Dynamical Model Reduction Method for Solving Parameter-Dependent Dynamical Systems
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Publication:5350447
DOI10.1137/16M1071493zbMath1373.65091arXiv1604.05706MaRDI QIDQ5350447
Anthony Nouy, Marie Billaud Friess
Publication date: 1 September 2017
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1604.05706
greedy algorithma posteriori error estimatelow-rank approximationmodel order reductionGalerkin projectionreduced basisparameter-dependent dynamical system
Error bounds for initial value and initial-boundary value problems involving PDEs (65M15) Simulation of dynamical systems (37M05) Numerical problems in dynamical systems (65P99)
Related Items (7)
A new splitting algorithm for dynamical low-rank approximation motivated by the fibre bundle structure of matrix manifolds ⋮ Physics-informed machine learning for reduced-order modeling of nonlinear problems ⋮ Error estimation in reduced basis method for systems with time-varying and nonlinear boundary conditions ⋮ A weak-intrusive stochastic finite element method for stochastic structural dynamics analysis ⋮ Neural Galerkin schemes with active learning for high-dimensional evolution equations ⋮ Well‐scaled, a‐posteriori error estimation for model order reduction of large second‐order mechanical systems ⋮ Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism
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