Machine Learning of Fatigue Strength of Hybrid and Additively Manufactured Aluminum Alloys in VHCF Regime-Reference-Cited by-同舟云学术

Machine Learning of Fatigue Strength of Hybrid and Additively Manufactured Aluminum Alloys in VHCF Regime

Published:2023-05-01 Issue: Volume: Page:262-276
ISSN:
Container-title:Advances in Accelerated Testing and Predictive Methods in Creep, Fatigue, and Environmental Cracking
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Author:

Awd Mustafa¹^ORCID,Walther Frank¹^ORCID

Affiliation:

1. TU Dortmund University, NRW, D-44227, DE

Publisher

ASTM International

Reference34 articles.

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2. J. O. Milewski, Additive Manufacturing of Metals: From Fundamental Technology to Rocket Nozzles, Medical Implants, and Custom Jewelry (Cham, Switzerland: Springer International, 2017).

3. Evaluation of Surface/Interface Quality, Microstructure and Mechanical Properties of Hybrid Additive-Subtractive Aluminium Parts;Bhaduri;CIRP Annals,2019

4. AIMS: A Metal Additive-Hybrid Manufacturing System: System Architecture and Attributes;Manogharan;Procedia Manufacturing,2015

5. A Novel Method for Additive/Subtractive Hybrid Manufacturing of Metallic Parts;Du;Procedia Manufacturing,2016

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