Document Type
Article
Publication Date
7-2013
Publication Title
Structural Safety
Abstract
A new method is proposed for reliability-based topology optimization of truss structures with random geometric imperfections and material variability. Such imperfections and variability, which may result from manufacturing processes, are assumed to be small in relation to the truss dimensions and mean material properties and normally distributed. Extensive numerical evidence suggests that the trusses, when optimized in terms of a displacement-based demand metric, are characterized by randomness in the stiffness that follow the Gumbel distribution. Based on this observation, it was possible to derive analytical expressions for the structural reliability, enabling the formulation of a computationally efficient single-loop reliability-based topology optimization algorithm. Response statistics are estimated using a second-order perturbation expansion of the stiffness matrix and design sensitivities are derived so that they can be directly used by gradient-based optimizers. Several examples illustrate the accuracy of the perturbation expressions and the applicability of the method for developing optimal designs that meet target reliabilities.
Recommended Citation
Jalalpour, M., Guest, J., and Igusa, T., “Reliability-based topology optimization of trusses with stochastic stiffness”, Structural Safety 43: 41-49, 2013
DOI
10.1016/j.strusafe.2013.02.003
Version
Postprint
Publisher's Statement
NOTICE: this is the author’s version of a work that was accepted for publication in Structural Safety. 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 Structural Safety, 43, (July 2013) DOI:10.1016/j.strusafe.2013.02.003
Volume
43
Comments
This work was supported by National Science Foundation under Grant No. CMMI-0928613 with Dr. Christina Bloebaum serving as program officer. This support is gratefully acknowledged.