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复合层材的优化,以处理诱导的变形和曲自身价值,基于改进的遗传算法
Qingchuan Liu1, Xiaodong Wang1, Zhidong Guan1
1School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
Materials (Basel, Switzerland)
|January 25, 2025
概括
这项研究优化了复合板材结构,以减少制造缺陷,如弹角度,并提高抗性. 一个改进的自适应基因算法 (IAGA) 显著提高了结构性能和可制造性.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 计算力学 计算力学 计算力学
背景情况:
- 复合层板和硬化板由于不同层面方向而表现出热残余应力和加工诱导的变形 (PID).
- 刚性面板中的几何特征和层方向不匹配加剧了PID,影响了结构完整性.
- 缓解这些问题对于提高复合结构的性能和可制造性至关重要.
研究的目的:
- 通过使用改进的自适应基因算法 (IAGA) 提出和验证一个多目标堆叠优化策略.
- 为了最大限度地减少加工诱导的变形 (PID),特别是弹入角,在复合层结构的L形硬化剂中.
- 为了提高复合材料硬化板的结构性能,特别是抗性.
主要方法:
- 采用粘弹性构成模型来准确模拟硬化过程中的模量变化.
- 开发并应用了一种改进的自适应基因算法 (IAGA),用于多目标优化叠加序列.
- 优化了复合板结构中L形硬化剂的层叠序列.
主要成果:
- 实现了弹入角的显著降低至0.12°,比对称平衡设计提高了50%.
- 通过优化堆叠序列,增强了20%的曲折固有值.
- 证明了IAGA对NSGA的优势,帕雷托解决方案多样性增加了三倍,并减少了70%的融合时间.
结论:
- 不对称的层设计有效地减轻复合硬化板中的残余应力和PID.
- 拟议的IAGA为优化复合板结构提供了一个强大而高效的框架.
- 这些发现有助于提高先进复合材料的结构性能和可制造性.
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