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Deterministic-based robust design optimization of composite structures under material uncertainty
RISE Research Institutes of Sweden, Materials and Production, Polymeric Materials and Composites. Linköping University, Sweden.
Linköping University, Sweden.
RISE Research Institutes of Sweden, Materials and Production, Polymeric Materials and Composites.ORCID iD: 0000-0001-6559-7694
Linköping University, Sweden.ORCID iD: 0000-0003-4472-1742
2023 (English)In: Composite structures, ISSN 0263-8223, E-ISSN 1879-1085, Vol. 322, article id 117336Article in journal (Refereed) Published
Abstract [en]

We propose a new deterministic robust design optimization method for composite laminate structures under worst-case material uncertainty. The method is based on a simultaneous parametrization of topology and material and combines a design problem and a material uncertainty problem into a single min–max optimization problem which provides an efficient approach to handle variation of material properties in stiffness driven design optimization problems. An analysis is performed using a design problem based on a failure criterion formulation to evaluate the ability of the proposed method to generate robust composite designs. The design problem is solved using various loads, boundary conditions and manufacturing constraints. The designs generated with the proposed method have improved objective responses compared to the worst-case response of designs generated with nominal material properties and are less sensitive to the variation of material properties. The analysis indicates that the proposed method can be efficiently applied in a robust structural optimization framework. © 2023 The Author(s)

Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 322, article id 117336
Keywords [en]
Failure criterion, Hyperbolic function parametrization, Laminated composites, Material uncertainty, Robust optimization, Structural optimization, Failure (mechanical), Hyperbolic functions, Composites structures, Design problems, Deterministics, Failure criteria, Parametrizations, Robust design optimization, Structural optimisations
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:ri:diva-65692DOI: 10.1016/j.compstruct.2023.117336Scopus ID: 2-s2.0-85165542694OAI: oai:DiVA.org:ri-65692DiVA, id: diva2:1786707
Note

 Correspondence Address: D. Hozić; RISE Research Institutes of Sweden, Division of Materials and Production, Polymers, Fibers and Composites Department, Borås, Box 857, 501 15, Sweden; 

This work was financed by the Swedish Energy Agency (Energimyndigheten) through grant number P48175-1 and the Swedish Research Council under grant agreement No. 2019-04615 , and is associated with the Swedish Electromobility Center 1 1 (SEC). Their support is gratefully acknowledged. The authors would also like to thank Krister Svanberg for providing his implementation of GCMMA.

Available from: 2023-08-09 Created: 2023-08-09 Last updated: 2024-10-28Bibliographically approved

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Cameron, ChristopherLoukil, Mohamed

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