I-FENN with DeepONets: Accelerating simulations in coupled multiphysics problems

doi:10.1016/j.cma.2025.118645

2025-12-23

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DOI：10.1016/j.cma.2025.118645

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摘要

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• 我们提出了一种基于GRU-DeepONet的I-FENN框架，用于多物理场仿真，并在热弹性和孔隙弹性中进行了验证。 • 一种改进的MIONet能够处理多个输入函数，并采用了一种新的策略来对不同的分段强制施加边界条件。 • 三个案例研究验证了该框架对未见过的加载场景的泛化能力。 • 该方法适用于二维和三维，与网格无关且可扩展，这一点通过网格细化测试得到确认。 • 实现利用deal.II库进行高效的HPC部署，并优化了数据传输和内存使用。

期刊

Computer Methods in Applied Mechanics and Engineering

IF:

7.3

论文数:

1.3W

被引数:

5.6W

机构

New York University

学者数:

4.4W

论文数: 3.9W

被引数: 5.8W

New York University Abu Dhabi

学者数:

2.1K

论文数: 1.5K

被引数: 3.3K

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