Torsional damage analysis of metallic materials using simulation-guided defect assessment

This study presents an integrated assessment of torsional damage in selectively laser-melted 316L stainless steel, AlSi10Mg aluminium alloy, and Ti–6Al–4V titanium alloy, combining mechanical testing, finite-element interpretation, post-fracture laser-confocal microscopy, and instance segmentation of fracture-surface discontinuities. The torsion series comprised 2, 10, and 3 independent specimens, with mean maximum torques of \\(56.5 \\pm 0.7\\) , \\(25.4 \\pm 2.0\\) , and \\(76.3 \\pm 4.2\\) N m, and corresponding conditional torsional stresses of \\(659.5 \\pm 6.4\\) , \\(227.3 \\pm 17.2\\) , and \\(955.3 \\pm 50.9\\) MPa. Tensile tests provided additional context, with 0.2% proof stresses of \\(552.8 \\pm 33.8\\) , \\(161.8 \\pm 2.3\\) , and \\(911.6 \\pm 183.9\\) MPa, and ultimate tensile strengths of \\(680.8 \\pm 46.2\\) , \\(251.9 \\pm 3.2\\) , and \\(1127.1 \\pm 37.3\\) MPa. Post-fracture microscopy yielded 75 original images and 1125 tiles. A physical-specimen split (9/3/3 train/validation/test) prevented data leakage. Preliminary YOLOv8n-seg diagnostics gave a maximum mask F1 of 0.68 and AP \\(_{50}\\) of 0.629, but these are exploratory due to missing per-specimen predictions. Finite-element results are treated qualitatively, as model records lack complete post-yield calibration, mesh-convergence history, and synchronized torque–twist data. The workflow separates measured quantities, numerical interpretation, and image-based evidence, identifying the data required for a fully validated torsional constitutive model.