Robust topology optimization: Minimization of expected and variance of compliance

Peter D. Dunning, H. Alicia Kim

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)
180 Downloads (Pure)

Abstract

Robust topology optimization has long been considered computationally intractable as it combines two highly expensive computational strategies. This paper considers simultaneous minimization of expectancy and variance of compliance in the presence of uncertainties in loading magnitude, using exact formulations and analytically derived sensitivities. It shows that only a few additional load cases are required, which scales in polynomial time with the number of uncertain load cases. The approach is implemented using the level set topology optimization method. Shape sensitivities are derived using the adjoint method. Several examples are used to investigate the effect of including variance in robust compliance optimization.
Original languageEnglish
Pages (from-to)2656-2664
Number of pages9
JournalAIAA Journal
Volume51
Issue number11
DOIs
Publication statusPublished - Nov 2013

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