Engineers are running ultra-high-fidelity computer simulations of air swirling through a radial impeller—a spinning disc with blades that compresses gas in jet engines and industrial pumps—to capture every chaotic eddy in real time. Current design methods rely on time-averaged snapshots of these flows, which miss the unsteady behaviour that actually drives energy losses. This is especially problematic for the tiny gap between the blade tip and the casing wall, where leakage causes significant inefficiency. Manufacturers often cannot shrink this gap further due to machining limits, yet no framework exists to predict how to reduce losses for a fixed gap. Radial impeller performance prediction also lags behind that of axial compressors, a gap this work aims to close. If successful, the project will produce a fast, reduced-order model that engineers can plug directly into 3D design software. That could lead to more efficient jet engines, turbochargers, and gas compressors—cutting fuel consumption and emissions without requiring tighter manufacturing tolerances. The work is primarily applied fluid dynamics, but the unsteady framework itself is a fundamental advance in how turbulent flows are characterised, with potential relevance to any system where unsteady aerodynamics matters.
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Research Aims Currently, unsteady numerical studies with DNS still rely on time averaged quantities. This means that, even today, unsteady flows are still viewed from a fundamentally steady point of view with no existing framework to switch to a truly unsteady perspective. Establishing a truly unsteady framework with which to characterise flows is the first aim of this project. Following on from this, the unsteady framework developed will be applied to a radial impeller to predict the unsteady losses, especially from the gap between the blade tip and the wall (tip gap). This serves to fill two gaps in knowledge: firstly, it is currently known that reducing the tip gap in radial impellers reduces the loss, but it is still unknown how the loss can be reduced for a fixed tip gap e.g. if it minimum tip gap is limited by manufacturing constraints. Secondly, the ability to predict radial impeller performance lags behind that for axial compressors. Achieving this aim will provide a step forward in reducing this discrepancy. Finally, from the DNS data and unsteady framework, develop a reduced order model for radial impeller loss that is fast enough to be used in the 3D design stage. Research Approach To achieve the first aim, DNS will be performed on a cascade version of the radial impeller (this is a simpler version of the geometry) in order to test different unsteady frameworks. Once a framework has been selected, the second aim will be achieved by performing DNS of the full radial impeller geometry with tip gaps under full operating conditions. Using the unsteady framework, unsteady flow behaviour can be linked to loss which will allow prediction of radial impeller performance. Methodology for achieving the third aim will likely involve the identification of the flow features within a radial impeller which dominates loss, with others being stripped from the loss prediction model. Novel Engineering/Physical Sciences Truly unsteady framework for characterising unsteady and turbulent flows Development of loss reduction methods in radial impellers with a fixed tip gap Higher accuracy radial impeller performance prediction
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