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<p>In previous designs, energy-absorbing structures typically relied on plastic deformation to absorb the energy generated by impacts, which means that such structures could only be used as single-use energy absorption solutions. Therefore, the development of reusable energy-absorbing structures has become a focus of current research. Due to their unique&#xa0;properties,&#xa0;multistable mechanical metamaterials have emerged as one of the materials capable of achieving this goal. This paper proposes a snap-fit mechanical metamaterial with programmable and reusable features. The mechanical performance of the snap-fit structure is studied through theoretical and numerical simulation. The results indicate that the designed structure exhibits excellent energy absorption performance. Additionally, multi-objective optimization is conducted using the Response Surface Method and the Non-dominated Sorting Genetic Algorithm (NSGA-II), resulting in optimal design parameters obtained through the Pareto solution set. By adjusting the structural parameters, programmable design can be carried out, offering new design approaches for applications such as robotics, impact protection devices, and instrument packaging.</p>

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Design and Optimization of a Snap-Fit Structure for Energy Absorbing

  • 期刊论文

  • 发表日期：

    2025年3月25日

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  • Jin Wu,
  • Huan He,
  • Guoping Chen,
  • Yuexin Wang,
  • Zhiyong Qiu

摘要

In previous designs, energy-absorbing structures typically relied on plastic deformation to absorb the energy generated by impacts, which means that such structures could only be used as single-use energy absorption solutions. Therefore, the development of reusable energy-absorbing structures has become a focus of current research. Due to their unique properties, multistable mechanical metamaterials have emerged as one of the materials capable of achieving this goal. This paper proposes a snap-fit mechanical metamaterial with programmable and reusable features. The mechanical performance of the snap-fit structure is studied through theoretical and numerical simulation. The results indicate that the designed structure exhibits excellent energy absorption performance. Additionally, multi-objective optimization is conducted using the Response Surface Method and the Non-dominated Sorting Genetic Algorithm (NSGA-II), resulting in optimal design parameters obtained through the Pareto solution set. By adjusting the structural parameters, programmable design can be carried out, offering new design approaches for applications such as robotics, impact protection devices, and instrument packaging.