In Situ Nondestructive Fatigue‐Life Prediction of Additive Manufactured Parts by Establishing a Process–Defect–Property Relationship-Reference-Cited by-同舟云学术

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In Situ Nondestructive Fatigue‐Life Prediction of Additive Manufactured Parts by Establishing a Process–Defect–Property Relationship

Published:2021-10-29 Issue:12 Volume:3 Page:2000268
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Seifi Seyyed Hadi¹,Yadollahi Aref²,Tian Wenmeng¹,Doude Haley³,Hammond Vincent H.⁴,Bian Linkan¹^ORCID

Affiliation:

1. Department of Industrial and Systems Engineering Mississippi State University 479-2 Hardy Road, 260 McCain Hall Mississippi State MS 39762 USA

2. Department of Mechanical Engineering University of South Alabama 150 Student Services Dr Mobile AL 36688 USA

3. Center for Advanced Vehicular Systems Mississippi State University 200 Research Blvd Starkville MS 39759 USA

4. Weapons and Materials Research Directorate US Army Research Laboratory Aberdeen Proving Ground Maryland 21005 USA

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202000268

Reference71 articles.

1. An overview of Direct Laser Deposition for additive manufacturing; Part I: Transport phenomena, modeling and diagnostics

2. Automatic fault detection for laser powder-bed fusion using semi-supervised machine learning

3. Additive manufacturing of fatigue resistant materials: Challenges and opportunities

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1. Review on methodologies of fatigue property prediction for carbon fiber reinforced polymer;Composites Part B: Engineering;2024-09

2. Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition;Journal of Manufacturing Science and Engineering;2024-05-21

3. Predicting the Mechanical Behavior of Additively Manufactured Mechanical Metamaterials Using Point Cloud Representation Learning;Journal of Computing and Information Science in Engineering;2024-02-05

4. In-Situ Fatigue Life Prediction with Simulated Defects for Additive Manufacturing Process;The Minerals, Metals & Materials Series;2024

5. Prediction of Coefficient of Friction and Wear Rate of Stellite 6 Coatings Manufactured by LMD Using Machine Learning;Lecture Notes in Networks and Systems;2024

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