Towards solving large-scale topology optimization problems with buckling constraints at the cost of linear analyses

Federico Ferrari, Ole Sigmund*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    This work presents a multilevel approach to large{scale topology optimization accounting for linearized buckling criteria. The method relies on the use of preconditioned iterative solvers for all the systems involved in the linear buckling and sensitivity analyses and on the approximation of buckling modes from a coarse discretization. The strategy shows three main benefits: first, the computational cost for the eigenvalue analyses is drastically cut. Second, artifacts due to local
    stress concentrations are alleviated when computing modes on the coarse scale. Third, the ability to select a reduced set of important global modes and filter out less important local ones. As a result, designs with improved buckling resistance can be generated with a computational cost little more than that of a corresponding compliance minimization problem solved for multiple loading cases. Examples of 2D and 3D structures discretized by up to some millions of degrees of freedom are solved in Matlab to show the effectiveness of the proposed method. Finally, a post{processing procedure is suggested in order to reinforce the optimized design against local buckling.
    Original languageEnglish
    Article number112911
    JournalComputer Methods in Applied Mechanics and Engineering
    Volume363
    Number of pages19
    ISSN0045-7825
    DOIs
    Publication statusPublished - 2020

    Keywords

    • Topology Optimization
    • Linearized buckling
    • Multilevel methods
    • Large-scale computing
    • Stress analysis

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