The University of Southampton
University of Southampton Institutional Repository

Projection schemes in stochastic finite element analysis

Projection schemes in stochastic finite element analysis
Projection schemes in stochastic finite element analysis
In traditional computational mechanics, it is often assumed that the physical properties of the system under consideration are deterministic. This assumption of determinism forms the basis of most mathematical modeling procedures used to formulate partial differential equations (PDEs) governing the system response. In practice, however, some degree of uncertainty in characterizing virtually any engineering system is inevitable. In a structural system, deterministic characterization of the system properties and its environment may not be desirable due to several reasons, including uncertainty in the material properties due to statistically inhomogeneous microstructure, variations in nominal geometry due to manufacturing tolerances, and uncertainty in loading due to the nondeterministic nature of the operating environment. These uncertainties can be modeled within a probabilistic framework, which leads to PDEs with random coefficients and associated boundary and initial conditions governing the system dynamics. It is implicitly assumed here that uncertainty in the PDE coefficients can be described by random variables or random fields that are constructed using experimental data or stochastic micromechanical analysis.
0849311802
CRC Press
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Nikolaidis, Efstratios
Ghiocel, Dan M.
Singhal, Suren
Nair, Prasanth B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Nikolaidis, Efstratios
Ghiocel, Dan M.
Singhal, Suren

Nair, Prasanth B. (2004) Projection schemes in stochastic finite element analysis. In, Nikolaidis, Efstratios, Ghiocel, Dan M. and Singhal, Suren (eds.) Engineering design reliability handbook. CRC Press.

Record type: Book Section

Abstract

In traditional computational mechanics, it is often assumed that the physical properties of the system under consideration are deterministic. This assumption of determinism forms the basis of most mathematical modeling procedures used to formulate partial differential equations (PDEs) governing the system response. In practice, however, some degree of uncertainty in characterizing virtually any engineering system is inevitable. In a structural system, deterministic characterization of the system properties and its environment may not be desirable due to several reasons, including uncertainty in the material properties due to statistically inhomogeneous microstructure, variations in nominal geometry due to manufacturing tolerances, and uncertainty in loading due to the nondeterministic nature of the operating environment. These uncertainties can be modeled within a probabilistic framework, which leads to PDEs with random coefficients and associated boundary and initial conditions governing the system dynamics. It is implicitly assumed here that uncertainty in the PDE coefficients can be described by random variables or random fields that are constructed using experimental data or stochastic micromechanical analysis.

Text
nair_04a.pdf - Version of Record
Download (4MB)

More information

Published date: 2004

Identifiers

Local EPrints ID: 22966
URI: http://eprints.soton.ac.uk/id/eprint/22966
ISBN: 0849311802
PURE UUID: 0990145d-a5dc-48cd-a183-95880ee79ed2

Catalogue record

Date deposited: 04 Apr 2006
Last modified: 15 Mar 2024 06:42

Export record

Contributors

Author: Prasanth B. Nair
Editor: Efstratios Nikolaidis
Editor: Dan M. Ghiocel
Editor: Suren Singhal

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×