Multi-physics information-integrated neural network for fatigue life prediction of additively manufactured Hastelloy X superalloy-Reference-Cited by-同舟云学术

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

Published:2024-07-07 Issue:1 Volume:19 Page:
ISSN:1745-2759
Container-title:Virtual and Physical Prototyping
language:en
Short-container-title:Virtual and Physical Prototyping

Author:

Wang Haijie¹,Li Bo¹²,Lei Liming³⁴,Xuan Fuzhen¹²

Affiliation:

1. School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, People’s Republic of China

2. Shanghai Collaborative Innovation Centre for High-end Equipment Reliability, Shanghai, People’s Republic of China

3. AECC Commercial Aircraft Engine Co., Ltd, Shanghai, People’s Republic of China

4. TaiHang Laboratory, Chengdu, People’s Republic of China

Funder

National Natural Science Foundation of China

Equipment Pre-Research Sharing Technology Key Project

Fundamental Research Funds for the Central Universities in China

Pre-Research Project of Civil Aerospace Technology

National Key R&D Program of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17452759.2024.2368652

Reference36 articles.

1. Metal additive manufacturing in aerospace: A review

2. Additive manufacturing and characterization of high temperature thermoplastic blends for potential aerospace applications

3. Fatigue life estimation of additively manufactured Ti-6Al-4V: Sensitivity, scatter and defect description in Damage-tolerant models

4. Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling

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