Turbomachinery active subspace performance maps are 2D contour plots that illustrate the variation of key flow performance metrics with different blade designs. While such maps are easy to construct for design parameterizations with two variables, in this presentation maps will be generated for a fan blade with twenty- five design variables. Turbomachinery active subspace performance maps combine active subspaces—a new set of ideas for dimension reduction—with fundamental turbomachinery aerodynamics and design spaces. In this presentation, contours of: (i)cruise efficiency, (ii) cruise pressure ratio, (iii) maximum climb flow capacity and (iv) sensitivity to manufacturing variations, are plotted as objectives for the fan.

These maps are then used to infer pedigree design rules: how best to increase fan efficiency; how best to desensitize blade aerodynamics to the impact of manufacturing variations? In the present study,the former required both a reduction in pressure ratio and flow capacity—leading to a reduction of the strength of the leading edge bow wave—while the latter required strictly a reduction in flow capacity. While such pedigree rules can be obtained from first principles, in this presentation these rules are derived from the active subspaces. This facilitates a more detailed quantification of the aerodynamic trade-offs. Thus, instead of simply stating that a particular design is more sensitive to manufacturing variations; or that it lies on a hypothetical ‘efficiency cliff ’, this presentation seeks to visualize, quantify and make precise such notions of turbomachinery design.

Dr Seshadri is a Research Associate in the Department of Engineering at the University of Cambridge, working in the area of computational engineering. Dr Seshadri's research interests include turbomachinery aeromechanics, uncertainty quantification and linear algebra.

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