Cooling dynamics of two titanium alloys during laser powder bed fusion probed with in situ X-ray imaging and diffraction

Materials & Design

Vivek Thampy¹  Aiden A. Martin²  Jenny Wang²  Philip J. Depond²  Manyalibo J. Matthews²  Anthony Y. Fong²  Rishi Ganeriwala²  Tien T. Roehling²  Nicholas P. Calta²  Johanna Nelson Weker³  Andrew M. Kiss³  Kevin H. Stone³  Duncan R.C. Lee³  Michael F. Toney³  Anthony W. Van Buuren³  Christopher J. Tassone³ 

[1] Corresponding authors.;Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, USA;SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025, USA;

关键词: Additive manufacturing;    Titanium alloys;    X-ray diffraction;    Rapid solidification;    X-ray imaging;    Laser powder bed fusion;   

DOI  :  

来源: DOAJ

【 摘 要 】

Metal parts produced by laser powder bed fusion (LPBF) additive manufacturing exhibit characteristic microstructures comparable to those observed in laser welding. The primary cause of this characteristic microstructure is rapid, localized heating and cooling cycles, which result in extreme thermal gradients where material solidification is followed by fast cooling in the solid state. The final microstructure and mechanical performance are also influenced by pore formation caused by melt pool fluid dynamics. Here, we use high speed, in situ X-ray diffraction to probe the kinetics of cooling and solid-solid phase transitions after laser melting in two aerospace titanium alloys: Ti-6Al-4V, an α + β alloy; and Ti-5Al-5V-5Mo-3Cr, a near-β alloy. We complement these diffraction studies with in situ X-ray imaging to probe melt pool dynamics and pore formation. From these two complementary probes, we quantify pore formation during melting and the subsequent microstructural evolution as the material rapidly cools after solidification. These results are critical for understanding defect formation and residual stress development in different titanium alloys under LPBF conditions and can help inform process models to predict final part performance.

【 授权许可】

Unknown