使用交互式纤维复合材料的形状记忆合金材料模型的调查和验证
Achyuth Ram Annadata1, Aline Iobana Acevedo-Velazquez2, Lucas A Woodworth3
1Institute of Textile Machinery and High Performance Material Technology, TU Dresden, 01062 Dresden, Germany.
Materials (Basel, Switzerland)
|March 13, 2024
概括
这项研究验证了伍德沃思和卡利斯克 (WK) 形状记忆合金 (SMA) 模型的适应性曲结构. WK模型准确地预测了交互式纤维复合材料 (IFRC) 中的SMA行为.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 计算建模 计算建模
背景情况:
- 智能系统需要适应性曲结构,以增强人机交互.
- 交互式纤维复合材料 (IFRC) 使用智能材料,特别是形状记忆合金 (SMA),作为执行器.
- 精确的SMA行为建模对于优化其多样化的应用至关重要.
研究的目的:
- 为了研究伍德沃思和卡利斯克 (WK) 的现象学构成性SMA材料模型.
- 为了解决Souza和Auricchio (SA) SMA模型在处理不规则几何形状的预拉伸方面的局限性.
- 通过IFRC结构中观察到的变形来验证WK模型的性能.
主要方法:
- 研究了WK SMA材料模型.
- 在IFRC结构中观察到的利用变形作为参考.
- 在ANSYS中使用SA SMA材料模型对WK模型与模拟模型进行了验证.
主要成果:
- WK SMA 材料模型在适用于不规则的 SMA 线材配置文件的预拉伸方面表现出灵活性.
- 验证证实了WK模型的可靠性和准确性,与IFRC应用的SA模型相比.
- 该研究建立了对WK模型的信任,用于基于SMA的系统中的预测分析.
结论:
- WK SMA 材料模型为模拟复杂的 SMA 行为提供了可行的解决方案,特别是在 IFRC 应用中.
- 使用经过验证的WK模型进行准确的预测分析,有助于开发先进的自适应曲结构.
- 这项研究有助于智能材料和智能系统设计的进步.
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