Christoph Kenel

TL;DR: In this paper, gas-atomized powders of two ternary alloys, Al-3.60Mg-1.18Zr and Al 3.57Zr, were densified via laser powder bed fusion.

TL;DR: In this paper, the authors investigated the feasibility of using acoustic emission for quality monitoring and combined a sensitive acoustic emission sensor with machine learning, where the acoustic signals were recorded using a fiber Bragg grating sensor during the powder bed additive manufacturing process in a commercially available selective laser melting machine.

TL;DR: In this article, a hybrid additive manufacturing process based on the integration of Laser Shock Peening (LSP) with selective laser melting (SLM) is described. But the authors do not consider the effect of residual stresses in the as-built (AB) state of SLM parts in the subsurface region.

TL;DR: This paper is a supplement to existing studies in this field and proposes a unique combination of highly sensitive acoustic sensor and machine learning for process monitoring of AM processes since it requires minimum modifications of commercially available industrial machines.

TL;DR: In this paper, the phase evolution of Ti-6Al-4V was observed in real-time by combining in situ X-ray diffraction and high-speed imaging to monitor phase evolution upon cyclic rapid laser heating and cooling.