4.7 Article

Towards predicting differences in fatigue performance of laser powder bed fused Ti-6Al-4V coupons from the same build

期刊

INTERNATIONAL JOURNAL OF FATIGUE
卷 126, 期 -, 页码 284-296

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijfatigue.2019.05.004

关键词

Powder bed fusion; Selective laser melting; Ti-6Al-4V; Size effect; Build defects; Fatigue performance; Thermal modeling

资金

  1. ONR [N000141712035]
  2. Cornell University Biotechnology Resource Center via NIH [IS10OD012287]
  3. National Science Foundation (NSF) [1657195]
  4. U.S. Department of Defense (DOD) [N000141712035] Funding Source: U.S. Department of Defense (DOD)

向作者/读者索取更多资源

The mechanical performance of powder bed fused (PBF) components can vary significantly, even within a single build with processing parameters kept constant. To better understanding this variability, two sets of uniaxial fatigue specimens were examined, differing only in gage section surface area and location on the build plate. Significantly different fatigue performance was observed between the two geometries, despite being manufactured in the same laser power bed fusion (L-PBF) build. Possible explanations for the difference in fatigue performance were then examined, such as mechanical interactions between fatigue cracks and the specimen geometry, microstructure, surface roughness, increased surface area, and build defects. Differences in the density of near surface build defects were identified as the cause of the difference in fatigue performance between the two sets of specimens. The difference in fatigue performance was found to be predictable from a simple weakest link model given knowledge of the ratio of defect densities. Subsequently, an attempt was made to predict the difference in defect densities using a full resolution thermal model. The model results suggest additional details such as the nonuniformity in powder spreading, laser-plume interactions, and/or the interference of debris from previously scanned tracks may be necessary ingredients for process-structure-performance predictions of fatigue critical PBF components.

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