用于加成制造哈氏合金 X 超级合金疲劳寿命预测的多物理信息集成神经网络

IF 10.2 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Virtual and Physical Prototyping Pub Date : 2024-07-07 DOI:10.1080/17452759.2024.2368652

Haijie Wang, Bo Li, Liming Lei, Fuzhen Xuan

引用次数: 0

摘要

神经网络固有的 "黑箱 "特性使疲劳寿命预测的物理可解释性面临挑战，导致预测结果在物理上不一致。在 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-physics information-integrated neural network for fatigue life prediction of additively manufactured Hastelloy X superalloy

The inherent ‘black-box’ characteristic of neural networks renders the physical interpretability of fatigue life prediction challenging, resulting in physically inconsistent prediction results. In ...

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来源期刊

Virtual and Physical Prototyping Engineering-Industrial and Manufacturing Engineering

CiteScore

13.60

自引率

6.60%

发文量

期刊介绍： Virtual and Physical Prototyping (VPP) offers an international platform for professionals and academics to exchange innovative concepts and disseminate knowledge across the broad spectrum of virtual and rapid prototyping. The journal is exclusively online and encourages authors to submit supplementary materials such as data sets, color images, animations, and videos to enrich the content experience. Scope: The scope of VPP encompasses various facets of virtual and rapid prototyping. All research articles published in VPP undergo a rigorous peer review process, which includes initial editor screening and anonymous refereeing by independent expert referees. This ensures the high quality and credibility of published work.