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Computing multiple solutions of topology optimization problems

Abstract:
Topology optimization problems often support multiple local minima due to a lack of convexity. Typically, gradient-based techniques combined with continuation in model parameters are used to promote convergence to more optimal solutions; however, these methods can fail even in the simplest cases. In this paper, we present an algorithm to perform a systematic exploratory search for the solutions of the optimization problem via second-order methods without a good initial guess. The algorithm combines the techniques of deflation, barrier methods and primal-dual active set solvers in a novel way. We demonstrate this approach on several numerical examples, observe mesh-independence in certain cases and show that multiple distinct local minima can be recovered.
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1137/20M1326209

Authors


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Institution:
University of Oxford
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0002-1241-7060


Publisher:
Society for Industrial and Applied Mathematics
Journal:
SIAM Journal on Scientific Computing More from this journal
Volume:
43
Issue:
3
Pages:
A1555–A1582
Publication date:
2021-05-06
Acceptance date:
2021-01-11
DOI:
EISSN:
1095-7197
ISSN:
1064-8275


Language:
English
Keywords:
Pubs id:
1154021
Local pid:
pubs:1154021
Deposit date:
2021-01-12

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