Dynamic Iteration Using Reduced Order Models: A Method for Simulation of Large Scale Modular Systems

DOI10.1137/S0036142901390494zbMath1033.65056OpenAlexW2074020883MaRDI QIDQ4785823

Muruhan Rathinam, Linda R. Petzold

Publication date: 5 January 2003

Published in: SIAM Journal on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/s0036142901390494

zbMATH Keywords

convergencecomparison of methodsnumerical examplesproper orthogonal decompositionlarge scale systemsmodel reductiondifferential algebraic equationswaveform relaxationdynamic iteration

Mathematics Subject Classification ID

Implicit ordinary differential equations, differential-algebraic equations (34A09) Nonlinear ordinary differential equations and systems (34A34) Numerical methods for initial value problems involving ordinary differential equations (65L05) Numerical methods for differential-algebraic equations (65L80)

Related Items

A note on POD model reduction methods for DAEs ⋮ Nonlinear model reduction via a locally weighted POD method ⋮ POD and CVT-based reduced-order modeling of Navier-Stokes flows ⋮ Reduced-order modeling of time-dependent PDEs with multiple parameters in the boundary data ⋮ Transport Reversal for Model Reduction of Hyperbolic Partial Differential Equations ⋮ Error estimates for abstract linear-quadratic optimal control problems using proper orthogonal decomposition ⋮ Reduced order output feedback control design for PDE systems using proper orthogonal decomposition and nonlinear semidefinite programming ⋮ POD-Galerkin approximations in PDE-constrained optimization ⋮ Convergence conditions on waveform relaxation of general differential-algebraic equations ⋮ Acceleration of iterative solution of series of systems due to better initial guess ⋮ Robust reduced order modeling of heat transfer in a back step flow ⋮ Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems