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Energy Coupling Mechanisms and Scaling Behavior Associated with Laser Powder Bed Fusion Additive Manufacturing
Author(s) -
Ye Jianchao,
Khairallah Saad A.,
Rubenchik Alexander M.,
Crumb Michael F.,
Guss Gabe,
Belak Jim,
Matthews Manyalibo J.
Publication year - 2019
Publication title -
advanced engineering materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 114
eISSN - 1527-2648
pISSN - 1438-1656
DOI - 10.1002/adem.201900185
Subject(s) - materials science , laser , molar absorptivity , laser power scaling , inconel 625 , absorption (acoustics) , inconel , optics , radius , specific energy , composite material , thermodynamics , alloy , physics , computer security , computer science
In situ optical absorptivity measurements are carried out to clarify the physics of the laser‐material interactions involved and to validate both finite element and analytical models describing laser powder bed fusion processing. Absorption of laser energy is evaluated directly using precise calorimetry measurements and compared to melt pool depths for common structural metal alloys (Ti‐6Al‐4V, Inconel 625, and stainless steel 316L) as a function of incident laser power, scan velocity and laser beam diameter. Changes in both absorptivity and melt pool depths for all materials are found to vary strongly across the conduction‐keyhole mode threshold. A hydrodynamic finite element model is coupled to a ray‐tracing‐based absorptivity model, yielding excellent agreement with the experimental results and elucidating additional physics. The experimental results are further analyzed using normalized enthalpy ( β ) and normalized thermal diffusion length ( L* th ) relations and demonstrate that the normalized melt pool depth ( d* = d/a , where d is melt pool depth and a is beam radius) is proportional to βL* th , while absorptivity follows an asymptotic exponential function against βL* th . Expressions for melt pool depth and laser absorptivity across different materials and laser scan systems are derived and thus provide useful tools to accelerate the optimization of laser processing parameters for metal 3D printing processes.