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This paper presents the dynamic mechanical characterization of a honeycomb-shaped meta-material. This meta-material is developed using 3D printing techniques, using a composite based on bio-sourced and biodegradable materials, in this case, polylactic acid reinforced with wood flour fibers (PLA/wood flour). The study focused on analyzing the effects of 3D printing parameters such as printing velocity, nozzle temperature, and density, highlighting its anti-trichiral performance. The influence of the three factors is studied by using the Dynamic Mechanical Analyzer (DMA). The storage modulus, loss modulus, and tangent delta tests were carried out on this architecture as a function of these printing parameters. A Dynamic variation of Young’s modulus as a function of temperature is presented. Artificial neural network (ANN) is used for training and optimization purposes.

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Exploration of 3D Printed Anti-trichiral Meta-materials Based on PLA/Wood Flour Bio-composites Using Dynamic Mechanical Analysis and Artificial Neural Networks (ANN) Technique

  • 会议论文

  • 发表日期：

    2025年

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  • Mondher Nasri,
  • Mohamed Toumi Nasri,
  • Badreddine Larbi,
  • Houda Khaterchi,
  • Salah Hamzi,
  • Ali Zghal,
  • Olivier Dalverny,
  • Amir Ben Rhouma

摘要

This paper presents the dynamic mechanical characterization of a honeycomb-shaped meta-material. This meta-material is developed using 3D printing techniques, using a composite based on bio-sourced and biodegradable materials, in this case, polylactic acid reinforced with wood flour fibers (PLA/wood flour). The study focused on analyzing the effects of 3D printing parameters such as printing velocity, nozzle temperature, and density, highlighting its anti-trichiral performance. The influence of the three factors is studied by using the Dynamic Mechanical Analyzer (DMA). The storage modulus, loss modulus, and tangent delta tests were carried out on this architecture as a function of these printing parameters. A Dynamic variation of Young’s modulus as a function of temperature is presented. Artificial neural network (ANN) is used for training and optimization purposes.