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U-PolyConformer: Spatiotemporal machine learning for microstructure engineering
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DOI：10.1016/j.ijplas.2025.104597.png)
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摘要
En 中文
• 提出了一种新颖的时空CNN-Transformer机器学习框架。
• 首次提出能够捕捉任意加载条件下全场应力与应变演化的框架。
• 具有强大的泛化能力；能够准确捕捉训练分布外的加载条件、微观结构和硬化行为。
• 采用了一种新颖的微观结构优化框架，通过延缓局部化来提升成形性。
Keyword:
Crystal plasticity finite element method
machine learning
Localized Deformation
Formability
Microstructure Engineering
AI总结
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期刊
IF:
12.8
论文数:
4.1K
被引数:
2.5W
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引用论文
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