Efficient component-wise and solver-based intrusive SFEM analysis of complex structures

In this study, important computational aspects of intrusive stochastic finite element methods (SFEM) are investigated. The importance of the interaction with 3rd party deterministic finite element (FE) solvers is emphasized within this context. Especially, data management is in the focus. Two implem...

Full description

Saved in:
Bibliographic Details
Published in:Finite elements in analysis and design 2010-05, Vol.46 (5), p.449-459
Main Authors: Panayirci, H.M., Pellissetti, M.F.
Format: Article
Language:English
Subjects:
Computational efficiency
Computational stochastic mechanics
Computational techniques
Exact sciences and technology
Finite element method
Finite-element and galerkin methods
Fundamental areas of phenomenology (including applications)
General-purpose software
Mathematical analysis
Mathematical methods in physics
Mathematical models
Matrices
Matrix methods
Perturbation methods
Physics
Solid mechanics
Solvers
Stochastic finite elements
Structural and continuum mechanics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this study, important computational aspects of intrusive stochastic finite element methods (SFEM) are investigated. The importance of the interaction with 3rd party deterministic finite element (FE) solvers is emphasized within this context. Especially, data management is in the focus. Two implementation techniques, namely the component-wise and the solver-based implementations, have been introduced in order to improve the computational efficiency. It is shown that by reducing the quantity and the size of the transferred system matrices, a significant reduction in the computational cost can be achieved. This is demonstrated on representative FE models, which are analyzed with the perturbation method, the Neumann expansion method and the polynomial chaos expansion method, respectively. Finally, a procedure is introduced in order to efficiently model and propagate the uncertainties in parameters, which do not appear in linear terms inside the components of the system matrices.
ISSN:0168-874X
1872-6925
DOI:10.1016/j.finel.2010.01.009