Since composite components have been used in many fields with high-performance requirements, their quality is always of great concern. During production, improving temperature uniformity of the mold, which has close contact with the composites, is critical for reducing component deformation. However, the bottleneck is realizing the rapid and accurate prediction for the mold temperature distribution. Therefore, this paper designs a new hybrid modeling method for mold temperature prediction, which is driven by both physical and data models. The proposed method is applied in a case study of quality assurance for a plate component. Its advantages are also validated.

中文翻译：

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一种面向复合材料部件质量保证的物理模型和数据驱动的混合预测方法

由于复合材料部件已被用于许多具有高性能要求的领域，其质量一直备受关注。在生产过程中，提高与复合材料紧密接触的模具的温度均匀性对于减少部件变形至关重要。然而，瓶颈在于实现对模具温度分布的快速准确预测。因此，本文设计了一种新的模具温度预测混合建模方法，该方法由物理模型和数据模型共同驱动。所提出的方法应用于板件质量保证的案例研究。它的优势也得到了验证。