July 3, 2019 / Brit Steiner

"Symplectic Model Order Reduction with Non-Orthonormal Bases" published

New Scientific Article

We are happy to announce that our submission "Symplectic Model Order Reduction with Non-Orthonormal Bases" was accepted and published in the Special Issue "Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics" in the open access journal "Mathematical and Computational Applications" (MCA). In our article, we classify basis generation techniques for symplectic model order reduction as orthonormal and non-orthonormal. We prove that existing basis generation techniques almost exclusively restrict to the class of orthonormal procedures. Furthermore, we propose a new, non-orthonormal method and present first theoretical results as well as a comparison with existing methods for a linear elasticity model in the numerical experiments.

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