Quantitative control of idealized analysis models of thin designs

Li, Ming, Zheng, Junzhe and Martin, Ralph Robert 2012. Quantitative control of idealized analysis models of thin designs. Computers & Structures 106-07 , pp. 144-153. 10.1016/j.compstruc.2012.04.012

Preview

PDF - Submitted Pre-Print Version Download (556kB) | Preview

Abstract

When preparing a design model for engineering analysis, model idealization is often used, where defeaturing, and/or local dimension reduction of thin regions, are carried out. This simplifies the analysis, but quantitative estimates of the idealization error, the analysis error caused by this idealization, are necessary if the results are to be of practical use. The paper focuses on a posteriori estimation of such idealization error, via both a theoretical analysis and practical algorithms. Our approach can compute bounds for the errors induced by dimension reduction, defeaturing or both in combination. Performance of our error estimate is demonstrated using examples.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	Defeaturing; Dimension reduction; Model idealization; CAD/CAE integration; Thin plate
Additional Information:	PDF uploaded in accordance with publisher's policy http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy [accessed 17/04/2015] NOTICE: this is the author’s version of a work that was accepted for publication in Computers & Structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Structures, [VOL 106-07, 2012] DOI 10.1016/j.compstruc.2012.04.012
Publisher:	Elsevier
ISSN:	0045-7949
Last Modified:	02 Dec 2024 12:30
URI:	https://orca.cardiff.ac.uk/id/eprint/36107

Citation Data

Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item