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Sizing optimization and experimental characterization of a variable stiffness shape memory polymer filled honeycomb composite

Autor(en): ORCID
ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Smart Materials and Structures, , n. 4, v. 32
Seite(n): 045007
DOI: 10.1088/1361-665x/acbd77
Abstrakt:

Variable stiffness structures and materials have been considered for many applications, including active vibration control and shape morphing. With regards to shape morphing, variable stiffness materials and composites have been considered for reconfigurable skin materials in aerospace vehicles. Of the many concepts that have been developed for such applications, shape memory polymers (SMPs) are one such promising materials for shape morphing. SMPs exhibit both high modulus ratios and recoverable strains but suffer from a low overall modulus and often require reinforcements, such as honeycomb. This work investigates the design space of such honeycomb reinforced SMPs as variable stiffness materials. Unit cell finite element models are developed for the material, and parametric studies are completed for varying honeycomb cell geometries. A multiobjective, constrained Pareto front optimization is completed for two honeycomb material models and in two loading directions using selected sizing design variables. Pareto fronts are established, and cell geometries are selected and fabricated to experimentally verify the optimized model predictions. The results both predict and demonstrate the advantages of using honeycomb reinforcements for SMPs. Effective in-plane moduli as high as 45 GPa are predicted while achieving a change in modulus of 450X. Compared to existing reinforcement strategies for shape memory polymers, these composites exhibit favorable combinations of both high stiffness and high changes in stiffness with a high degree of tailorability through the honeycomb cell geometry and predicted performances that meet and exceed the state of the art.

Copyright: © 2023 Carson Squibb, Michael Philen
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10707651
  • Veröffentlicht am:
    21.03.2023
  • Geändert am:
    07.02.2024
 
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