A new method for simultaneous material and topology optimization of composite laminate structures using Hyperbolic Function Parametrization
2021 (English)In: Composite structures, ISSN 0263-8223, E-ISSN 1879-1085, Vol. 276, article id 114374Article in journal (Refereed) Published
Abstract [en]
This paper presents a new discrete parametrization method for simultaneous topology and material optimization of composite laminate structures, referred to as Hyperbolic Function Parametrization (HFP). The novelty of HFP is the way the candidate materials are parametrized in the optimization problem. In HFP, a filtering technique based on hyperbolic functions is used, such that only one design variable is used for any given number of material candidates. Compared to state-of-the-art methods such Discrete Material and Topology Optimization (DMTO) and Shape Function with Penalization (SFP), HFP has much fewer optimization variables and constraints but introduces additional non-linearity in the optimization problems. A comparative analysis of HFP, DMTO and SFP are performed based on the problem of maximizing the stiffness of composite plates under a total volume constraint and multiple manufacturing constraints using various loads, boundary conditions and input parameters. The comparison shows that all three methods are highly sensitive to the choice of input parameters for the optimization problem, although the performance of HFP is overall more consistent. HFP method performs similarly to DMTO and SFP in terms of the designs obtained and computational cost. However, HFP obtains similar or better objective function values compared to the DMTO and SFP methods. © 2021 The Author(s)
Place, publisher, year, edition, pages
Elsevier Ltd , 2021. Vol. 276, article id 114374
Keywords [en]
Composite sizing optimization, Hyperbolic function parametrization, Laminated composites, Multi-material optimization, Structural Optimization, Topology Optimization, Hyperbolic functions, Shape optimization, Topology, Discrete material optimizations, Discrete topology, Multi-material optimizations, Optimization function, Parametrizations, Shape functions, Structural optimisations, Topology optimisation
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:ri:diva-56006DOI: 10.1016/j.compstruct.2021.114374Scopus ID: 2-s2.0-85112835915OAI: oai:DiVA.org:ri-56006DiVA, id: diva2:1588253
Note
Funding details: Energimyndigheten, P48175-1; Funding text 1: This work is financed by the Swedish Energy Agency (Energimyndigheten) through Grant No. P48175-1, and is associated with the Swedish Electromobility Center 3 3 (SEC). Their support is gratefully acknowledged. The authors would also like to thank Krister Svanberg for providing his implementation of GCMMA on which our optimization solver is based.
2021-08-262021-08-262024-10-28Bibliographically approved