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Defect sensitivity and fatigue design: Deterministic and probabilistic aspects in AM metallic materials
Fatigue performance in both traditional and additively manufactured materials is severely
affected by the presence of defects, which deserve special attention to ensure the in-service …
affected by the presence of defects, which deserve special attention to ensure the in-service …
Fatigue performance of metal additive manufacturing: A comprehensive overview
H Javidrad, B Koc, H Bayraktar, U Simsek… - Virtual and Physical …, 2024 - Taylor & Francis
Fatigue life assessment of metal additive manufacturing (AM) products has remained
challenging due to the uncertainty of as–built defects, heterogeneity of the microstructure …
challenging due to the uncertainty of as–built defects, heterogeneity of the microstructure …
Physics-guided machine learning frameworks for fatigue life prediction of AM materials
Introducing random defects is a type of the dominant causes of fatigue scatter of additive
manufacturing (AM) materials. The fracture mechanics-based models oversimplify the …
manufacturing (AM) materials. The fracture mechanics-based models oversimplify the …
Defect driven physics-informed neural network framework for fatigue life prediction of additively manufactured materials
Additive manufacturing (AM) has attracted many attentions because of its design freedom
and rapid manufacturing; however, it is still limited in actual application due to the existing …
and rapid manufacturing; however, it is still limited in actual application due to the existing …
Size effect in fatigue modelling of defective materials: Application of the calibrated weakest-link theory
Fatigue life prediction is critical for the design of engineering components made from
defective materials. Not only do these imperfections show a detrimental effect on the fatigue …
defective materials. Not only do these imperfections show a detrimental effect on the fatigue …
Fatigue-life prediction of additively manufactured metals by continuous damage mechanics (CDM)-informed machine learning with sensitive features
H Wang, B Li, FZ Xuan - International Journal of Fatigue, 2022 - Elsevier
Additive manufacturing (AM) process-induced defects make the fatigue life prediction of AM-
built parts challenging. A machine learning (ML) framework based on sensitive features and …
built parts challenging. A machine learning (ML) framework based on sensitive features and …
Stress gradient effect in metal fatigue: Review and solutions
SP Zhu, WL Ye, JAFO Correia, AMP Jesus… - Theoretical and Applied …, 2022 - Elsevier
Under external loadings, notched components always show varying degrees of stress
concentration. Accordingly, different kinds of approaches have been presented to …
concentration. Accordingly, different kinds of approaches have been presented to …
Mechanical, fracture-deformation, and tribology behavior of fillers-reinforced sisal fiber composites for lightweight automotive applications
PK Miniappan, S Marimuthu, SD Kumar… - Reviews on Advanced …, 2023 - degruyter.com
The main focus of this study is on the effects of fly ash, basalt powder, and tungsten carbide
(WC) on the mechanical (tensile strength, flexural strength, impact strength, and Shore D …
(WC) on the mechanical (tensile strength, flexural strength, impact strength, and Shore D …
[HTML][HTML] An analysis of microstructural morphology, surface topography, surface integrity, recast layer, and machining performance of graphene nanosheets on Inconel …
K Paswan, S Sharma, SP Dwivedi… - Journal of Materials …, 2023 - Elsevier
Inconel 718 finds extensive applications in the aviation and aerospace industries,
particularly in the manufacturing of jet engines and high-speed airframe components like …
particularly in the manufacturing of jet engines and high-speed airframe components like …
[HTML][HTML] Enhancement in wear-resistance of 30MNCRB5 boron steel-substrate using HVOF thermal sprayed WC–10% Co–4% Cr coatings: a comprehensive research …
The rotavator blade, a part of an agricultural equipment rotavator, is used for the soil bed
preparation. These blades have direct interaction with soil in agricultural land. Bad, rocky …
preparation. These blades have direct interaction with soil in agricultural land. Bad, rocky …