Gradient-Preserving Hyper-Reduction of Nonlinear Dynamical Systems via Discrete Empirical Interpolation

DOI10.1137/22m1503890zbMath1526.65057arXiv2206.01792OpenAlexW4385208348MaRDI QIDQ6066424

Federico Vismara, Cecilia Pagliantini

Publication date: 16 November 2023

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2206.01792

zbMATH Keywords

nonlinear Hamiltonian systemsdiscrete empirical interpolationadaptive hyper-reductionpreservation of gradient structuresymplectic model order reduction

Mathematics Subject Classification ID

Numerical methods for Hamiltonian systems including symplectic integrators (65P10) Dynamical systems in numerical analysis (37N30) Numerical methods for ordinary differential equations (65L99)

Related Items (1)

Energy-conserving hyper-reduction and temporal localization for reduced order models of the incompressible Navier-Stokes equations

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