接近同位素,极度刚性,连续的3D机械元材料序列使用隐式神经表示
Yunkai Zhao1, Lili Wang1, Xiaoya Zhai1
1Department of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|November 27, 2024
概括
研究人员使用拓优化和数据驱动设计开发了具有极度刚性的连续机械元材料序列. 这些新型材料在广泛的密度范围内实现了近乎理论性的性能,克服了以前的限制.
科学领域:
- 材料科学与工程 材料科学与工程
- 机械工程 机械工程
- 计算设计的计算设计.
背景情况:
- 机械超材料通过量身定制的密度分布提供独特的特性.
- 设计连续序列,在所有方向上都接近理论极限的刚性是具有挑战性的.
- 现有的设计往往无法在中高相对密度下保持高性能.
研究的目的:
- 提出新的,连续的3D机械元材料序列,具有接近同位素的和极端的刚性.
- 为了在广泛的密度范围 (0.2-1) 中实现接近理论极限的性能.
- 使用隐式神经函数,为不断变化的密度引入无分辨率表示.
主要方法:
- 结合拓优化与数据驱动的设计方法.
- 开发了三种不同的近同otropic,极度刚性的元材料序列.
- 利用隐式神经函数用于连续密度表示.
主要成果:
- 在最不利的方向实现了超过98%的哈辛-施特里克曼上界.
- 在0.2-1的相对密度范围内表现出高性能,优于之前的设计.
- 实验验证证了拟议序列的可制造性和高刚性.
结论:
- 提出的方法成功地产生了具有异常刚性的连续机械元材料序列.
- 隐式神经函数使无分辨率,不断变化的密度用于先进的元材料设计.
- 这些发现推动了高性能机械超材料的设计和应用.
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