Dataset for Designing extrusion dies on the basis of eXplainable Artificial Intelligence
收藏doi.org2025-03-25 收录
下载链接:
http://doi.org/10.17632/dy97xr6t8h.1
下载链接
链接失效反馈官方服务:
资源简介:
This dataset contains the porthole die data used to develop a design support tool for aluminium extrusion porthole dies based on eXplainable IA.
The tool is useful for dies with 4 cavities and 4 ports per cavity.
Dataset includes the geometrical data related to 596 different ports from 88 first-trial 4 cavities and 4 ports per cavity dies.
In terms of the R² metric and the results obtained with the application examples, the results obtained with this ML-based model are significantly better than those of a previous model based on linear regression.
It also includes the results and geometries of the FEM simulations performed to validate the model.
本数据集收录了用于开发基于可解释人工智能(eXplainable IA)的铝合金挤出型材孔洞模具设计辅助工具的孔洞模具试验数据。该工具适用于每个模具腔室具有4个孔洞的模具。数据集包含了与88个首试模具的4个腔室和每个腔室4个孔洞相关的596个不同孔洞的几何数据。从R²指标及应用实例的结果来看,基于机器学习的本模型所取得的结果显著优于基于线性回归的先前模型。此外,还包括了用于验证模型的有效性的有限元模拟(FEM)的结果和几何形状。
提供机构:
doi.org



