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Graph convolutional networks-driven multiscale topology optimization base on polygonal coarse-grid elements

delete2025-06-15
delete0
PRE
AI
S
Shengqiao Zhu
吕
吕军 (Jun Lv)
D
Di Wu
H
Haoming Yu
W
Weiyi Wang
Z
Zhesheng Zhang
Y
Yiling Xie
R
Renzhuo Zhao
DOI：10.1016/j.ijmecsci.2025.110500delete
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摘要

摘要

En 中文
• 数据驱动框架能够预测异质多边形子结构的数值基函数。 • 所设计的神经网络实现了卓越的预测精度和泛化能力。 • 训练好的代理模型能够适应按需目标，无需离线重新处理。 • 一种AI增强的设计范式展现出比传统拓扑优化更高的效率。

期刊

International Journal of Mechanical Sciences 封面图
International Journal of Mechanical Sciences
IF:
9.4
论文数:
1.0W
被引数:
4.5W

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