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#machine learning Preprint Sep 2026

Physics-based prediction, uncertainty quantification and decision-making for IN718 crystallographic texture intensity across LPBF defocus regimes

Reliable prediction of crystallographic texture in laser powder bed fusion is critical for linking process conditions with anisotropic response and for qualification. However, black-box models may fail under shift and cannot distinguish weak data support from loss of physical validity. This study develops a two-stage p...

Yi-Sheng Lu, John Riris, Jie Song et al. · 0 citations
Open access Aug 2026

Mechanistic modeling of strengthening and stress corrosion cracking in LPBF SS 316L-AL2O3 metal matrix nanocomposites

A microstructure-resolved electro-chemo-mechanical framework is developed to investigate strengthening and stress corrosion cracking (SCC) in laser powder bed fusion (LPBF) 316L stainless steel reinforced with Al2O3 ceramic nanoparticles. The framework, implemented in the MOOSE finite element platform, couples three ph...

Aqib Zahoor, Jie Song, Yao Fu · 0 citations

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