可预设负泊松比和弹性模量的超材料智能化设计和制造

超材料（Metamaterials）是指通过人工设计，实现超常物理性能的微结构阵列材料。作为新兴的人工微结构材料，其微观单元的几何构型设计在超材料的研究和应用中扮演了至关重要的角色，最终决定了超材料的宏观物理性能。然而，目前大部分超材料的研究遵循“设计-测试-分析”的正向研究方法。在针对具有特定性质或参数的微观结构进行逆向设计时，这种方法具有极大的局限性。鉴于此，亟需寻找一种能够实现预设性能的微结构逆向设计方法，以桥接超材料的理论设计与工业实际应用。

本文首先提出了一款新型三维拉胀与压扭耦合的超材料，以解决可重入结构在压缩过程中负泊松比不持续的问题。该结构将基础二维凸几何按照特定规则排列组装，赋予了非可重入结构负泊松比（Negative Poisson's Ratio, NPR）效应。采用实验和数值模拟相结合的分析方法，验证了所提出微结构单元的变形机理及性质预测模型。

为了使超材料的设计及性质预测一般化，本文采用移动可变形组件的拓扑优化与智能优化相结合的方法，进一步提出了可预设泊松比及弹性模量的超材料智能化设计方法（Intelligent Design System, IDS）。在有限元计算和实验测试下，优化所得超材料微结构的测试性能与预设相吻合，证明了性质预测模型的准确性以及加工制造的可靠性。此外，将提出的方法整合成便携式可执行程序，方便迁移使用。最后，建立了多目标优化下的模糊数学模型，明确了IDS许可预设性能的范围边界，以供使用者提前预知收敛情况。除此之外，还利用IDS逆向设计可吸收振动能量的超材料，结合数值分析验证泊松比及体积分数对吸能效应的影响，证实了该设计方法在工业应用中的有效性。

研究结果表明，所提出的设计方法有效地沟通了力学超材料理论设计及工业应用，显著提高了超材料的设计效率，并为非专业人士应用超材料提供了便利。通过简化设计流程达到降低技术门槛的目的，不仅为超材料的设计提供了大量的数据库，还推动了超材料技术的广泛应用。

Metamaterials are microstructured arrays of materials that achieve extraordinary physical properties through artificial design. As emerging artificial microstructured unit materials, the design of their unit geometry configuration and ordering microscopic plays a crucial role in the research and application of metamaterials, and ultimately determines the macroscopic physical properties of metamaterials. However, most of the existing research on metamaterials follows the forward research path of design-test-analysis, which cannot realize the reverse design of microstructures for specific functions or parameters. In view of this, there is an urgent need to find a method that can predefine the properties of metamaterials and design microstructural units through reverse engineering to bridge the gap between theoretical design of metamaterials and practical industrial applications.

This thesis presents a novel approach to designing negative Poisson's ratio (NPR) metamaterials, culminating in the development of a three-dimensional tensile and compression-torsion coupled metamaterial based on this innovative design strategy. The methodology hinges on assembling two-dimensional structures that imparts an NPR effect to the non-reentrant structure. The authors validate the deformation mechanism and the Poisson's ratio prediction model of their proposed microstructural unit through a combination of experimental and numerical analyses. Advancing further, the thesis introduces an intelligent design system (IDS) for metamaterials with pre-defined properties. This system utilizes a topology optimization method for movable morphable components (MMC), integrated with an intelligent optimization algorithm, thus broadening the scope of reverse design and property prediction for metamaterials. By employing this method, metamaterials with customizable Poisson's ratios and Young's moduli are developed. The precision of the predictions and the reliability of the fabrication processes are corroborated through finite element analysis and experimental validation. Moreover, the authors have packaged the IDS into a software and established a fuzzy model under a multi-objective optimization framework. IDS provides users with boundaries on the predictable performance range of the design system, offering valuable guidance. Finally, IDS was used to carry out the reverse design of the vibration-absorbing metamaterials, which was verified using numerical analysis to confirm the effectiveness of the design method in industrial applications.

The results show that the IDS effectively links up the theoretical design and industrial application of metamaterials, greatly improves the design efficiency of metamaterials, and facilitates the application of metamaterials by non-specialists.

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