工艺与制造英文2024被引 47
复合材料模具充填图案综合数据集用于工艺建模与预测
Comprehensive Composite Mould Filling Pattern Dataset for Process Modelling and Prediction
Boon Xian Chai, Jinze Wang, Thanh Kim Mai Dang, Mostafa Nikzad, Boris Eisenbart, Bronwyn Fox · Swinburne University of Technology
摘要整理
树脂传递模塑（RTM）工艺因其优异的制造效率和产品质量而受到学术界和工业界的广泛关注。特别是模具充填阶段的进展对确保增强纤维完全饱和至关重要。当代工艺仿真方法主要采用基于物理的方法来模拟复杂的树脂渗透现象，但计算成本高昂。因此，应用机器学习和数据驱动建模方法来降低工艺仿真成本具有重要意义。本研究以复合材料仪表板面板为案例，建立了包含不同注入位置下RTM工艺模具充填图案的综合数据集。阐述了数据集的问题描述和研究意义。该综合数据集的发布旨在降低复合材料成型工艺中机器学习研究的入门门槛，同时为未来研究中新开发算法和模型的评估提供标准化基准。
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