On the efficiency of machine learning for fatigue assessment of post-processed additively manufactured AlSi10Mg
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
On the efficiency of machine learning for fatigue assessment of post-processed additively manufactured AlSi10Mg
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF FATIGUE
Volume 160, Issue -, Pages 106841
Publisher
Elsevier BV
Online
2022-03-15
DOI
10.1016/j.ijfatigue.2022.106841
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- The effects of shot peening, laser shock peening and ultrasonic nanocrystal surface modification on the fatigue strength of Inconel 718
- (2021) Erfan Maleki et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Fatigue performance and crack propagation behavior of selective laser melted AlSi10Mg in 0°, 15°, 45° and 90° building directions
- (2021) Zhongwei Xu et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Analysing the Fatigue Behaviour and Residual Stress Relaxation of Gradient Nano-Structured 316L Steel Subjected to the Shot Peening via Deep Learning Approach
- (2021) Erfan Maleki et al. METALS AND MATERIALS INTERNATIONAL
- Fatigue behaviour of notched laser powder bed fusion AlSi10Mg after thermal and mechanical surface post-processing
- (2021) Erfan Maleki et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- Application of artificial intelligence to optimize the process parameters effects on tensile properties of Ti-6Al-4V fabricated by laser powder-bed fusion
- (2021) Erfan Maleki et al. International Journal of Mechanics and Materials in Design
- Fatigue limit prediction and analysis of nano-structured AISI 304 steel by severe shot peening via ANN
- (2020) Erfan Maleki et al. ENGINEERING WITH COMPUTERS
- Very-high-cycle fatigue behavior of Ti-6Al-4V manufactured by selective laser melting: Effect of build orientation
- (2020) Guian Qian et al. INTERNATIONAL JOURNAL OF FATIGUE
- Optimization of Shot Peening Effective Parameters on Surface Hardness Improvement
- (2020) Erfan Maleki et al. METALS AND MATERIALS INTERNATIONAL
- Defects as a root cause of fatigue weakening of additively manufactured AlSi10Mg components
- (2020) Paolo Ferro et al. THEORETICAL AND APPLIED FRACTURE MECHANICS
- Fatigue strength assessment of “as built” AlSi10Mg manufactured by SLM with different build orientations
- (2020) S. Beretta et al. INTERNATIONAL JOURNAL OF FATIGUE
- Deep neural network approach to estimate biaxial stress-strain curves of sheet metals
- (2020) Akinori Yamanaka et al. MATERIALS & DESIGN
- Machine learning based fatigue life prediction with effects of additive manufacturing process parameters for printed SS 316L
- (2020) Zhixin Zhan et al. INTERNATIONAL JOURNAL OF FATIGUE
- Analyzing the mechano-bactericidal effect of nano-patterned surfaces on different bacteria species
- (2020) Erfan Maleki et al. SURFACE & COATINGS TECHNOLOGY
- A novel approach based on the elastoplastic fatigue damage and machine learning models for life prediction of aerospace alloy parts fabricated by additive manufacturing
- (2020) Zhixin Zhan et al. INTERNATIONAL JOURNAL OF FATIGUE
- Evaluation of the impact behaviour of AlSi10Mg alloy produced using laser additive manufacturing
- (2019) Luca Girelli et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- A statistical model of fatigue failure incorporating effects of specimen size and load amplitude on fatigue life
- (2019) Guian Qian et al. PHILOSOPHICAL MAGAZINE
- Microstructure of selective laser melted AlSi10Mg alloy
- (2019) Xihe Liu et al. MATERIALS & DESIGN
- Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives
- (2019) Xinbo Qi et al. Engineering
- Shot Peening Process Effects on Metallurgical and Mechanical Properties of 316 L Steel via: Experimental and Neural Network Modeling
- (2019) E. Maleki et al. METALS AND MATERIALS INTERNATIONAL
- Surface layer nanocrystallization of carbon steels subjected to severe shot peening: Analysis and optimization
- (2019) Erfan Maleki et al. MATERIALS CHARACTERIZATION
- The Effect of Stress Relief on the Mechanical and Fatigue Properties of Additively Manufactured AlSi10Mg Parts
- (2019) Mfusi et al. Metals
- Fatigue behavior prediction and analysis of shot peened mild carbon steels
- (2018) Erfan Maleki et al. INTERNATIONAL JOURNAL OF FATIGUE
- Additive manufacturing of metallic components – Process, structure and properties
- (2018) T. DebRoy et al. PROGRESS IN MATERIALS SCIENCE
- On the fatigue strength enhancement of additive manufactured AlSi10Mg parts by mechanical and thermal post-processing
- (2018) Sara Bagherifard et al. MATERIALS & DESIGN
- Influence of defects and as-built surface roughness on fatigue properties of additively manufactured Alloy 718
- (2018) Arun Ramanathan Balachandramurthi et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
- A deep neural network for classification of melt-pool images in metal additive manufacturing
- (2018) Ohyung Kwon et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Using deep neural network with small dataset to predict material defects
- (2018) Shuo Feng et al. MATERIALS & DESIGN
- Effect of surface roughness on corrosion fatigue performance of AlSi10Mg alloy produced by Selective Laser Melting (SLM)
- (2017) Avi Leon et al. MATERIALS CHARACTERIZATION
- Predicting protein–protein interactions from protein sequences by a stacked sparse autoencoder deep neural network
- (2017) Yan-Bin Wang et al. Molecular BioSystems
- Additive manufacturing of metals
- (2016) Dirk Herzog et al. ACTA MATERIALIA
- Metal Additive Manufacturing: A Review of Mechanical Properties
- (2016) John J. Lewandowski et al. Annual Review of Materials Research
- The metallurgy and processing science of metal additive manufacturing
- (2016) W. J. Sames et al. INTERNATIONAL MATERIALS REVIEWS
- Rapid Solidification: Selective Laser Melting of AlSi10Mg
- (2016) Ming Tang et al. JOM
- Additive manufacturing technologies: state of the art and trends
- (2015) Julien Gardan INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Formulation of bead width model of an SLM prototype using modified multi-gene genetic programming approach
- (2014) A. Garg et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis
- (2012) Jun Xiong et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Balling behavior of stainless steel and nickel powder during selective laser melting process
- (2011) Ruidi Li et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More