Local equilibration error estimators for guaranteed error control in adaptive stochastic higher-order Galerkin FEM
- Eigel, Martin
- Merdon, Christian
2010 Mathematics Subject Classification
- 35R60 47B80 60H35 65C20 65N12 65N22 65J10
- partial differential equations with random coefficients, equilibrated estimator, guaranteed bounds, uncertainty quantification, stochastic finite element methods, operator equations, adaptive methods
Equilibration error estimators have been shown to commonly lead to very accurate guaranteed error bounds in the a posteriori error control of finite element methods for second order elliptic equations. Here, we extend previous results by the design of equilibrated fluxes for higher-order finite element methods with nonconstant coefficients and illustrate the favourable performance of different variants of the error estimator within two deterministic benchmark settings. After the introduction of the respective parametric problem with stochastic coefficients and the stochastic Galerkin FEM discretisation, a novel a posteriori error estimator for the stochastic error in the energy norm is devised. The error estimation is based on the stochastic residual and its decomposition into approximation residuals and a truncation error of the stochastic discretisation. Importantly, by using the derived deterministic equilibration techniques for the approximation residuals, the computable error bound is guaranteed for the considered class of problems. An adaptive algorithm allows the simultaneous refinement of the deterministic mesh and the stochastic discretisation in anisotropic Legendre polynomial chaos. Several stochastic benchmark problems illustrate the efficiency of the adaptive process.
- SIAM ASA J. Uncertain. Quantif., 4 (2016) pp. 1372--1397.