This study explores advanced material engineering through the novel optimization of geometric parameters of a re-entrant honeycomb auxetic unit cell for superior mechanical properties and energy absorption. The Euler-Bernoulli beam theory is utilized for deriving equations for mechanical properties tailored to this configuration. The primary focus of optimization is achieving a negative Poisson’s ratio, enhancing overall mechanical performance by increased values of absorbed energy, suiting its widespread applications and then by finite element modeling and analysis, simulations revealing a significant improvement in the considered factors are performed. This research contributes to materials science and structural design by showcasing a novel approach to tailor mechanical properties through unit cell parameter optimization, highlighting its innovative applications in engineering. In conclusion, this work demonstrates the feasibility and efficacy of optimization with the use of a multi-objective genetic algorithm for enhanced mechanical properties, with enhancements in \(\frac{E_x}{E_s}\) , \(\nu _{xy}\) and increased energy absorption up to 64%, offering valuable information for advances in material science and engineering.

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Optimizing Re-entrant Honeycomb Auxetic Unit Cell Structure for Superior Mechanical Properties for Practical Applications

  • Anurag Balayan,
  • Stuti Dwivedi,
  • Navdeep Malik,
  • Amanpreet Singh Whan,
  • Rajnish Mallick,
  • Pankaj Kumar,
  • Bisheshwar Haorongbam,
  • Anshul Sharma,
  • Manoj Sahni,
  • Kusum Meena

摘要

This study explores advanced material engineering through the novel optimization of geometric parameters of a re-entrant honeycomb auxetic unit cell for superior mechanical properties and energy absorption. The Euler-Bernoulli beam theory is utilized for deriving equations for mechanical properties tailored to this configuration. The primary focus of optimization is achieving a negative Poisson’s ratio, enhancing overall mechanical performance by increased values of absorbed energy, suiting its widespread applications and then by finite element modeling and analysis, simulations revealing a significant improvement in the considered factors are performed. This research contributes to materials science and structural design by showcasing a novel approach to tailor mechanical properties through unit cell parameter optimization, highlighting its innovative applications in engineering. In conclusion, this work demonstrates the feasibility and efficacy of optimization with the use of a multi-objective genetic algorithm for enhanced mechanical properties, with enhancements in \(\frac{E_x}{E_s}\) , \(\nu _{xy}\) and increased energy absorption up to 64%, offering valuable information for advances in material science and engineering.