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Updated: Jun 29, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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通过合分子动力学和机器学习来加速Fe-C合金中的弹性性质预测

Sandesh Risal1, Navdeep Singh2, Yan Yao3,4

  • 1Department of Mechanical Engineering, University of Houston, Houston, TX 77204, USA.

Materials (Basel, Switzerland)
|April 9, 2024
PubMed
概括

高质量的材料属性数据很少,阻碍了机器学习 (ML) 模型的准确性. 这项研究使用分子动力学 (MD) 模拟和ML进行了广泛的Fe-C合金弹性特性数据,以改善预测.

关键词:
一个合适的MEAM.这是RF-MEAMAM.密度函数理论密度函数理论具有弹性特性,具有弹性特性.机器学习是机器学习.机械性能 机械性能 机械性能分子动力学分子动力学

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