The University of Southampton
University of Southampton Institutional Repository

Error estimation and h-adaptive refinement in the analysis of natural frequencies

Error estimation and h-adaptive refinement in the analysis of natural frequencies
Error estimation and h-adaptive refinement in the analysis of natural frequencies

This paper deals with the estimation of the discretization error and the definition of an optimum h-adaptive process in the finite element analysis of natural frequencies and modes. Consistent and lumped mass matrices are considered. In the first case, the discretization error essentially proceeds from the stiffness modelization, so it is possible to apply the same error estimators than those considered in static problems. On the other hand, the error associated with the modelization of the inertial properties must be taken into account if lumped mass matrices are used. As far as h-adaptivity is concerned, it is usually interesting to obtain meshes with a specified error for each mode. However, traditional criteria for static problems consider only one load case. Defining the optimum mesh as the one that gets the desired error with the minimum number of elements, a method is proposed for the h-adaptive process taking into account a set of natural modes simultaneously. The proposed methods have been validated by applying them to bi-dimensional test problems.
0168-874X
137-153
Fuenmayor, F.J.
452423ef-ca4b-4004-8ece-9e3dd0ca886e
Restrepo, J.L.
a6afde13-7a8f-464d-8ba6-f94fde4693bd
Tarancón, J.E.
4f994549-2f0f-4408-8a64-f2e0e0d8ad4f
Baeza, L.
09dc5565-ad4b-49af-a104-d4b6ad28e1b0
Fuenmayor, F.J.
452423ef-ca4b-4004-8ece-9e3dd0ca886e
Restrepo, J.L.
a6afde13-7a8f-464d-8ba6-f94fde4693bd
Tarancón, J.E.
4f994549-2f0f-4408-8a64-f2e0e0d8ad4f
Baeza, L.
09dc5565-ad4b-49af-a104-d4b6ad28e1b0

Fuenmayor, F.J., Restrepo, J.L., Tarancón, J.E. and Baeza, L. (2001) Error estimation and h-adaptive refinement in the analysis of natural frequencies. Finite Elements in Analysis and Design, 38 (2), 137-153. (doi:10.1016/S0168-874X(01)00055-5).

Record type: Article

Abstract


This paper deals with the estimation of the discretization error and the definition of an optimum h-adaptive process in the finite element analysis of natural frequencies and modes. Consistent and lumped mass matrices are considered. In the first case, the discretization error essentially proceeds from the stiffness modelization, so it is possible to apply the same error estimators than those considered in static problems. On the other hand, the error associated with the modelization of the inertial properties must be taken into account if lumped mass matrices are used. As far as h-adaptivity is concerned, it is usually interesting to obtain meshes with a specified error for each mode. However, traditional criteria for static problems consider only one load case. Defining the optimum mesh as the one that gets the desired error with the minimum number of elements, a method is proposed for the h-adaptive process taking into account a set of natural modes simultaneously. The proposed methods have been validated by applying them to bi-dimensional test problems.

Full text not available from this repository.

More information

Published date: 2001
Organisations: Dynamics Group

Identifiers

Local EPrints ID: 411223
URI: https://eprints.soton.ac.uk/id/eprint/411223
ISSN: 0168-874X
PURE UUID: d97c5c0c-918b-4af0-9f30-cfe0f267aa57
ORCID for L. Baeza: ORCID iD orcid.org/0000-0002-3815-8706

Catalogue record

Date deposited: 15 Jun 2017 16:32
Last modified: 20 Jul 2019 00:28

Export record

Altmetrics

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 https://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.

×