspended in a turbulent flow absorb incident concentrated solar radiation, are potentially an efficient way to capture high-temperature solar heat. High-temperature heat, in turn, enables the application of solar energy into new processes, especially in industrial minerals processing. Design and scale-up of solar particle receivers is currently hindered by a lack of predictive capabilities of computational models.
In this project, you will develop innovative machine learning approaches to modelling the interphase transfers of heat and momentum between the particle and fluid carrier phase. These models will be tested against very large scale computations of particle-laden flows, carried out on cutting edge supercomputing resources. The outcome will be improved models with quantified performance, leading to practical tools the nascent industry in solar processing of materials can use to design and scale up reactors.
How to Apply
Express your interest in this project by emailing Professor Evatt Hawkes at evatt.hawkes@unsw.edu.au. Include a copy of your CV and your academic transcript(s).
School / Research Area
Mechanical and Manufacturing Engineering
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