Methods for evaluating fracture patterns of polycrystalline materials based on the parameter analysis of fatigue striations: A review

MethodsX, Год журнала: 2024, Номер 13, С. 102989 - 102989

Опубликована: Окт. 11, 2024

Язык: Английский

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Experimental Study and Random Forest Machine Learning of Surface Roughness for a Typical Laser Powder Bed Fusion Al Alloy

Metals, Год журнала: 2024, Номер 14(10), С. 1148 - 1148

Опубликована: Окт. 8, 2024

Surface quality represents a critical challenge in additive manufacturing (AM), with surface roughness serving as key parameter that influences this aspect. In the aerospace industry, of aviation components is very important parameter. study, typical Al alloy, AlSi10Mg, was selected to study its when using Laser Powder Bed Fusion (LPBF). Two Random Forest (RF) models were established predict upper printed samples based on laser power, scanning speed, and hatch distance. Through it found two-dimensional (2D) RF model successful predicting values experimental data. The best minimum 2.98 μm, which known without remelting. More than two-thirds had less 7.7 μm. maximum 11.28 And coefficient determination (R2) 0.9, also suggesting 3D-printed alloys can be predicted ML approaches such model. This helps understand relationship between printing parameters print better quality.

Язык: Английский

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Roughness measurement results evaluation of 6082 aluminium alloy specimens after fatigue bending tests

Precision Engineering, Год журнала: 2024, Номер 91, С. 77 - 94

Опубликована: Сен. 10, 2024

Язык: Английский

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Study of vibrational surface topography measurement errors of LPBF Inconel 718 alloy after shot peening process

Measurement, Год журнала: 2024, Номер unknown, С. 116434 - 116434

Опубликована: Дек. 1, 2024

Язык: Английский

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Study of etched surface topography with the compensation of contactless vibrational measurement errors

Measurement, Год журнала: 2024, Номер 242, С. 116218 - 116218

Опубликована: Ноя. 15, 2024

Язык: Английский

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