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Manifold alignment-based multi-fidelity reduced-order modeling applied to structural analysis

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Abstract

This work presents the application of a recently developed parametric, non-intrusive, and multi-fidelity reduced-order modeling method on high-dimensional displacement and stress fields arising from the structural analysis of geometries that differ in the size of discretization and structural topology. The proposed approach leverages manifold alignment to fuse inconsistent field outputs from high- and low-fidelity simulations by individually projecting their solution onto a common subspace. The effectiveness of the method is demonstrated on two multi-fidelity scenarios involving the structural analysis of a benchmark wing geometry. Results show that outputs from structural simulations using incompatible grids, or related yet different topologies, are easily combined into a single predictive model, thus eliminating the need for additional pre-processing of the data. The new multi-fidelity reduced-order model achieves a relatively higher predictive accuracy at a lower computational cost when compared to a single-fidelity model.

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Code availability

The computer program that implements the method presented in this work will be made available through a repository link.

Notes

  1. The geometry file of the baseline aircraft is provided as electronic supplementary material.

  2. The AVL source code is publicly available at https://web.mit.edu/drela/Public/web/avl/.

  3. The AVL model of the baseline aircraft is provided as electronic supplementary material.

  4. The Nastran model of the baseline wing structure is provided as electronic supplementary material.

  5. CPU times are based on an Intel Core i9-10885H CPU.

  6. The field data generated with each fidelity level are provided as supplementary material.

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Author notes

  1. Christian Perron, Darshan Sarojini, Dushhyanth Rajaram, Jason Corman and Dimitri Mavris have contributed equally to this work

Authors and Affiliations

  1. Daniel Guggenheim School of Aerospace Engineering, Georgia Institute of Technology, North Avenue NW, Atlanta, GA, 30332, USA

    Christian Perron, Darshan Sarojini, Dushhyanth Rajaram, Jason Corman & Dimitri Mavris

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  1. Christian Perron
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  2. Darshan Sarojini
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  3. Dushhyanth Rajaram
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Correspondence to Dushhyanth Rajaram.

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The data and accompanying material used to generate results presented in this work will be made available as electronic supplementary material.

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Perron, C., Sarojini, D., Rajaram, D. et al. Manifold alignment-based multi-fidelity reduced-order modeling applied to structural analysis. Struct Multidisc Optim 65, 236 (2022). https://doi.org/10.1007/s00158-022-03274-1

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