FG Porous Beam Data
收藏arXiv2025-09-30 收录
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https://github.com/eshaghi-ms/DeepNetBeam
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资源简介：
该数据集是通过采用不同的科学机器学习方法对功能梯度多孔梁进行分析所生成的数据。数据集涵盖了物理学信息神经网络（PINN）、深度能量方法（DEM）以及神经算子方法等不同方法的结果，并通过与解析和数值解进行验证。该任务旨在预测在任意条件下，具有功能梯度材料的孔隙梁的响应情况。
This dataset is generated by analyzing functionally graded porous beams using various scientific machine learning methods. The dataset includes results from different approaches such as Physics-Informed Neural Networks (PINN), Deep Energy Method (DEM), and neural operator methods, and is validated against analytical and numerical solutions. The task aims to predict the response of functionally graded porous beams under arbitrary conditions.
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