A method to significantly improve finite element stress predictions

In this thesis, we present a novel method to improve the finite element stress predictions in static, dynamic and nonlinear analyses of solids. We focus on the use of low-order displacement-based finite elements, 3-node and 4-node elements in two-dimensional (2D) solutions, and 4-node and 8-node elements in 3D solutions -- because these elements can be computationally efficient, provided good stress predictions are obtained. We give a variational basis of the new method and compare the procedure, and its performance, with other effective previously proposed stress improvement techniques. We observe that the stresses of the new method converge quadratically in ID and 2D solutions, i.e. with the same order as the displacements, and conclude that the new stress improvement method shows much promise for the analysis of solids, structures and multiphysics problems, to calculate improved stress predictions and to establish error measures. Highlights: --Novel stress improvement method is given for static, dynamic and nonlinear analysis of solids. --Focus is on the use of low-order elements. --Quadratic convergence is observed for the improved stresses. --Method is compared with existing techniques.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2012

Author dc:creator

• Payen, Daniel Jose

Advisor dc:contributor.advisor

• Klaus-Jürgen Bathe.

• Mechanical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/74984

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/74984