Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates
DOI10.1016/j.jcp.2014.09.014zbMath1349.65422arXiv1407.1061OpenAlexW1979307734MaRDI QIDQ349696
Publication date: 5 December 2016
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1407.1061
Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) Mesh generation, refinement, and adaptive methods for the numerical solution of initial value and initial-boundary value problems involving PDEs (65M50) Partial difference equations (39A14) Numerical methods for difference equations (65Q10)
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- A posteriori error estimation and adaptive mesh refinement for a multiscale operator decomposition approach to fluid-solid heat transfer
- Numerical approach for quantification of epistemic uncertainty
- An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations
- Adaptive sparse grid multilevel methods for elliptic PDEs based on finite differences
- Dimension-adaptive tensor-product quadrature
- A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database
- A Posteriori Error Analysis of Parameterized Linear Systems Using Spectral Methods
- A Posteriori Error Analysis of Stochastic Differential Equations Using Polynomial Chaos Expansions
- Adjoint methods for PDEs: a posteriori error analysis and postprocessing by duality
- An optimal control approach to a posteriori error estimation in finite element methods
- A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
- Estimating the error of numerical solutions of systems of reaction-diffusion equations
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- Sparse grids
- Propagation of Uncertainties Using Improved Surrogate Models
- A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data
- Goal-oriented error estimation and adaptivity for the finite element method
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