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Separable Shape Tensors for Aerodynamic Design

Published

Author(s)

Zachary J. Grey, Andrew Glaws, Olga Doronina

Abstract

Airfoil shape design is a classical problem in engineering and manufacturing. In this work, we combine principled physics-based considerations for the shape design problem with modern computational techniques using a data-driven approach. Modern and traditional analyses of two-dimensional (2D) and three-dimensional (3D) aerodynamic shapes reveal a flow-based sensitivity to specific deformations that can be represented generally by affine transformations (rotation, scaling, shearing, and translation). We present a novel representation of shapes that decouples affine-style deformations over a submanifold and a product submanifold principally of the Grassmannian. As an analytic generative model, the separable representation, informed by a database of physically relevant airfoils, offers: (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) an improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal 2D shapes.
Citation
Journal of Computational Design and Engineering

Citation

Grey, Z. , Glaws, A. and Doronina, O. (2023), Separable Shape Tensors for Aerodynamic Design, Journal of Computational Design and Engineering, [online], https://doi.org/10.1093/jcde/qwac140, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934971 (Accessed July 20, 2024)

Issues

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Created January 31, 2023, Updated April 11, 2023