READ ME File For 'Effects of rescanning parameters on densification and microstructural refinement of 316L stainless steel fabricated by laser powder bed fusion'

Dataset DOI: 10.5258/SOTON/D2084

ReadMe Author: Anqi Liang, University of Southampton

This dataset supports the publication:
AUTHORS: Anqi Liang, Khee Siang Pey, Tomas Polcar, Andrew R. Hamilton
TITLE: Effects of rescanning parameters on densification and microstructural refinement of 316L stainless steel fabricated by laser powder bed fusion 
JOURNAL: Journal of Materials Processing Technology
PAPER DOI IF KNOWN: 


This dataset contains:

Original data of plots in accepted manuscript

The figures are as follows:

Fig. 4  (a) Average width and (b) depth of single laser scan tracks with different linear energy densities and laser powers.
Fig. 6  Cell size of single laser scan tracks with different linear energy density and laser power.
Fig. 8  Predicted and measured depths of melt pools from single laser scans as a function of the linear energy density, P/v.
Fig. 9  Cooling rate, G×R, expressed as a function of the linear energy density, P/v.
Fig. 10  The experimentally measured cell size obtained with CL M2 printer and calculated cell size based on empirical equations are shown as a function of predicted cooling rate.
Fig. 11  Density of five cubes produced via different processing parameters measured by both Archimedes method and optical microscopy.
Fig. 13  Cell size for five cubes processed using parameter A1–A5, as indicated.
Fig. 15  Optical micrograph measurements of local density at regions with 20 layers of rescanning in specimen A+B1, A+B2, A+B3 and A+B4 compared with a uniform sample processed with initial parameter A only.
Fig. 18  Measured and predicted cell sizes for both initial scanning and rescanning regions using parameter A+B1, A+B2, A+B3, A+B4.

Date of data collection: Janurary 2019 to December 2020

Information about geographic location of data collection: University of Southampton, U.K.

Related projects:

Microstructural engineering for enhanced fatigue performance using laser powder bed fusion

Date that the file was created: Janurary 2021