Effects of volumetric energy density on defect structure and fatigue behaviour of powder bed fusion manufactured 316L stainless steel

Three structures of AISI 316L austenitic stainless steel were additively manufactured using the laser beam powder bed fusion (PBF-LB) process with varying volumetric energy density (VED) levels: low (50.8 J/mm³), medium (79.4 J/mm³), and high (84.3 J/mm³). The impact of VED on defects, microstructure, and fatigue behaviour was investigated and compared to wrought 316L steel. Various novel techniques were used to analyse the grain structure and defects. Fatigue behaviour was assessed through low and high cycle fatigue tests and tensile tests at room temperature. Results showed that increasing VED improved material density (from 91.8 % to 99.6 %) and reduced defect size and complexity. Both lack of fusion (LoF) and pore-type defects were identified, with fewer and less complex LoF defects at higher VED. Defects were primarily located at subsurface regions corresponding to the border hatch-fill contour layer. Printed structures exhibited lower high cycle fatigue (HCF) strength than wrought steel, but this difference diminished in low cycle fatigue (LCF) regimes for medium and high VED structures, where twinning and martensitic transformation enhanced fatigue strength. The defect characteristics significantly influenced HCF strength, and achieving a fatigue limit comparable to wrought steel requires very low defect density even at high VED.

Authors

Institutions

Publication Details

Journal
Materials Science and Engineering A
Published
2025-01-16
DOI
https://doi.org/10.1016/j.msea.2025.147868
Citations
18
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
12.84

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of volumetric energy density on defect structure and fatigue behaviour of powder bed fusion manufactured 316L stainless steel

Matias Jaskari, Atef Hamada, Tarek Allam, Sumit Ghosh et al.
18 citations
Materials Science and Engineering A
Additive Manufacturing Materials and Processes
12.84
article

Effects of volumetric energy density on defect structure and fatigue behaviour of powder bed fusion manufactured 316L stainless steel

Matias Jaskari, Atef Hamada, Tarek Allam, Sumit Ghosh, Antti Järvenpää, L.P. Karjalainen, Krzysztof Dzięcioł, Ruth Schwaiger
article en
18 citations

Abstract

Three structures of AISI 316L austenitic stainless steel were additively manufactured using the laser beam powder bed fusion (PBF-LB) process with varying volumetric energy density (VED) levels: low (50.8 J/mm³), medium (79.4 J/mm³), and high (84.3 J/mm³). The impact of VED on defects, microstructure, and fatigue behaviour was investigated and compared to wrought 316L steel. Various novel techniques were used to analyse the grain structure and defects. Fatigue behaviour was assessed through low and high cycle fatigue tests and tensile tests at room temperature. Results showed that increasing VED improved material density (from 91.8 % to 99.6 %) and reduced defect size and complexity. Both lack of fusion (LoF) and pore-type defects were identified, with fewer and less complex LoF defects at higher VED. Defects were primarily located at subsurface regions corresponding to the border hatch-fill contour layer. Printed structures exhibited lower high cycle fatigue (HCF) strength than wrought steel, but this difference diminished in low cycle fatigue (LCF) regimes for medium and high VED structures, where twinning and martensitic transformation enhanced fatigue strength. The defect characteristics significantly influenced HCF strength, and achieving a fatigue limit comparable to wrought steel requires very low defect density even at high VED.

Materials Science and Engineering AVol. 925
Suez University (EG), Forschungszentrum Jülich (DE), VATT Institute for Economic Research (FI), University of Oulu (FI)
Business Finland
Affordable and clean energy
Openalex Percentile: Top 1%
Additive Manufacturing Materials and Processes
12.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.