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In-situ full-field mapping of melt flow dynamics in laser metal additive manufacturing

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TLDR
In this article, Zhao et al. reported in-situ characterization of melt-flow dynamics in every location of the entire melt pool in laser metal additive manufacturing by populous and uniformly dispersed micro-tracers through high-resolution synchrotron x-ray imaging.
Abstract
Melt flow plays a critical role in laser metal additive manufacturing, yet the melt flow behavior within the melt pool has never been explicitly presented. Here, we report in-situ characterization of melt-flow dynamics in every location of the entire melt pool in laser metal additive manufacturing by populous and uniformly dispersed micro-tracers through in-situ high-resolution synchrotron x-ray imaging. The location-specific flow patterns in different regions of the melt pool are revealed and quantified under both conduction-mode and depression-mode melting. The physical processes at different locations in the melt pool are identified. The full-field melt-flow mapping approach reported here opens the way to study the detailed melt-flow dynamics under real additive manufacturing conditions. The results obtained provide crucial insights into laser additive manufacturing processes and are critical for developing reliable high-fidelity computational models.

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Journal ArticleDOI

Direct Observation of Pore Formation Mechanisms during LPBF Additive Manufacturing Process and High Energy Density Laser Welding

TL;DR: In this article, the pore formation mechanism during the laser powder bed fusion (LPBF) process is investigated. And the results provide direct evidence and insight into pore forming mechanisms during the LPBF process, which may guide the development of pore elimination/mitigation approaches.
Journal ArticleDOI

Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks

TL;DR: In this article, a physics-informed neural network (PINN) framework was proposed to predict the temperature and melt pool dynamics during metal additive manufacturing (AM) processes with only a moderate amount of labeled data sets.
Posted Content

Machine learning for metal additive manufacturing: Predicting temperature and melt pool fluid dynamics using physics-informed neural networks

TL;DR: The investigations show that the PINN, owed to the additional physical knowledge, can accurately predict the temperature and melt pool dynamics during metal AM processes with only a moderate amount of labeled data-sets.
Journal ArticleDOI

In situ design of advanced titanium alloy with concentration modulations by additive manufacturing.

TL;DR: Additive manufacturing is a revolutionary technology that offers a different pathway for material processing and design as mentioned in this paper, however, innovations in either new materials or new processing technologies have not yet materialized.
Journal ArticleDOI

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

TL;DR: In this paper, the authors present an updated review of the literature on in-situ sensing, measurement and monitoring for metal PBF processes, with a classification of methods and a comparison of enabled performances, summarising the types and sizes of defects that are practically detectable while the part is being produced and the research areas where additional technological advances are currently needed.
References
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Journal ArticleDOI

Additive manufacturing of metallic components – Process, structure and properties

TL;DR: A review of the emerging research on additive manufacturing of metallic materials is provided in this article, which provides a comprehensive overview of the physical processes and the underlying science of metallurgical structure and properties of the deposited parts.
Journal ArticleDOI

Laser powder-bed fusion additive manufacturing: Physics of complex melt flow and formation mechanisms of pores, spatter, and denudation zones

TL;DR: In this paper, the effect of the recoil pressure and Marangoni convection in laser powder bed fusion (L-PBF) of 316L stainless steel was demonstrated. And the results were validated against the experiments and the sensitivity to laser absorptivity was discussed.
Journal ArticleDOI

Keyhole threshold and morphology in laser melting revealed by ultrahigh-speed x-ray imaging

TL;DR: The direct visualization of the keyhole morphology and dynamics with high-energy x-rays shows that (i) keyholes are present across the range of power and scanning velocity used in laser powder bed fusion; and (ii) there is a well-defined threshold from conduction mode to keyhole based on laser power density.
Journal ArticleDOI

Real-time monitoring of laser powder bed fusion process using high-speed X-ray imaging and diffraction

TL;DR: The high-speed synchrotron hard X-ray imaging and diffraction techniques used to monitor the laser powder bed fusion (LPBF) process of Ti-6Al-4V in situ and in real time demonstrate that many scientifically and technologically significant phenomena in LPBF, including melt pool dynamics, powder ejection, rapid solidification, and phase transformation, can be probed with unprecedented spatial and temporal resolutions.
Journal ArticleDOI

In situ X-ray imaging of defect and molten pool dynamics in laser additive manufacturing

TL;DR: A mechanism map for predicting the evolution of melt features, changes in melt track morphology from a continuous hemi-cylindrical track to disconnected beads with decreasing linear energy density and improved molten pool wetting with increasing laser power is developed.
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