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portfolio

publications

research

Mitigating stray grains in laser-melting of CMSX-4 single crystal superalloy

Published:

High weld speeds and low powers minimize the amount of stray grains and maximize the epitaxial single crystal growth in traditional laser welding process. We extends the analytical solidification modeling applied in welding to laser melting with conditions representative of laser powder bed fusion (LPBF) additive manufacturing (AM) process. LPBF features higher laser powers and lower scanning speeds compared with welding which shows a potential to further decrease the amount of stray grains and therefore print single crystal components.

Deep Learning Approaches for Time-Resolved Laser Absorption Prediction

Published:

The quantification of the amount of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additively manufactured metal components. The geometry of a vapor depression, also known as a keyhole, in melt pools formed during laser melting is closely related to laser absorptivity. This relationship has been observed by the state-of-the-art in situ high speed synchrotron x-ray visualization and integrating sphere radiometry. These two techniques create a temporally resolved dataset consisting of keyhole images and the corresponding laser absorptivity. It is then possible to use deep learning techniques to predict absorption for keyhole x-ray images, reducing dependence on costly direct experimental measurements and multi-physics modeling.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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