High-order methods as an alternative to using sparse tensor products for stochastic Galerkin FEM

DOI10.1016/j.camwa.2013.06.005zbMath1350.65006OpenAlexW2014725412MaRDI QIDQ316572

Claude Jeffrey Gittelson

Publication date: 27 September 2016

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2013.06.005

zbMATH Keywords

convergencenumerical exampleshigh-order methodselliptic boundary value problemuncertainty quantificationelliptic two-point boundary value problempartial differential equations with random coefficientssparse tensor productsstochastic finite element methodsstochastic Galerkin approximations

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items

A convergent adaptive stochastic Galerkin finite element method with quasi-optimal spatial meshes, Editorial: High-order finite element approximation for partial differential equations

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