Investigating the impact of functional grading on mechanical performance for auxetic structures


Kenan H., Özen M., AZELOĞLU C. O.

Mechanics of Advanced Materials and Structures, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1080/15376494.2025.2541917
  • Dergi Adı: Mechanics of Advanced Materials and Structures
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: Auxetic structures, compression test, functionally graded structures, mechanical performance
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This study investigates auxetic structures, which exhibit a negative Poisson’s ratio due to their unique geometries, with a focus on the effects of functional grading on their mechanical performance. Unlike previous approaches that enhance auxetic behavior by adding new elements, this work adopts a functional grading strategy based on geometric variation to tailor mechanical properties. Three auxetic patterns—reentrant, reentrant combined-wall (RCW) honeycomb, and ellipse—were chosen for their design adaptability and suitability for functional grading. These patterns were redesigned using a geometric grading approach, fabricated via fused deposition modeling (FDM), and tested under compressive loading. The novelty of the study lies in the implementation of functional grading through geometry rather than material composition. The experimental results demonstrated that functionally graded models outperformed their uniform counterparts, particularly in the elastic–plastic region, with increases of 56% for the reentrant model, 35% for the RCW honeycomb, and 53% for the ellipse based on load carrying capacity. Moreover, the graded ellipse model achieved the highest energy absorption among the tested specimens. Functional grading also influenced deformation initiation, enabling more controlled structural behavior. These findings highlight the potential of geometric grading to enhance auxetic structures, offering promising insights for future design and optimization efforts.