Title
Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates.
Abstract
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.
Year
DOI
Venue
2014
10.1016/j.jcp.2014.09.014
Journal of Computational Physics
Keywords
DocType
Volume
Uncertainty quantification,A posteriori error estimation,Sparse grids,Stochastic collocation,Adaptivity
Journal
280
Issue
ISSN
Citations 
C
0021-9991
0
PageRank 
References 
Authors
0.34
10
2
Name
Order
Citations
PageRank
John D. Jakeman1527.65
Timothy Wildey200.34