An overlapping domain decomposition method for the solution of parametric elliptic problems via proper generalized decomposition
arXiv:2307.16334 · doi:10.1016/j.cma.2023.116484
Abstract
A non-intrusive proper generalized decomposition (PGD) strategy, coupled with an overlapping domain decomposition (DD) method, is proposed to efficiently construct surrogate models of parametric linear elliptic problems. A parametric multi-domain formulation is presented, with local subproblems featuring arbitrary Dirichlet interface conditions represented through the traces of the finite element functions used for spatial discretization at the subdomain level, with no need for additional auxiliary basis functions. The linearity of the operator is exploited to devise low-dimensional problems with only few active boundary parameters. An overlapping Schwarz method is used to glue the local surrogate models, solving a linear system for the nodal values of the parametric solution at the interfaces, without introducing Lagrange multipliers to enforce the continuity in the overlapping region. The proposed DD-PGD methodology relies on a fully algebraic formulation allowing for real-time computation based on the efficient interpolation of the local surrogate models in the parametric space, with no additional problems to be solved during the execution of the Schwarz algorithm. Numerical results for parametric diffusion and convection-diffusion problems are presented to showcase the accuracy of the DD-PGD approach, its robustness in different regimes and its superior performance with respect to standard high-fidelity DD methods.
References in corpus (12)
- Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
- D3M: A deep domain decomposition method for partial differential equations
- Multilevel domain decomposition-based architectures for physics-informed neural networks
- Error control for the localized reduced basis multi-scale method with adaptive on-line enrichment
- Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction
- An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes
- Randomized Local Model Order Reduction
- Nonintrusive proper generalised decomposition for parametrised incompressible flow problems in OpenFOAM
- Parametric solutions involving geometry integrated with computer-aided design
- A one-shot overlapping Schwarz method for component-based model reduction: application to nonlinear elasticity
- Separated response surfaces for flows in parametrised domains: comparison of a priori and a posteriori PGD algorithms
- Hybridisable discontinuous Galerkin solution of geometrically parametrised Stokes flows
Cited by in corpus (3)
- PGD-based local surrogate models via overlapping domain decomposition: a computational comparison
- Data augmentation for the POD formulation of the parametric laminar incompressible Navier-Stokes equations
- An overlapping domain decomposition method for parametric Stokes and Stokes-Darcy problems via proper generalized decomposition