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TCD–statistics–machine learning framework for defect-controlled fatigue in recycled powder LPBF Inconel 718

delete2026-08-01
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OA
AI
L
L. Romanelli *
C
Ciro Santus
G
Giuseppe Macoretta
B
Bernardo Disma Monelli
H
Hossein Rajaei
C
Cinzia Menapace
M
M. Benedetti *
DOI:10.1016/j.tafmec.2026.105832delete
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Abstract

Abstract

En 中文
• Plain and V-notched specimens manufactured through Inconel 718 recycled powder. • FE simulations for the fatigue stress concentration factors of surface profiles. • FE and nonlinear surrogate models for pore fatigue stress concentration factors. • Incorporation of the size effect to account for highly stressed region dimensions. • Novel TCD-statistics-FE-surrogate framework for accurate fatigue strength prediction.
Keywords:
Laser powder bed fusion
Inconel 718
Recycled powder
Theory of critical distances
Defects
Surrogate models
Size effect
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Theoretical and Applied Fracture Mechanics cover
Theoretical and Applied Fracture Mechanics
IF:
5.6
Papers:
4.4K
Citations:
1.3W

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university of trento
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university of pisa
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