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Updated: Mar 15, 2026

Surrogate Model Development for Digital Experiments in Welding
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Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

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对一个过程参数驱动的深度学习预测模型的研究,用于在轴接中的多物理场

Chaolong Yang1, Zhiqiang Xu2, Feiting Shi3,4

  • 1College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China.

Materials (Basel, Switzerland)
|March 14, 2026
PubMed
概括

这项研究开发了机器学习模型,用于预测大型轮轴的接质量. 多层感知器 (MLP) 模型在预测温度,变形和残余应力方面取得了很高的准确性,超过了传统方法.

关键词:
在MLP深度学习模型中,变形变形的情况大的法兰轴轴.剩余压力是一种残留压力.温度的温度的温度的温度的温度.接过程参数 接过程参数

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