Approximated Lax Pairs for the Reduced Order Integration of Nonlinear Evolution Equations
arXiv:1401.4829 · doi:10.1016/j.jcp.2014.01.047
Abstract
A reduced-order model algorithm, called ALP, is proposed to solve nonlinear evolution partial differential equations. It is based on approximations of generalized Lax pairs. Contrary to other reduced-order methods, like Proper Orthogonal Decomposition, the basis on which the solution is searched for evolves in time according to a dynamics specific to the problem. It is therefore well-suited to solving problems with progressive front or wave propagation. Another difference with other reduced-order methods is that it is not based on an off-line / on-line strategy. Numerical examples are shown for the linear advection, KdV and FKPP equations, in one and two dimensions.
Cited by in corpus (20)
- On the stability of projection-based model order reduction for convection-dominated laminar and turbulent flows
- Conservative model reduction for finite-volume models
- Lagrangian Dynamic Mode Decomposition for Construction of Reduced-Order Models of Advection-Dominated Phenomena
- Dimensionality Reduction and Reduced Order Modeling for Traveling Wave Physics
- Projection-Based Model Reduction with Dynamically Transformed Modes
- Lagrangian basis method for dimensionality reduction of convection dominated nonlinear flows
- Reduced Basis Methods: Success, Limitations and Future Challenges
- Parametric model order reduction and its application to inverse analysis of large nonlinear coupled cardiac problems
- Registration-based model reduction of parameterized two-dimensional conservation laws
- Manifold Approximations via Transported Subspaces: Model reduction for transport-dominated problems
- Overcoming slowly decaying Kolmogorov n-width by transport maps: application to model order reduction of fluid dynamics and fluid--structure interaction problems
- and -adaptive Interpolation by Transformed Snapshots for Parametric and Stochastic Hyperbolic PDEs
- Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems
- Structure-preserving reduced-order modelling of Korteweg de Vries equation
- Lagrangian Data-Driven Reduced Order Modeling of Finite Time Lyapunov Exponents
- Transformed Snapshot Interpolation with High Resolution Transforms
- Approximation of skewed interfaces with tensor-based model reduction procedures: application to the reduced basis hierarchical model reduction approach
- Hyper-reduction for parametrized transport dominated problems via online-adaptive reduced meshes
- A Low Rank Neural Representation of Entropy Solutions
- Well-balanced POD-based reduced-order models for finite volume approximation of hyperbolic balance laws