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基于FEM方法和数据挖掘的V形复合结构的固化过程诱导变形的概率预测
Guangshuo Feng1, Bo Liu1,2
1School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Materials (Basel, Switzerland)
|July 27, 2024
概括
连续纤维增强复合材料的工艺诱导变形 (PID) 是不可预测的. 本研究使用有限元分析和数据挖掘来预测V形结构中的PID,提高制造精度.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 复合材料制造业 复合材料制造业
背景情况:
- 连续纤维增强复合材料具有高特异模量和强度,使其在工业中具有价值.
- 工艺诱导变形 (PID) 是一个关键的制造挑战,导致不可预测的零件变化.
- 准确预测PID对于质量控制和性能优化至关重要.
研究的目的:
- 在V形复合结构中开发PID的概率预测方法.
- 调查材料参数不确定性对PID的影响.
- 用实验数据验证预测的准确性.
主要方法:
- 在ABAQUS.中开发了一种连续合热化学机械有限元 (FE) 模型.
- 材料参数的不确定性被纳入了具有不同半径和厚度的V形结构.
- 在FE数据上训练了一个决策树模型,用于PID灵敏度分析和概率分布预测.
主要成果:
- 发现PID随着特定材料方向的热膨胀系数的增加而增加.
- 包含的角度的预测准确性与实验结果进行了验证.
- 数据挖掘方法证明了PID预测的高准确性和效率.
结论:
- 开发的FE和数据挖掘方法准确地预测了V形复合结构中的PID.
- 这种方法为工程应用提供了一个高效的计算选项.
- 了解PID驱动器对于提高复合材料制造工艺至关重要.
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